Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add product-on-purpose/pm-skills --skill discover-market-sizinggit clone --depth 1 https://github.com/product-on-purpose/pm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/product-on-purpose/pm-skills/discover-market-sizing)<a href="https://agentmods.dev/skills/product-on-purpose/pm-skills/discover-market-sizing"><img src="https://agentmods.dev/badge/skills/product-on-purpose/pm-skills/discover-market-sizing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/product-on-purpose/pm-skills/discover-market-sizing"><img src="https://agentmods.dev/badge/skills/product-on-purpose/pm-skills/discover-market-sizing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00093 | $0.02876 |
| Opus 5 | $0.00046 | $0.01438 |
| Sonnet 5 | $0.00019 | $0.00575 |
| Haiku 4.5 | $0.00009 | $0.00288 |
Grade A, and why
discover-market-sizing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- discover-market-sizing — 95% identical, 16 lines differ
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Sizing
You produce a multi-framework market-sizing meta-analysis covering TAM (Total Addressable Market), SAM (Serviceable Addressable Market), and SOM (Serviceable Obtainable Market). You run all applicable sizing frameworks (top-down, bottom-up, comparable company, analogous market), compare where they converge and diverge, and synthesize a calibrated estimate with a recommendation. Divergence between frameworks is often the most valuable finding. Your job is to produce a defensible artifact and explain the reasoning.
Identity
- Phase skill (discover); Triple Diamond integration
- Single-turn lifetime; produces one artifact per invocation
- Read-only tools (Read, Grep, WebFetch, WebSearch) if available; no write outside the output artifact
- Outputs a markdown document with structured sections
Core principle
Multi-framework synthesis and epistemic discipline. Run all applicable frameworks; convergence across methods increases confidence, divergence is a finding to explain. Every dollar figure must trace to (a) a cited public source, (b) an explicitly-stated assumption with reasoning, or (c) a sensitivity range showing the bounds. Hand-wavy guesses are a P0 anti-pattern. When data is thin, offer a labeled lower-confidence estimate with explicit assumptions rather than refusing outright.
Scope: external market opportunity only. This skill sizes the market a product competes in - not internal-tool investment cases (time-savings x headcount x cost).
When NOT to Use
- You are sizing an internal-tool investment case (time saved x headcount x cost), not an external market -> compute the ROI directly; this skill covers external market opportunity only
- You need to rank or prioritize a list of features or initiatives, not size a market -> use
define-prioritization-framework - You need competitive positioning or a feature comparison, not TAM/SAM/SOM -> use
discover-competitive-analysis - You have not yet identified who the target customer is -> use
foundation-personafirst
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 229 lines · 93 tokens per session scan A 2a280410c51b
discover-market-sizing is a skill published in the GitHub repository product-on-purpose/pm-skills (663 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 2,876 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
idea-validator
Use when the user asks to validate a product idea, stress-test an idea, evaluate whether an idea is good, or decide whether to build something. Do NOT use for prioritizing an existing backlog or reviewing a shipped feature — those need RICE scoring or a design review instead.
product-designer
Use when the user asks to review a design, critique a UI or mockup, give design feedback, or check a screen for usability and accessibility issues. Do NOT use for visual brand or aesthetic preference debates, or for reviewing copy before layout is settled.
prompt-engineer
Use when the user asks to improve, optimize, rewrite, debug, or shorten a prompt, or asks why a prompt is producing bad output. Do NOT use for writing a Claude Code SKILL.md — that needs skill structure rules, not prompt techniques.
status-update-writer
Use when the user asks to write a status update, weekly or monthly update, stakeholder update, project update, standup, status report, or QBR. Do NOT use for writing a PRD or a retro doc — those need different structures.
linkedin-post-writer
Use when the user asks to write, draft, or rewrite a LinkedIn post, turn notes or an article into a LinkedIn post, or fix a hook that is not landing. Do NOT use for X/Twitter threads, newsletters, or blog posts — those need different length and hook rules.
spec-from-conversation
Turn an unstructured stakeholder conversation, Slack thread, or meeting transcript into a structured spec (problem, goals, non-goals, success metrics, open questions). Use whenever a PM has raw conversational input and needs a first-draft spec, or when someone says "can you turn this into a doc" after a discussion.…