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 ljucask/pureinn-product-development --skill pm-market-analysisgit clone --depth 1 https://github.com/ljucask/pureinn-product-developmentWrote 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/ljucask/pureinn-product-development/pm-market-analysis)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-market-analysis"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-market-analysis/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/ljucask/pureinn-product-development/pm-market-analysis"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-market-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00041 | $0.05930 |
| Opus 5 | $0.00020 | $0.02965 |
| Sonnet 5 | $0.00008 | $0.01186 |
| Haiku 4.5 | $0.00004 | $0.00593 |
Grade A, and why
pm-market-analysis scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://api.openai.com/v1/responses \ How it starts
The opening of the file, as written. The whole thing — 593 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - Market Analysis
Agent mode (--agent)
Supports --agent: runs autonomously in a subagent, drafts the artifact from existing inputs, and returns a short summary + coverage note.
- No flag → interactive (default); if inputs are heavy, offer agent mode.
--agent→ obey. First check inputs are complete. Anything missing: do NOT invent it - mark[ASSUMED - what/why]in the output and summary. Never hallucinate to fill a gap.
What this skill does
Takes raw research input (Perplexity/ChatGPT market data, competitor research, manual observations) and produces four structured market artifacts:
- Market Size Analysis (TAM/SAM/SOM)
- Competitor Analysis
- SWOT Analysis
- Market Timing Rationale ("Why now?")
Three input paths: (A) paste your own research, (B) guided elicitation from domain knowledge, (C) AI-powered research via OpenAI web search (requires OPENAI_API_KEY in pureinn-variables.md).
Path A and C produce research-backed artifacts. Path B produces assumption-based output marked for validation.
Commissioned builds - whose market? When the build is commissioned by a client, this analysis targets the client's market and the client's competitors - not yours. TAM/SAM/SOM sizes their opportunity; the competitor set is who they compete with (and who their users compare them against). State this reframing explicitly at the top of the artifacts. Client-discovery meeting notes in meetings/ often already contain competitor mentions and market claims - read them (client claims tagged [CLIENT-ASSERTED]).
Dependencies
Recommended before running:
pm-project-charter- target segment and geography are defined there
Produces artifacts used by:
pm-problem-validation- market analysis is Track C inputpm-personas- segment data informs persona developmentpm-prd- market context is a key PRD sectionpm-product-roadmap- market sizing and timing feed into roadmap framing
Open questions
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 · 593 lines · 41 tokens per session scan A d26ec4174ce1
pm-market-analysis is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 5,930 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
ai-native-design
A workflow for turning a product brief and API contract into frontend design prompts and implementation guidance. It supports three outside design channels and keeps generated frontend work aligned with the same brief and contract.
backend-development
A set of instructions for building server-side code such as APIs and database-backed applications. It uses API contracts, data models, the chosen technology stack, and tests as the project’s reference points.
decision-gate
A decision checkpoint for software-project workflows. After each phase produces its files, it asks the user to accept the result, request a change, add information, or regenerate it before the next phase begins.
frontend-development
A set of instructions for building the user-facing part of a web application, such as its pages, controls, and interactions. It applies to single-page applications and follows the project’s API, product, technology, and design documents.
relay
A Chinese-language procedure for handing an unfinished task from one AI session to another without losing its context.
validation-loop
A development routine that checks each important file immediately after it is changed by running the project’s build, lint, type-check, or test commands.