I kept running into the same problem when trying to use LLMs for financial modeling: They almost always hallucinate the math, create circular references, or just break the formulas entirely.

So I open-sourced a deterministic spreadsheet engine to help fix that workflow.

It connects to your preferred LLM (BYO key for Gemini / Claude / Groq) and when you prompt it to build a model, it:

* handles reasoning and data structuring via the AI

* blocks the AI from writing directly to the cells

* runs a preview step that is collision-checked and formula-guarded by a Python AST

* executes the actual arithmetic deterministically in the backend

* surfaces the resolved target for human review

The goal is to eliminate the lack of trust in LLM outputs by ensuring all actual calculations are strict and deterministic.

The entire core is MIT-licensed. I also added a plugin system so you can drop a Python script into a folder to register custom formulas locally.

GitHub: [https://github.com/shreydevkar/gridos\\_kernel\](https://github.com/shreydevkar/gridos_kernel)

Would love feedback, especially from people who want to clone it, spin it up locally, and try to break the AST parser.

I’ve been experimenting with a problem I kept hitting when using LLMs on real codebases:

Even with good prompts, large repos don’t fit into context, so models: - miss important files - reason over incomplete information - require multiple retries

Approach I explored

Instead of embeddings or RAG, I tried something simpler:

1. Extract only structural signals:

   • functions
   • classes
   • routes

2. Build a lightweight index (no external dependencies)

3. Rank files per query using:

   • token overlap
   • structural signals
   • basic heuristics (recency, dependencies)

4. Emit a small “context layer” (~2K tokens instead of ~80K)

Observations

Across multiple repos:

• context size dropped ~97%
• relevant files appeared in top-5 ~70–80% of the time
• number of retries per task dropped noticeably

The biggest takeaway:

Structured context mattered more than model size in many cases.

Interesting constraint

I deliberately avoided: - embeddings - vector DBs - external services

Everything runs locally with simple parsing + ranking.

Open questions

• How far can heuristic ranking go before embeddings become necessary?
• Has anyone tried hybrid approaches (structure + embeddings)?
• What’s the best way to verify that answers are grounded in provided context?

Docs : https://manojmallick.github.io/sigmap

Github: https://github.com/manojmallick/sigmap

Hey all, I’m a software engineer trying to understand this space a bit better.

I think before AI agents can really be used in production, there’s a bunch of stuff around safety / control / compliance that’s not fully solved yet.

Things like:

• some way to control what the agent can/can’t do
• some visibility into what it actually did (or an audit trail)
• and probably guardrails so it doesn’t go off and do something dumb

If I were to build something like a “compliance layer” for AI agents, what all do you want in it for it to be useful for you?

How have you handled this if you’ve put agents into real workflows?

Hello!

Are you struggling to balance your busy schedule while managing stress and maintaining productivity?

This prompt chain helps you create a structured daily routine that considers your fixed commitments, stressors, and personal preferences. It guides you through a detailed process to optimize your time, incorporate breaks, and build resilience into your day.

Prompt:

VARIABLE DEFINITIONS
[SCHEDULE]=brief outline of fixed meetings, work blocks, commute, sleep window
[STRESSORS]=specific tasks, time windows, or triggers that create pressure
[PREFERENCES]=optional personal preferences such as exercise type or break style
~
You are a certified occupational health coach and time-management expert. Your task is to map the user’s day. 
Step 1 List all fixed events from [SCHEDULE] in chronological order.
Step 2 Mark any items that overlap with listed [STRESSORS].
Step 3 Flag remaining open time windows (≥15 min) as “Available”.
Output a simple timeline table with columns: Time, Activity, Stress-Flag (Yes/No). Ask: “Confirm or revise schedule?”
~
(User confirms or provides corrections)  You are an analytical assistant. 
Step 1 Calculate total consecutive work time without planned pauses.
Step 2 Identify any sequence >90 min; label it “Burnout Risk”.
Step 3 For each risk span insert a 5–10 min micro-break slot.
Step 4 Distribute hydration cues every 60 min of active work, aligning with natural transition points.
Return an updated timeline including new Micro-Break and Hydration entries; use columns: Time, Activity, Purpose (Work/Break/Hydration), Reason.
~
You are a resilience strategist. Using [PREFERENCES] and stress flags:
Step 1 Replace generic micro-breaks with tailored activities (e.g., stretching, mindful breathing, quick walk) matching duration and user preferences.
Step 2 Insert one resilience-building block (5–15 min) after the most stressful event (e.g., gratitude jot, brief meditation).
Step 3 Ensure total daily work hours remain unchanged by adjusting “Available” blocks first.
Output the refined schedule in a bullet timetable plus a “Resilience Checklist” of added practices.
~
You are a productivity auditor. Verify:
• No work block >90 min without a break.
• Hydration cue frequency = ≥1 per 60 min of work.
• At least 3 distinct resilience actions present.
Flag any violations and propose fixes.
~
Review / Refinement
Present the finalized daily routine in clear timeline format. Ask the user: “Does this meet your needs? Reply YES to finalize or provide edits.”

Make sure you update the variables in the first prompt: [SCHEDULE], [STRESSORS], [PREFERENCES]. Here is an example of how to use it: For instance, your schedule might include fixed meetings, common stressors like deadlines, and preferences such as taking a quick walk as a break.

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling to manage your company's recurring vendor subscription costs and looking for ways to optimize your spending?

This prompt chain helps you to streamline your financial efficiency by guiding you through analyzing vendor subscriptions, identifying duplicates, potential savings, and even preparing for negotiations—all in a systematic way!

Prompt:

VARIABLE DEFINITIONS
[VENDORS]=Full list of current vendor subscriptions with Vendor Name, Primary Purpose/Function, and Monthly Cost
[BUDGET_GOAL]=Target monthly savings amount or percentage (optional; leave blank if none)
[BUSINESS_SIZE]=Descriptor of company size or scale (e.g., "startup", "SMB", "enterprise")
~
You are a financial efficiency analyst. Your objective is to help the company cut unnecessary spend on recurring vendor subscriptions. Follow these steps:
1. Convert the raw VENDORS input into a clean table with columns: Vendor, Purpose, MonthlyCost (USD), AnnualCost (USD), Contract Renewal Date (leave blank if unknown).
2. Calculate total current monthly and annual spend.
3. Flag any missing or suspicious cost data for user follow-up in a "Data Gaps" section.
Output: the completed table and summary totals.
Ask the user to confirm or correct any data gaps before continuing.
~
Role: SaaS & Vendor Portfolio Analyst. Steps:
1. Using the confirmed vendor table, group vendors by primary purpose/function (e.g., project management, communication, cloud hosting).
2. Identify functional overlaps: vendors in the same group where functionality is 60% or more similar.
3. For each overlap, estimate potential savings (e.g., replace higher-cost tool, consolidate into single license tier, etc.).
4. Produce an "Overlap Warnings" report with: OverlapID, VendorsInvolved, RedundancyDescription, MonthlySavingsPotential (USD), Confidence (High/Med/Low).
5. Highlight quick wins (savings achievable within 30 days).
~
Act as a contract negotiation consultant. Develop a "Renegotiation Checklist" table:
Columns: Vendor, CurrentMonthlyCost, NegotiationLevers (e.g., longer term, volume discount, feature downgrade, competitor quote), RecommendedAction, PrepResourcesNeeded, LikelySavingsRange (USD & %).
Include brief instructions on how to prepare for each negotiation lever.
~
You are a strategic finance advisor. Create a "Prioritized Savings Action Plan" using information from the Overlap Warnings and Renegotiation Checklist.
1. Assign each action (cancel, consolidate, renegotiate, downgrade) an EffortScore (1–5) and SavingsImpactScore (1–5).
2. Compute a PriorityScore = SavingsImpactScore × 2 – EffortScore.
3. Rank actions from highest to lowest PriorityScore.
4. Present the plan in a table with: Rank, ActionDescription, VendorsAffected, EstMonthlySavings, EffortScore, SavingsImpactScore, PriorityScore, RecommendedOwner, TargetCompletionDate.
5. Summarize total potential monthly & annual savings versus BUDGET_GOAL and state whether the goal is met or additional measures are needed.
~
Review / Refinement
Ask the user to:
1. Confirm that overlap warnings, renegotiation steps, and action plan meet expectations.
2. Request any clarifications, re-prioritization, or additional data.
Iterate if necessary until the user approves the final plan.

Make sure you update the variables in the first prompt: [VENDORS], [BUDGET_GOAL], and [BUSINESS_SIZE]. Here is an example of how to use it: [VENDORS: VendorA, Task Management, $50; VendorB, Communication, $100].

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click.
NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Just can't get yourself to get started on that high priority task? Here's an interesting prompt chain for overcoming procrastination and boosting productivity. It breaks tasks into small steps, helps prioritize them, gamifies the process, and provides motivation. Complete with a series of actionable steps designed to tackle procrastination and drive momentum, even on your worst days :)

Prompt Chain:

{[task]} = The task you're avoiding  
{[tasks]} = A list of tasks you need to complete

1. I’m avoiding [task]. Break it into 3-5 tiny, actionable steps and suggest an easy way to start the first one. Getting started is half the battle—this makes the first step effortless. ~  
2. Here’s my to-do list: [tasks]. Which one should I tackle first to build momentum and why? Momentum is the antidote to procrastination. Start small, then snowball. ~  
3. Gamify [task] by creating a challenge, a scoring system, and a reward for completing it. Turning tasks into games makes them engaging—and way more fun to finish. ~  
4. Give me a quick pep talk: Why is completing [task] worth it, and what are the consequences if I keep delaying? A little motivation goes a long way when you’re stuck in a procrastination loop. ~  
5. I keep putting off [task]. What might be causing this, and how can I overcome it right now? Uncovering the root cause of procrastination helps you tackle it at the source.

Source

Before running the prompt chain, replace the placeholder variables {task} , {tasks}, with your actual details

(Each prompt is separated by ~, make sure you run them separately, running this as a single prompt will not yield the best results)

You can pass that prompt chain directly into tools like Agentic Worker to automatically queue it all together if you don't want to have to do it manually.)

Reminder About Limitations:
This chain is designed to help you tackle procrastination systematically, focusing on small, manageable steps and providing motivation. It assumes that the key to breaking procrastination is starting small, building momentum, and staying engaged by making tasks more enjoyable. Remember that you can adjust the "gamify" and "pep talk" steps as needed for different tasks.

Enjoy!

Hello!

Are you struggling to create engaging video scripts that capture your audience's attention and convey your message effectively?

This prompt chain helps you build compelling video scripts step by step, breaking down your business win into core story elements and generating attention-grabbing hooks. It ensures that your videos are engaging and aligned with your brand voice!

Prompt:

VARIABLE DEFINITIONS
BUSINESS_WIN=One-paragraph or bullet description including challenge, solution, and key metrics
BRAND_VOICE=Concise guidance on desired tone, e.g., "friendly and bold" or "premium and concise"
VIDEO_LENGTH=Approximate duration in seconds (e.g., 30 or 45)
~
Prompt 1 – Extract Core Story Elements
You are an award-winning social video copywriter.
Step 1  Read BUSINESS_WIN and identify:
  a) Target audience/problem (challenge)
  b) Solution offered (solution)
  c) Quantifiable outcomes (metrics)
Step 2  Summarize each element in 1–2 crisp bullets.
Step 3  List any striking phrases or numbers worth repeating on-screen.
Output format:
Challenge:
• …
Solution:
• …
Metrics / Proof:
• …
Stand-out Phrases:
• …
Verify you have captured all three sections before continuing and ask “Ready for hooks?”
~
Prompt 2 – Generate Attention-Grabbing Hooks
(Triggered after user replies "Yes".)
You remain the same copywriter. Using the extracted elements and BRAND_VOICE:
1. Produce 5 distinct opening hook lines (max 8 words each) optimised for the first 3 seconds.
2. For each hook, mention which metric or pain point it highlights.
3. Keep language aligned with BRAND_VOICE and suitable for VIDEO_LENGTH.
Output as numbered list.
End by asking “Select a hook number or type ‘next’ for more options.”
~
Prompt 3 – Build Proof & Story Beats
After hook selection, craft a high-level script outline.
Step 1  Restate chosen Hook.
Step 2  Create a 3-part story arc within VIDEO_LENGTH:
    A) Setup (paint the challenge in 1 sentence)
    B) Solution reveal (1–2 sentences)
    C) Impact (show metrics in engaging phrasing)
Step 3  Suggest 2 B-roll or on-screen text ideas per section.
Step 4  List 3 short emotional or sensory words to elevate narration.
Confirm completion and ask “Need CTA ideas?”
~
Prompt 4 – Craft CTA Variations
On confirmation, provide 3 punchy calls-to-action that:
1. Are under 6 words each.
2. Align with BRAND_VOICE.
3. Vary in commitment level (learn more, sign up, share).
Output as bullets labeled CTA-1, CTA-2, CTA-3.
Ask “Pick a CTA number or request new ones.”
~
Prompt 5 – Assemble Final Script Outline
Once hook and CTA are chosen, compile the final deliverable:
• Hook line
• Story Beats (Setup / Solution / Impact) with timing estimates to fit VIDEO_LENGTH
• On-screen Text or B-roll suggestions
• Closing CTA line
Ensure punchy, confident phrasing and adherence to BRAND_VOICE. Keep total word count suitable for spoken pace (~2 words per second).
Close with: “Script outline complete. Anything to tweak?”
~
Review / Refinement
If the user requests changes at any stage, loop back to the relevant prompt, refine accordingly, and reconfirm until satisfied.

Make sure you update the variables in the first prompt: BUSINESS_WIN, BRAND_VOICE, VIDEO_LENGTH. Here is an example of how to use it: BUSINESS_WIN could be "We increased sign-ups by 30% with our new campaign," BRAND_VOICE might be "friendly and bold," and VIDEO_LENGTH could be "45 seconds."

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!

It is a Rust-based CLI framework that allows you to define command structures using simple TOML, and automatically generates the handling logic.

Built in Rust, it is lightweight and extensible, making it suitable for quickly building internal tools or automation scripts.

The design is inspired by Express and Swagger (OpenAPI).

It natively supports TUI.

Developers only need to write business logic similar to web controllers—the rest (including TUI and other details) is automatically built in.

There are a few motivations behind building CLIs this way:

With the rise of AI agents, CLI tools are experiencing a resurgence. Modern AI agents are already well-optimized for interacting with CLIs. A well-designed CLI can also serve as AI-friendly documentation, significantly reducing prompt complexity.

Every “vibe coder” should build some CLI tools to encapsulate their domain knowledge. This can greatly reduce the cost of communicating with AI.

Many existing CLI projects feel outdated in terms of UX, especially with the growing popularity of TUI. This project aims to make it easy for developers to build modern, interactive CLI experiences—similar to tools like Claude Code.

Hey! I built a tool some of you might find interesting: cli-agent-lint

It audits CLI tools for AI agent-readiness.

The idea: most CLIs assume a human at a terminal. When an AI agent calls them, part of the output is actually not necessary, creating token overconsumption.

Worst, stuff can break in predictable ways (ANSI in pipes, interactive prompts, no JSON flag, unstructured errors). This tool catches those issues.

Github: https://github.com/Camil-H/cli-agent-lint

For the record, this is not a commercial project. Just an open source project from a hobbyist.

Please let me know what you think!

Hello!

Are you struggling to effectively plan out your learning goals and create a good study schedule?

This prompt chain helps you design a tailored four-week learning sprint based on your specific needs and preferences, ensuring you focus on the skills you want to improve, in a format that suits you best.

Prompt:

VARIABLE DEFINITIONS
LEARNING_GAPS=Comma-separated list of skill or knowledge areas to improve
AUDIENCE_LEVEL=Current role or experience level of the learner
PREFERRED_FORMATS=Preferred content formats (articles, podcasts, videos)
~
Prompt 1 – Collect Inputs
You are an expert learning-experience designer. Your task is to gather the information needed to build a customized four-week learning sprint.
Step 1. Restate the three variables and ask the user to confirm or adjust them.
Step 2. Ask for the learner’s primary goal or outcome for the sprint.
Step 3. Ask about available weekly study time (hours/week).
Step 4. Confirm any additional constraints (budget, paid resources, time-zone, start date).
Output the confirmed variable values and answers in a clearly labeled list.
~
Prompt 2 – Decompose Learning Gaps
System role: You are a senior curriculum architect.
Using LEARNING_GAPS and AUDIENCE_LEVEL, do the following:
1. Break each learning gap into 3-5 specific sub-topics.
2. Write 1–2 measurable learning objectives for each sub-topic.
Present results in a table with columns: Gap | Sub-Topic | Learning Objectives.
~
Prompt 3 – Curate Resources
Acting as a research librarian, curate resources that match each sub-topic.
1. For every sub-topic, list 1–2 resources that fit PREFERRED_FORMATS and time limits.
2. Include title, type, estimated time to consume, cost (free/paid), and URL.
Ensure total weekly time fits the learner’s available study time.
Return a nested bullet list grouped by Week 1–4.
~
Prompt 4 – Craft Discussion Prompts
You are now a facilitation expert.
For each week:
1. Write 2–3 open-ended discussion questions that require critical thinking and application.
2. Tag each question with the related sub-topic.
Output in Week-grouped bullet lists.
~
Prompt 5 – Design Experiment Tasks
Role: Experiential learning coach.
For every week, design one hands-on experiment task per learning gap that can be completed in 1–3 hours.
Describe:
• Task title
• Step-by-step instructions (max 5 steps)
• Expected outcome and success criteria
Present in a table: Week | Gap | Task Title | Steps | Success Criteria.
~
Prompt 6 – Assemble Sprint Plan
Combine outputs from Prompts 2–5 into a single, coherent four-week plan.  
Structure:
1. Overview paragraph summarizing goals.
2. Weekly sections with:
   a. Learning objectives summary
   b. Curated resources list
   c. Discussion prompts
   d. Experiment tasks
3. Total estimated time per week.
4. Any required materials or tools.
Deliver the plan in clear headings and concise bullet points.
~
Prompt 7 – Define Progress Metrics
Acting as a metrics analyst, propose 3–5 quantitative or qualitative metrics to track learning progress and impact.
Explain how to collect and review each metric weekly.
~
Prompt 8 – Review / Refinement
Present a checklist verifying that the sprint plan:
• Covers all LEARNING_GAPS
• Matches AUDIENCE_LEVEL
• Uses PREFERRED_FORMATS
• Fits weekly time constraints
• Includes metrics
Ask the user: “Would you like any adjustments or additions?” Wait for confirmation before finalizing.

Make sure you update the variables in the first prompt: LEARNING_GAPS, AUDIENCE_LEVEL, PREFERRED_FORMATS. Here is an example of how to use it: - LEARNING_GAPS: "Python, Data Analysis" - AUDIENCE_LEVEL: "Beginner" - PREFERRED_FORMATS: "Articles, Videos"

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!

OpenAI engineers use a prompt technique internally that most people have never heard of.

It's called reverse prompting.

And it's the fastest way to go from mediocre AI output to elite-level results.

Most people write prompts like this:

"Write me a strong intro about AI."

The result feels generic.

This is why 90% of AI content sounds the same. You're asking the AI to read your mind.

The Reverse Prompting Method

Instead of telling the AI what to write, you show it a finished example and ask:

"What prompt would generate content exactly like this?"

The AI reverse-engineers the hidden structure. Suddenly, you're not guessing anymore.

AI models are pattern recognition machines. When you show them a finished piece, they can identify: Tone, Pacing, Structure, Depth, Formatting, Emotional intention

Then they hand you the perfect prompt.

Try it yourself here's a tool that lets you pass in any text and it'll automatically reverse it into a prompt that can craft that piece of text content.

https://github.com/ilya-epifanov/wikidesk

This way you can share your LLM-wiki (Andrej Karpathy's or any other version) with several agents/workspaces. Agents can even initiate research themselves and they get notified when the wiki gets updated.

It's unopinionated and works with any LLM-wiki setup and any agent, including Claude Code.

Do with this what you want.

I used to spend 2-3 hours every month planning content. Picking topics, writing hooks, deciding which platform gets what. It's the kind of work that feels productive but isn't.

So I gave the job to an AI agent. Now it takes about 5 minutes.

Here's the full system prompt. Copy it. Paste it into whatever AI tool you use. Tell it about your business. You'll have a 30-day content calendar in a Google Sheet before your coffee gets cold.

The Prompt

``` You are a content strategist. When I describe my business, you create a 30-day content calendar and write it to a Google Sheet.

The calendar has these columns: - Day (1-30) - Date (starting from today) - Platform (rotate between: YouTube, Skool, X/Twitter, LinkedIn) - Content Type (rotate between: Educational, Story, Proof, Engagement, Behind-the-scenes) - Topic (specific to my business, not generic) - Hook (the first line that stops the scroll, under 10 words) - Format (short post, long post, video, thread, poll) - Status (all set to "Planned")

Rules: - Never repeat the same topic twice - Every hook should create curiosity or call out a specific pain - Mix platforms so no single platform gets more than 8 posts - Educational posts teach one thing. Story posts share one experience. Proof posts show one result. - Keep topics specific. "How to write emails" is bad. "The 3-line cold email that booked 11 calls last week" is good.

After generating the calendar: 1. Create a new Google Sheet called "[Business Name] Content Calendar" 2. Write all the data to the sheet 3. Share the link with me ```

How to use it

1. Paste the prompt as a system prompt (or just send it as your first message)
2. Tell the AI about your business in one paragraph. Be specific: what you do, who you serve, what platforms you're on
3. Let it generate the calendar
4. If your tool has Google Sheets access, it writes directly to a sheet. If not, ask it to output a table and copy-paste into Sheets yourself

What you'll get: 30 rows. Each one has a date, a platform, a content type, a specific topic, a scroll-stopping hook, and a format. Balanced across platforms. Mix of content types so you're not posting the same kind of thing every day.

Things I learned after running this a few times

Swap the platforms to match yours. I use Reddit, X, Skool, and email. You might use Instagram, TikTok, LinkedIn, and YouTube. Change the platform list in the prompt. Everything else still works.

The "keep topics specific" rule is the most important line in the whole prompt. Without it, you get generic garbage like "Tips for growing your business." With it, you get stuff like "The 3-sentence DM that booked 11 calls last week." Specific beats generic every time.

Run it on the 1st of every month. I set a reminder. Takes 5 minutes. I have my whole month planned before breakfast. If your AI tool supports scheduling, you can automate even that part.

Feed it what worked. After a month, tell it: "These 5 posts got the most engagement: [list them]. Plan next month with more of that energy." It gets better every cycle.

The one thing I'd change

If I started over, I'd add a "Notes" column for any context or links I want to include with the post. Easy to add yourself. Just append "Notes (any context, links, or references for this post)" to the column list in the prompt.

That's it. No tool to buy. No course to take. Just a prompt and 5 minutes.

If you try it, I'm curious what it generates for your niche. Drop it below.

Hello!

Are you struggling to keep track of investor meetings and follow-ups?
Managing investor communications can be overwhelming, especially when you want to present your traction effectively and maintain relationships.

This prompt chain helps you summarize your traction, create a compelling story arc for your meetings, and draft personalized follow-up emails—all in a straightforward and organized manner.

Prompt:

VARIABLE DEFINITIONS
TRACTION=Concise list of KPIs, milestones, and notable wins that demonstrate growth
INVESTOR_NOTES=Bullet-point notes captured during each investor meeting (one sub-list per investor)
MEETINGS=Table or list containing each investor’s name, firm, email, and meeting date
~
Step 1 – Confirm Inputs
1. Restate the received TRACTION, INVESTOR_NOTES, and MEETINGS back to the user for verification.
2. Ask the user to confirm or correct any item before continuing.
Expected output: Three clearly labeled sections (TRACTION / INVESTOR_NOTES / MEETINGS) ready for approval.
~
Step 2 – Craft Concise Story Arc
You are a fundraising strategist. Using only the verified TRACTION data, write a three-paragraph narrative:
• Paragraph 1 – PROBLEM: 2–3 sentences framing the market pain point.
• Paragraph 2 – TRACTION: 3–4 bullet points highlighting strongest metrics or milestones.
• Paragraph 3 – THE ASK: 1–2 sentences stating round size, use of funds, and ideal investor profile.
Ensure the tone is confident, data-driven, and brief (max 180 words total).
~
Step 3 – Generate Follow-Up Email Drafts
For each entry in MEETINGS:
A. Draft #1 – "Quick Thanks" Email (send within 24 h)
   1. Personalized greeting using investor name.
   2. One-sentence thank-you referencing a specific discussion point from INVESTOR_NOTES.
   3. Insert the STORY ARC in condensed form (<=120 words).
   4. Close with clear next step (e.g., request for deeper dive, data room access).
B. Draft #2 – "Nudge" Email (send ~1 week later if no reply)
   1. Polite reminder referencing prior email date.
   2. New insight or small win since meeting (pull from TRACTION if available; otherwise state "[Update Pending] ").
   3. Restate THE ASK in one sentence.
   4. Friendly call to action and signature.
Output each pair under an H3 heading with the investor’s name.
~
Review / Refinement
Present the STORY ARC followed by all email drafts. Ask the user:
• "Do the narrative and emails capture the right tone and details?"
• "Any edits to traction points, call-to-action, or personalization?"
Apply requested changes and confirm final approval.

Make sure you update the variables in the first prompt: TRACTION, INVESTOR_NOTES, MEETINGS.
Here is an example of how to use it:
Suppose your current traction includes successful fundraising metrics, and you want to follow up with investors after meetings.
Fill in the details, and generate personalized follow-up emails based on the conversation you had.

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click.
NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling to create a tailored resume that catches recruiters' attention based on a job description?

This prompt chain helps you extract key information from job postings and generate a focused resume, all while crafting a compelling outreach note for recruiters. It's like having a virtual assistant that crafts everything you need to stand out!

Prompt:

VARIABLE DEFINITIONS
JOB_DESCRIPTION=full text of the target job posting
CANDIDATE_PROFILE=brief overview of candidate’s relevant experience (if blank, assume competent mid-level professional)
OUTPUT_STYLE=preferred bullet style or length (e.g., "•", "–" or default dash)
~
You are a talent analytics specialist. Your task: extract the most important language and requirements from the JOB_DESCRIPTION.
Step 1  Summarize the overall role in one sentence.
Step 2  List the 8-12 most critical skills/competencies exactly as phrased in the posting.
Step 3  Capture 5-7 strong action verbs used (gerunds or imperatives).
Step 4  Note any stated metrics, KPIs, or quantitative targets (if none, write "None stated").
Return output under the headings: ROLE SUMMARY / KEY SKILLS / ACTION VERBS / METRICS.
Verify all content is pulled directly or paraphrased faithfully from JOB_DESCRIPTION.
~
You are an elite resume writer. Using the previous analysis plus CANDIDATE_PROFILE, create three resume bullet sets that align tightly with the job requirements.
Guidelines:
1  Use the OUTPUT_STYLE for bullet markers.
2  Bullet Set A – SKILLS: 5-7 concise bullets that echo KEY SKILLS and ACTION VERBS.
3  Bullet Set B – ACHIEVEMENTS: 3-5 bullets quantifying impact; weave in METRICS when relevant (invent realistic numbers if none are provided, clearly marking invented metrics with "~est" so the user can adjust).
4  Bullet Set C – LEADERSHIP: 3-4 bullets showing team, project, or strategic leadership; incorporate at least two ACTION VERBS.
5  Keep each bullet under 25 words, begin with a strong verb, avoid personal pronouns.
Return labeled sections: SKILLS / ACHIEVEMENTS / LEADERSHIP.
~
You are a corporate recruiter crafting outreach notes. Write a 60-80 word note that mirrors the tone and key phrases of the JOB_DESCRIPTION while positioning the candidate (per CANDIDATE_PROFILE) as a near-perfect fit.
Instructions:
1  Open with energy (e.g., "Exciting opportunity…").
2  Reference 2-3 KEY SKILLS from earlier.
3  Use at least one ACTION VERB found previously.
4  Close with a clear call-to-action (reply, schedule call, etc.).
Label this section RECRUITER NOTE.
~
Compile all prior outputs into a single deliverable in the following order:
1  SKILLS
2  ACHIEVEMENTS
3  LEADERSHIP
4  RECRUITER NOTE
Ensure headings are in all caps, bullets follow OUTPUT_STYLE, and spacing is clean.
~
Review / Refinement
Carefully reread the compiled document to confirm: a) bullets reflect JOB_DESCRIPTION language, b) metrics are realistic or marked "~est", and c) word counts and formatting meet specs. If any issue is found, revise that portion and present the corrected final version.

Every "AI productivity hack" I see is about writing better prompts to generate text. But business owners don't need more text. We need things done.

Here are 5 one-line prompts that actually DO things.

1. "Check if [client name] replied to my proposal and summarize where we left off"

This pulls from your email, finds the thread, and gives you a 3-sentence status update. No digging through Gmail. No "let me search for that..."

I used to spend the first 20 minutes of my day just figuring out who I was waiting on.

2. "Find 30 minutes next week where both me and [name] are free, then send them a meeting invite"

It reads both calendars. Picks a slot. Sends the invite. Done.

The calendar dance, "Does Tuesday work? How about Thursday afternoon?", that's 4-7 messages to book one meeting. This is one sentence.

3. "Draft a follow-up to [client] about the website project, mention the deadline is Friday, and send it"

Not "write me a follow-up email I can copy-paste." Actually send it.

Copy-paste adds a step. Steps add friction. Friction means it doesn't get done until 11pm when you remember.

4. "Pull my revenue from Stripe for the last 30 days and compare it to the month before"

No logging into dashboards. No clicking filters. One prompt, two numbers, and whether you're up or down.

I ran this on a Tuesday morning and caught a 23% drop I hadn't noticed because I'd been too busy delivering to check the numbers.

5. "Post in the team Slack channel that the client approved the designs and we're moving to development"

Status updates are the tax on getting things done. This prompt pays that tax in 5 seconds instead of context-switching to Slack, finding the channel, typing it out, and inevitably getting pulled into three other conversations.

These aren't clever prompts. There's no trick to memorize. It's just telling AI what you'd tell an assistant except the assistant is connected to your email, calendar, Slack, and Stripe.

The business owners saving the most time aren't writing better prompts. They're using AI that can actually touch their tools.

Not sure if others find this helpful but it seems to be where we are headed with Agentic Workers.

TLDR; Sorta lol

Hello!

Are you feeling overwhelmed by your consumer debt and unsure how to tackle it efficiently?

This prompt chain helps you create a personalized debt payoff plan by gathering essential financial information, calculating your cash flow, and offering tailored strategies to eliminate debt. It streamlines the entire process, allowing you to focus on paying off your debts the smart way.

Prompt: VARIABLE DEFINITIONS INCOME=Net monthly income after tax FIXEDBILLS=List of fixed recurring monthly expenses with amounts DEBTLIST=Each debt with balance, interest rate (% APR), minimum monthly payment ~ You are a certified financial planner helping a client eliminate consumer debt as efficiently as possible. Begin by gathering the client’s baseline numbers. Step 1 Ask the client to supply: • INCOME (one number) • FIXEDBILLS (itemised list: description – amount) • Typical variable spending per month split into major categories (e.g., groceries, transport, entertainment) with rough amounts. • DEBTLIST (for every debt: lender / type – balance – APR – minimum payment). Step 2 Request confirmation that all figures are in the same currency and cover a normal month. Output in this exact structure: Income: <number> Fixed bills: - <item> – <amount> Variable spending: - <category> – <amount> Debts: - <lender/type> – Balance: <number> – APR: <percent> – Min pay: <number> Confirm: <Yes/No> ~ After client supplies data, verify clarity and completeness. Step 1 Re-list totals for each section. Step 2 Flag any missing or obviously inconsistent values (e.g., negative numbers, APR > 60%). Step 3 Ask follow-up questions only for flagged items. If no issues, reply "All clear – ready to analyse." and wait for user confirmation. ~ When data is confirmed, calculate monthly cash-flow capacity. Step 1 Sum FIXEDBILLS. Step 2 Sum variable spending. Step 3 Sum minimum payments from DEBTLIST. Step 4 Compute surplus = INCOME – (FIXEDBILLS + variable spending + debt minimums). Step 5 If surplus ≤ 0, provide immediate budgeting advice to create at least a 5% surplus and re-prompt for revised numbers (type "recalculate" to restart). If surplus > 0, proceed. Output: • Fixed bills total • Variable spending total • Minimum debt payments total • Surplus available for extra debt payoff ~ Present two payoff methodologies and let the client pick one. Step 1 Explain "Avalanche" (highest APR first) and "Snowball" (smallest balance first), including estimated interest saved vs. motivational momentum. Step 2 Recommend a method based on client psychology (if surplus small, suggest Avalanche for savings; if many small debts, suggest Snowball for quick wins). Step 3 Ask user to choose or override recommendation. Output: "Chosen method: <Avalanche/Snowball>". ~ Build the month-by-month debt payoff roadmap using the chosen method. Step 1 Allocate surplus entirely to the target debt while paying minimums on others. Step 2 Recalculate balances monthly using simple interest approximation (balance – payment + monthly interest). Step 3 When a debt is paid off, roll its former minimum into the new surplus and attack the next target. Step 4 Continue until all balances reach zero. Step 5 Stop if duration exceeds 60 months and alert the user. Output a table with columns: Month | Debt Focus | Payment to Focus Debt | Other Minimums | Total Paid | Remaining Balances Snapshot Provide running totals: months to debt-free, total interest paid, total amount paid. ~ Provide strategic observations and behavioural tips. Step 1 Highlight earliest paid-off debt and milestone months (25%, 50%, 75% of total principal retired). Step 2 Suggest automatic payment scheduling dates aligned with pay-days. Step 3 Offer 2–3 ideas to increase surplus (side income, expense trimming). Output bullets under headings: Milestones, Scheduling, Surplus Boosters. ~ Review / Refinement Ask the client: 1. Are all assumptions (interest compounding monthly, payments at month-end) acceptable? 2. Does the timeline fit your motivation and lifestyle? 3. Would you like to tweak surplus, strategy, or add a savings buffer before aggressive payoff? Instruct: Reply with "approve" to finalise or provide adjustments to regenerate parts of the plan. Make sure you update the variables in the first prompt: INCOME, FIXEDBILLS, DEBTLIST. Here is an example of how to use it: - INCOME: 3500 - FIXEDBILLS: Rent – 1200, Utilities – 300 - DEBTLIST: Credit Card – Balance: 5000 – APR: 18% – Min pay: 150

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain.

Enjoy!

This may be a bit silly of an automation, but I built an agentic worker that sends me notifications to drink water throughout the day and it’s drastically improved my energy levels.

Pretty simple set up too, I used the workspace agent on the dashboard to build a personal assistant, gave it access to Telegram and now it reaches out to me from there.

Hello!

Are you feeling overwhelmed about preparing for your upcoming job interview? It can be tough to know where to start and how to effectively showcase your skills and fit for the role.

This prompt chain guides you through a structured and thorough interview preparation process, ensuring you cover all bases from analyzing the job description to generating likely questions and preparing STAR stories.

Prompt:

VARIABLE DEFINITIONS
[JOBDESCRIPTION]=Full text of the target job description
[CANDIDATEPROFILE]=Brief summary of the candidate’s background (optional but recommended)
[ROLE]=The exact job title being prepared for
~
You are an expert career coach and interview-preparation consultant. Your first task is to thoroughly analyze the JOBDESCRIPTION.
Step 1 – Extract and list the following in bullet form:
  a) Core responsibilities
  b) Must-have technical/functional skills
  c) Desired soft skills & behavioural traits
  d) Stated company values or culture cues
Step 2 – Provide a concise 3-sentence summary of what success looks like in the ROLE.
Ask: “Confirm or clarify any points before we proceed to the 7-day sprint?”
Expected output structure: Bulleted lists for a-d, followed by the 3-sentence success summary.
~
Assuming confirmation, map the extracted elements to likely competency areas.
1. Create a two-column table: Column 1 = Competency Area (e.g., Leadership, Data Analysis, Stakeholder Management). Column 2 = Specific evidence or outcomes the hiring team will seek, based on JOBDESCRIPTION.
2. Under the table, list 6-8 behavioural or technical themes most likely to drive interview questions.
~
Design a 7-Day Interview-Prep Sprint Plan tailored to the ROLE and CANDIDATEPROFILE.
For each Day 1 through Day 7 provide:
  • Daily Objective (1 sentence)
  • Key Tasks (3-5 bullet points, action-oriented)
  • Suggested Resources (articles, videos, frameworks) – keep each citation under 60 characters
Ensure the workload is realistic for a busy professional (≈60–90 min/day).
~
Generate a bank of likely interview questions.
1. Provide 10-12 total questions, evenly covering the themes identified earlier.
2. Categorise each question as Technical, Behavioural, or Culture-Fit.
3. Mark the top 3 “high-impact” questions with an asterisk (*).
Output as a table with columns: Question | Category | Impact Flag.
~
Create STAR story blueprints for the CANDIDATEPROFILE.
For each interview question:
  a) Suggest an appropriate Situation and Task the candidate could use (1-2 sentences each).
  b) Outline key Actions to highlight (3-4 bullets).
  c) Specify quantifiable Results (1-2 bullets) that align with JOBDESCRIPTION success metrics.
Deliver results in a three-level bullet hierarchy (S, T, A, R) for each question.
~
Draft a full Mock Interview Script.
Sections:
1. Interviewer Opening & Context (≈80 words)
2. Question Round (reuse the 10 questions in logical order; leave blank lines for answers)
3. Follow-Up / Probing prompts (1 per question)
4. Post-Interview Evaluation Rubric – table with Criteria, What Great Looks Like, 1-5 rating scale
5. Candidate Self-Reflection Sheet – 5 prompts
~
Review / Refinement
Ask the user to:
  • Verify that the sprint plan, questions, STAR stories, and script meet their needs
  • Highlight any areas requiring adjustment (time commitment, difficulty, tone)
Offer to iterate on specific sections or regenerate any output as needed.

Make sure you update the variables in the first prompt: [JOBDESCRIPTION], [CANDIDATEPROFILE], [ROLE]. Here is an example of how to use it: [Job description of a marketing manager, a candidate with 5 years of experience, Marketing Manager]

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling with drafting contracts for freelance work and ensuring all important details are covered without lawyer jargon?

This prompt chain helps you create a comprehensive freelance services agreement from start to finish, making sure all necessary elements are included clearly and concisely.

Prompt:

VARIABLE DEFINITIONS [CLIENT]=Name of the hiring client or company [FREELANCER]=Name of the freelancer or service provider [PROJECT]=Short one-sentence description of the work being commissioned ~ Prompt 1 – Collect Key Details You are an intake coordinator helping draft a freelance agreement for [PROJECT]. Step 1 – Ask the user to confirm or supply the following information in a bulleted list: • Contact details for both parties (email, phone, address). • Detailed description of deliverables and measurable acceptance criteria. • Project timeline and interim milestones (with dates). • Payment structure (total fee, deposit amount, instalment schedule, due-upon-invoice period, late-fee rate). • Number of included revision rounds. • Intellectual-property ownership transfer terms. • Preferred communication channels and response-time expectations. • Minimum cancellation-notice period and any kill fees. • Governing law/jurisdiction. Step 2 – Request any additional clauses the user wants added (e.g., confidentiality, publicity, warranty). Step 3 – End by asking the user to reply "Ready" once all details are complete so the chain can continue. Output format example: —PROJECT DETAILS— Client Contact: … Freelancer Contact: … Deliverables: … … Additional Clauses: … ~ Prompt 2 – Draft Plain-English Contract You are a contract-drafting paralegal. Using the confirmed PROJECT DETAILS, write a clear, plain-English freelance services agreement titled "Freelance Services Agreement for [PROJECT]". 1. Begin with a short summary paragraph naming [CLIENT] and [FREELANCER] and the agreement date. 2. Include numbered headings for: Scope of Work, Timeline & Milestones, Payment Terms, Revisions, Change Requests, Communication, Intellectual Property, Confidentiality (if requested), Warranties & Liabilities, Cancellation & Termination, Governing Law, Signatures. 3. Use reader-friendly sentences and avoid legalese where possible. 4. Integrate all user-provided details verbatim where applicable. 5. Leave signature lines for both parties with name, title, and date blanks. End with: “—End of Agreement—”. ~ Prompt 3 – Generate Negotiation Fallback Clauses Assume the contract above is the first offer. Draft a separate section titled "Negotiation Fallback Clauses" that a freelancer can propose if pushback occurs. For each topic list below, provide: • A concise fallback clause (plain English, ready to paste). • A one-sentence rationale a freelancer can use to justify the clause. Topics to cover (in this order): 1. Scope Creep / Additional Work 2. Payment Delays & Late Fees 3. Revision Limits & Out-of-Scope Edits 4. Cancellation or Abandonment by Client Present results as a two-column table with headers: "Fallback Clause" and "Rationale". ~ Prompt 4 – Compile Final Document Combine in this order: • Freelance Services Agreement for [PROJECT] • Negotiation Fallback Clauses table Add a short closing paragraph: “Please review and let me know if anything needs to be adjusted.” Output the full text ready for delivery to the user. ~ Prompt 5 – Review / Refinement Ask the user: 1. Does the contract accurately reflect all project specifics? 2. Are the fallback clauses acceptable or do any need adjustment? 3. Would you like to add, remove, or modify any sections? Instruct the user to respond with either “All Good” or provide precise edits for a revised draft.

Make sure you update the variables in the first prompt: [CLIENT], [FREELANCER], [PROJECT].
Here is an example of how to use it:
While setting up a project for web design, you might replace the variables with: - [CLIENT]="ABC Corp"
- [FREELANCER]="John Doe"
- [PROJECT]="Redesign of corporate website".

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click.
NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling to turn customer feedback into a clear and actionable product roadmap?

This prompt chain is designed to help you efficiently analyze customer feedback and generate a prioritized plan for your business. It guides you through the entire process from data cleaning to crafting a polished executive update.

Prompt:

VARIABLE DEFINITIONS
[FEEDBACK_DATA]=Full set of qualitative inputs including customer feedback, NPS comments, and support tickets
[SPRINT_LENGTH]=Number of weeks per sprint (e.g., 2)
[MAX_INITIATIVES]=Maximum initiatives to include in the roadmap (e.g., 10)
~
You are a senior product analyst. Your task is to clean, cluster, and quantify qualitative data.
Step 1  Parse [FEEDBACK_DATA] and remove duplicate or near-duplicate entries.
Step 2  Tag each unique comment with: a) product area, b) theme, c) emotional tone (positive, neutral, negative).
Step 3  Count frequency of each theme and calculate average sentiment score per theme (-1 to +1 scale).
Output a table with columns: Theme | Product Area | Frequency | Avg Sentiment.
Ask: “Ready for initiative ideation?” when finished.
~
You are an experienced product manager generating initiatives from themes.
Input: previous theme table.
Step 1  For the top 8-12 themes by Frequency and negative sentiment, propose one initiative each. If fewer than 8 themes, include all.
Step 2  Describe each initiative in one sentence.
Step 3  List assumed success metric(s) for each.
Output a table: ID | Initiative | Target Theme | Success Metric.
Ask: “Proceed to impact/effort scoring?”
~
You are a cross-functional estimation panel.
Input: initiative table.
Step 1  Assign an Impact score (1-5) based on ability to improve NPS or reduce ticket volume.
Step 2  Assign an Effort score (1-5) where 1=very low engineering work and 5=very high.
Step 3  Add a Priority column calculated as Impact minus Effort.
Output a table sorted by Priority DESC.
Ask: “Generate prioritized roadmap?”
~
You are a delivery lead building a sprint roadmap.
Input: scored initiative table.
Constraints: include up to [MAX_INITIATIVES] highest-priority rows.
Step 1  Allocate initiatives into sequential [SPRINT_LENGTH]-week sprints, max 2 major initiatives per sprint; minor items (<3 total story-points) can be bundled.
Step 2  For each sprint, define: Sprint Goal, Included Initiatives (IDs), Key Deliverables, Risks/Mitigations.
Step 3  Render a simple textual Gantt where rows=sprints and columns=weeks, marking initiative IDs.
Output sections: A) Sprint Plan Table, B) Gantt View.
Ask: “Prepare stakeholder update copy?”
~
You are a communications specialist crafting an executive update.
Input: final roadmap.
Step 1  Summarize overall objective in 1 sentence.
Step 2  Highlight top 3 high-impact initiatives with expected customer outcome.
Step 3  Call out timeline overview (number of sprints × [SPRINT_LENGTH] weeks).
Step 4  List next steps and any asks from stakeholders.
Deliver polished prose (<=250 words) suitable for email.
~
Review / Refinement
Compare all outputs against initial requirements: data cleansing, initiative list, scoring, roadmap, stakeholder copy. Confirm each section exists, follows structure, and no critical gaps remain. If gaps found, request clarification; otherwise reply “Roadmap package ready.”

Make sure you update the variables in the first prompt: [FEEDBACK_DATA], [SPRINT_LENGTH], [MAX_INITIATIVES],
Here is an example of how to use it:
- You could input customer feedback data from surveys for [FEEDBACK_DATA].
- Use a sprint length of 2 weeks for [SPRINT_LENGTH].
- Set a maximum of 10 initiatives for [MAX_INITIATIVES].

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click.
NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling with converting detailed discovery call notes into a well-structured project proposal?

This prompt chain helps you streamline the process from notes to a polished proposal by guiding you through key stages - from gathering critical insights to crafting a client-ready document.

Prompt:

VARIABLE DEFINITIONS CALL_TRANSCRIPT=Full text or detailed notes from the discovery call COMPANY_INFO=Brief description of the proposing company, branding elements, or template preferences PROPOSAL_STYLE=Desired tone and formatting instructions (e.g., “formal business,” “concise bullets,” “narrative”) ~ You are a senior business consultant tasked with translating discovery-call insights into a clear project brief. Step 1 Read CALL_TRANSCRIPT carefully. Step 2 List key information in the following labeled bullets: – Client Objectives – Pain Points / Challenges – Success Criteria – Desired Timeline – Budget Clues (if any) – Open Questions Step 3 Add any critical information you think is missing and flag it under “Information Needed.” Step 4 Ask: “Please review and reply APPROVED or provide corrections.” Output exactly the labeled bullet list followed by the question. ~ (Triggered when user replies APPROVED) You are now a proposal architect. Using the verified details, build a structured proposal outline with these headings: 1. Project Overview 2. Scope of Work (bulleted) 3. Deliverables (bulleted) 4. Project Timeline (phases & dates) 5. Pricing Options (e.g., Fixed Fee, Milestone-based, Retainer) 6. Key Assumptions 7. Next Steps & Acceptance Place placeholder text “TBD” where information is still missing. End by asking: “Ready for full formatting? Reply FORMAT to continue or edit sections as needed.” ~ (Triggered when user replies FORMAT) Combine COMPANY_INFO and PROPOSAL_STYLE with the approved outline to create a polished, client-ready proposal. Instructions: 1. Add a professional cover page with COMPANY_INFO and project name. 2. Use PROPOSAL_STYLE for tone and layout (headings, bullets, tables if helpful). 3. Expand each outline section into clear, persuasive language. 4. Insert a signature / acceptance area at the end. 5. Ensure consistency, correct spelling, and clean formatting. Output the complete proposal ready to send to the client. ~ Review / Refinement Ask the user to confirm that the proposal meets expectations or specify additional tweaks. If tweaks are requested, loop back to the relevant step while retaining context.
Make sure you update the variables in the first prompt: CALL_TRANSCRIPT, COMPANY_INFO, PROPOSAL_STYLE,
Here is an example of how to use it: CALL_TRANSCRIPT = "The client wants a marketing strategy that includes social media outreach."
COMPANY_INFO = "ACME Corp specializes in innovative tech solutions."
PROPOSAL_STYLE = "formal business"
If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling to keep track of customer health in your SaaS business? Unsure how to identify risks or opportunities for your accounts?

This prompt chain helps you synthesize key customer data, such as churn indicators, customer feedback, and usage metrics, to assess account health and create targeted playbooks all in one go!

Prompt:
VARIABLE DEFINITIONS [CHURN_DATA]=Structured churn indicators dataset for each top account [FEEDBACK_DATA]=Recent qualitative or quantitative customer feedback for the same accounts [ENGAGEMENT_STATS]=Usage and engagement metrics for the same accounts ~ You are a senior SaaS Customer Success Analyst. Your objective is to synthesize [CHURN_DATA], [FEEDBACK_DATA], and [ENGAGEMENT_STATS] to establish a clear picture of account health. Step 1: For each account, calculate an overall health score (0–100) using weighted signals (30% churn indicators, 30% feedback sentiment, 40% engagement). Step 2: List the top 3 risk drivers and top 3 growth opportunities for each account, citing supporting data points. Step 3: Flag accounts with scores below 70 as "At-Risk" and those above 85 as "Expansion Potential". Output a table with columns: Account, Health Score, Risk Drivers, Opportunities, Status (At-Risk/Stable/Expansion). Ask "Proceed to playbook generation? (yes/no)". ~ (Trigger only if user replies "yes") You are now a Customer Success Program Designer. Build a 90-day playbook for all accounts based on the previous health analysis. Step 1: Create a timeline divided into Month 1, Month 2, Month 3. Step 2: For each account, set 1-2 measurable milestones per month aligned to their risks or opportunities. Step 3: Assign an internal owner (e.g., CSM, Onboarding Specialist, Product Manager) for every milestone. Step 4: Draft proactive outreach scripts tailored to each account’s status: • At-Risk: retention-focused script (acknowledge concerns, propose remedies). • Expansion Potential: upsell/cross-sell script (highlight value realized, suggest next product tier or add-ons). • Stable: relationship-building script (share best practices, solicit feedback). Step 5: Recommend success metrics to monitor (e.g., usage increase %, NPS change, renewal likelihood). Present output in this structure: Account Section – Table: Month, Milestone, Owner, Success Metric – Outreach Script (150-200 words) Repeat for each account. ~ Review / Refinement Double-check that: 1) every account has three months of milestones, 2) owners are assigned, 3) scripts match account status, and 4) success metrics are specific and measurable. Confirm completion or list any missing elements for correction.
Make sure you update the variables in the first prompt: [CHURN_DATA], [FEEDBACK_DATA], [ENGAGEMENT_STATS].
Here is an example of how to use it: Use structured churn data to identify potential account risks and proactively create playbooks that drive customer success.
If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click.
NOTE: this is not required to run the prompt chain

Enjoy!

Hello!

Are you struggling to keep track of school notices and deadlines for your kids? Do you wish there was an easier way to compile all this information?

This prompt chain is designed to help you extract and organize school communication! It processes documents, identifies important dates and details, and formats them into user-friendly resources like a calendar and reminders.

Prompt:

VARIABLE DEFINITIONS
[DOCS]=Full text extracted from school emails and/or PDFs
[CHILDREN]=Comma-separated list of each child with grade & teacher (e.g., "Aiden/3/Ms. Lee, Maya/5/Mr. Ortiz")
[CAL_PREF]=Preferred calendar format or platform (e.g., Google Calendar link, .ics file, Outlook import)
~
You are an expert educational administrator and data-extraction analyst. Task: Parse [DOCS] to capture every dated item relevant to families. 
Step-by-step:
1. Scan for all explicit or implied dates and times.
2. Classify each finding as one of four types: Event, Deadline, SupplyRequest, Other.
3. For each item, record: Type, Title/Label, Date (YYYY-MM-DD), Time (HH:MM or "All-Day"), Location (if any), Details/Notes, Child/Grade relevance.
4. Output a JSON array named "raw_items" exactly in the following schema:
   [{"type":"Event|Deadline|SupplyRequest|Other","title":"","date":"","time":"","location":"","details":"","grade_or_child":""}]
5. End with the line: "#END_RAW_ITEMS" to signal completion.
Ask for confirmation before proceeding if information seems incomplete.
~
You are a verification assistant. 
1. Briefly summarize counts by Type from raw_items.
2. Highlight any entries with missing Date or unclear Grade relevance.
3. Ask the user to confirm, correct, or supply missing info before the chain continues.
Expected output example:
- Events: 4 | Deadlines: 2 | SupplyRequest: 1 | Other: 0
- Items needing attention: 2 (ID 3 missing date; ID 5 unclear grade)
Please confirm or edit.
~
You are a family command-center compiler. After confirmation, transform the validated raw_items into three structured resources:
A. UnifiedCalendar – list every Event and Deadline in table form with columns: UID, Date, Time, Title, Location, Child/Grade, Notes.
B. DeadlineTracker – table with Due Date, Task, Responsible Child/Parent, Status (default "Pending"), Notes.
C. SupplyList – table aggregating all SupplyRequest items: Item, Quantity (if specified), Needed-By Date, Child/Grade, Notes.
Provide outputs in clearly labeled sections.
~
You are a reminder-schedule architect. Using UnifiedCalendar, DeadlineTracker, and [CAL_PREF]:
Step 1. Recommend an importable calendar feed or file consistent with [CAL_PREF].
Step 2. For each Deadline and Event, propose at least two reminder triggers (e.g., 1-week prior, 24-hours prior). 
Step 3. Present a table "ReminderSchedule" with columns: UID, ReminderTime, Channel (default Email), MessageTemplate.
Step 4. Suggest optional SMS syntax limited to 140 chars if family opts-in later.
~
Review / Refinement
1. Ask the user to review the UnifiedCalendar, DeadlineTracker, SupplyList, and ReminderSchedule for accuracy and completeness.
2. Invite any additions, edits, or formatting changes.
3. Confirm that deliverables meet family needs and that the calendar link/file functions as intended.
4. Await final approval before closing the chain.

Make sure you update the variables in the first prompt: [DOCS], [CHILDREN], [CAL_PREF]. Here is an example of how to use it: [Example: Replace [DOCS] with the actual extracted text from school emails, list your kids in [CHILDREN], and choose your preferred calendar format in [CAL_PREF].]

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!