AGENT SKILLBY MANOJBAJAJ95
Product market fit analysis
AT A GLANCE
Product market fit analysis is a go-to-market skill for AI agents. Expert framework for assessing and achieving product-market fit. It is published by manojbajaj95 in the manojbajaj95/claude-gtm-plugin GitHub repository (67 stars) under the MIT license. Install it with: npx skills add manojbajaj95/claude-gtm-plugin --skill product-market-fit-analysis
- SOURCE REPOSITORY
- manojbajaj95/claude-gtm-plugin (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 7.4 KB255 LINES
QUICK ANSWER
- WHAT IT IS01
- Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. The value is a focused slice of product market fit analysis judgment, useful when several similar skills cover the same ground.
- INPUTS02
- Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add manojbajaj95/claude-gtm-plugin --skill product-market-fit-analysisREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 36
Product Market Fit Analysis#
Workspace Context#
Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.
Operating Contract#
This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.
Comprehensive framework for assessing, achieving, and scaling product-market fit.
Quick Reference#
| Situation | Use This Skill For |
|---|---|
| Measuring PMF | Sean Ellis Survey |
| Retention analysis | Retention Curves |
| PMF validation | Leading Indicators |
| Segment-specific PMF | Segment Analysis |
| Scaling decisions | Post-PMF Strategy |
Part 1: What Is PMF?#
Definition#
Product-market fit is the condition where a product satisfies a strong market demand. It's not binary — it's a spectrum.
Key Insight#
PMF is obvious when you have it.
Matt MacInnis: "Product market fit is something where you absolutely know it when you see it. Therefore if you don't absolutely know it, you don't have it."
PMF Levels#
| Level | Customers | Focus |
|---|---|---|
| Nascent | 3-5 | Satisfaction |
| Developing | 5-25 | Demand |
| Strong | 25-100 | Efficiency |
| Extreme | 100+ | Scaling |
Part 2: PMF Measurement Frameworks#
Sean Ellis "Disappointment" Survey#
The Question:
"How would you feel if you could no longer use this product?"
- Very disappointed
- Somewhat disappointed
- Not disappointed
The Benchmark:
40% "very disappointed" = on the right track
Focus on the "very disappointed" segment as the core value indicator.
Retention Curves#
Uri Levine's Definition:
"Product market fit has one metric. Retention. If you create value, they will come back. If they're not coming back, you're not creating value."
What to look for:
- Curves that flatten over time (not decaying to zero)
- "Smile curve" — engagement increases over time (strongest signal)
Key retention points:
- Day 7 retention
- Day 30 retention
- Day 90 retention
Reference Customers#
Christian Idiodi:
"The holy grail is really a reference customer - somebody who loves it enough to tell people about it."
| Market | Target References |
|---|---|
| B2B | 6-8 reference customers |
| B2C | 15-25 reference customers |
Part 3: Leading Indicators#
Signs of True PMF#
| Indicator | What It Means |
|---|---|
| "Very disappointed" > 40% | Strong core value |
| Retention curve flattening | Product creates ongoing value |
| Customer "pull" | Market is pulling product |
| Outrage during outages | Product is mission-critical |
| Customer driving next steps | Intent, not polite interest |
Customer "Pull" Signals#
Raaz Herzberg:
"We felt the questions change — 'How are you pricing this? When can we start a POV?' That's real intent."
True pull is characterized by:
- Customers driving next steps
- Questions about pricing/timelines
- Urgency in communication
Outage Response Test#
Jeff Weinstein:
"During those 20 minutes our customers weren't furious. That was the signal we did not have product market fit."
If your product goes down and nobody notices or complains, you haven't solved a mission-critical problem.
Part 4: Segment-Specific PMF#
Key Insight#
Karri Saarinen: "The way we think about it is, 'Do we have the fit in specific segments?' and how strong that fit is."
PMF exists in segments, not universally.
Finding Your Segment#
Start narrow, then expand:
- Find PMF in one segment (e.g., early-stage startups)
- Double down where you see natural pull
- Expand to adjacent segments
Common Segments#
- Company size / stage
- Industry vertical
- Use case / workflow
- Geography
- Team size
Part 5: Distribution + PMF#
Critical Insight#
Casey Winters: "If you have a product that retains well and you can't find more users for it, I don't think that's product market fit."
True PMF requires:
- ✅ Retaining product
- ✅ Scalable, built-in distribution
Without both, you don't have true PMF.
Part 6: Pre-PMF Navigation#
What to Do Pre-PMF#
- Focus on retention, not acquisition
- Talk to every customer personally
- Iterate rapidly on product
- Find the segment with strongest pull
- Don't spend on paid acquisition
Warning Signs#
- Growth comes from "launch spikes" not organic
- Users aren't coming back
- No customers willing to be references
- Market is pushing product, not pulling
- You're guessing why users churn
Part 7: Post-PMF Scaling#
Protecting PMF#
Casey Winters: "Protecting what you've built is increasingly important once you build scale. You might fall out of product market fit in a year or five years if you're not continually making your product better."
Scaling Checklist#
- Retention curve has flattened (positive)
- Have target reference customers
- Clear segment with strongest fit
- Built-in distribution mechanism
- Team structure supports growth
PMF Can Be Lost#
Markets shift, competitors improve, user expectations rise. Continuously monitor and protect PMF.
Part 8: Questions to Assess PMF#
Diagnostic Questions#
- If users couldn't use your product anymore, what percentage would be 'very disappointed'?
- What does your retention curve look like at day 7, 30, and 90?
- Do you have customers willing to be references and tell others about you?
- Is the market pulling the product from you, or are you pushing it on them?
- Are customers driving next steps or just being politely interested?
- What specific segment do you have the strongest fit in?
Part 9: Common Mistakes#
What to Avoid#
| Mistake | Reality |
|---|---|
| Confusing launch spikes with PMF | Sustained organic growth matters |
| Ignoring retention data | If they don't come back, no PMF |
| Scaling too early | Paid growth before PMF burns cash |
| Conflating TAM with PMF | Large market ≠ fit within it |
| Listening to "somewhat disappointed" | Focus on "very disappointed" |
Part 10: Decision Framework#
Should You Scale?#
| Signal | Action |
|---|---|
| 40%+ "very disappointed" + flattening retention | Ready to scale |
| < 40% "very disappointed" | Keep iterating |
| No reference customers | Build them first |
| No distribution mechanism | Find channels first |
Scale vs. Iterate Decision#
| Factor | Scale | Keep Iterating |
|---|---|---|
| PMF survey | > 40% very disappointed | < 40% |
| Retention | Curve flattening | Decaying to zero |
| References | Target achieved | Not yet |
| Distribution | Channels identified | Unknown |
Related Skills#
- growth-strategy: For growth frameworks post-PMF
- customer-success-and-retention: For retention improvement
- conversion-rate-optimization: For activation optimization
FAQ
07 QUESTIONS
01What is the Product market fit analysis agent skill?
Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. It is listed under go-to-market in the 100xLab agent skills directory.
02How do I install Product market fit analysis in Cursor, Claude Code, or Codex?
Run npx skills add manojbajaj95/claude-gtm-plugin --skill product-market-fit-analysis in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Product market fit analysis, not every skill in the repository.
03What does the Product market fit analysis SKILL.md cover?
The SKILL.md includes sections on Workspace Context, Operating Contract, Quick Reference, Part 1: What Is PMF?, Definition and Key Insight. Read the full text on this page or in plain markdown at /resources/agent-skills/manojbajaj95-claude-gtm-plugin--product-market-fit-analysis--clvraf/raw.
04Which agents can use Product market fit analysis?
Product market fit analysis installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is Product market fit analysis under?
The manojbajaj95/claude-gtm-plugin repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is Product market fit analysis free to use?
Reading, copying and installing Product market fit analysis costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of Product market fit analysis?
Product market fit analysis comes from https://github.com/manojbajaj95/claude-gtm-plugin, which has 67 GitHub stars. The SKILL.md is at https://github.com/manojbajaj95/claude-gtm-plugin/blob/HEAD/skills/product-market-fit-analysis/SKILL.md. The author is manojbajaj95.
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ATTRIBUTION
Product market fit analysis was written by its original authors and is published in manojbajaj95/claude-gtm-plugin (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.