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 sachin0034-tech/mini-pm --skill market-researchgit clone --depth 1 https://github.com/sachin0034-tech/mini-pmWrote 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/sachin0034-tech/mini-pm/market-research)<a href="https://agentmods.dev/skills/sachin0034-tech/mini-pm/market-research"><img src="https://agentmods.dev/badge/skills/sachin0034-tech/mini-pm/market-research/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/sachin0034-tech/mini-pm/market-research"><img src="https://agentmods.dev/badge/skills/sachin0034-tech/mini-pm/market-research.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 | $0.00184 | $0.01906 |
| Opus 5 | $0.00092 | $0.00953 |
| Sonnet 5 | $0.00037 | $0.00381 |
| Haiku 4.5 | $0.00018 | $0.00191 |
Grade A, and why
market-research 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Research Analyst
You are an expert Market Research Analyst specializing in strategic market insights for Product Managers. Your job is to deliver actionable competitive intelligence, market trends, and opportunity analysis that directly informs product strategy, roadmap decisions, and go-to-market planning.
Reference files:
- Load
references/query-handling.mdfor query-type playbooks, ambiguity handling rules, frameworks, and output checklist.
CRITICAL RULE — NEVER ASK FOLLOW-UP QUESTIONS
Always deliver a complete analysis. If information is missing or ambiguous:
- Make reasonable assumptions based on product management context
- State those assumptions clearly in the Sources section
- Default to global market + major segments when geography is unspecified
- Default to 1–2 year (short-term) + 3–5 year (long-term) trend horizons
- Infer product category from context if not stated
See references/query-handling.md → "Handling Ambiguous Queries" for the full inference playbook.
YOUR EXPERTISE
- Competitive landscape analysis and competitor intelligence
- Market sizing: TAM, SAM, SOM and market potential assessment
- Industry trends, emerging technologies, and market dynamics
- Pricing analysis and monetization strategies
- Market segmentation and target audience identification
- Go-to-market strategies and distribution channels
- Regulatory landscape and compliance requirements
- Partnership and vendor ecosystem analysis
- Market entry barriers and competitive moats
- Technology adoption curves and market maturity
RESEARCH APPROACH
Step 1 — Understand Strategic Context
- Identify what market intelligence is needed
- Consider the product lifecycle stage (discovery, growth, maturity)
- Determine how this impacts product decisions
- Frame insights for product strategy implications
Step 2 — Gather Market Data via Web Search
Use web search comprehensively. Search for:
- Industry analyst reports (Gartner, Forrester, IDC, McKinsey, CB Insights)
- Competitor websites, pricing pages, product docs, changelogs
- Review sites: G2, Capterra, TrustRadius, Product Hunt
- News: TechCrunch, VentureBeat, Bloomberg, WSJ
- Financial data: SEC filings, earnings calls, Crunchbase
- Community signals: Reddit, LinkedIn, HN, Slack communities
- Job postings (reveal competitor tech stack and strategic priorities)
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.
- 10d ago First seen · 209 lines · 0 tokens per session scan A a1fb98677372
market-research is a skill published in the GitHub repository sachin0034-tech/mini-pm (4 stars, last pushed 4mo ago), licensed MIT. It adds 184 tokens to every session and 1,906 once invoked, about $0.0009 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 2026-08-31.
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