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 tjboudreaux/cc-plugin-product-strategist --skill product-opportunity-mappinggit clone --depth 1 https://github.com/tjboudreaux/cc-plugin-product-strategistWrote 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/tjboudreaux/cc-plugin-product-strategist/product-opportunity-mapping)<a href="https://agentmods.dev/skills/tjboudreaux/cc-plugin-product-strategist/product-opportunity-mapping"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-plugin-product-strategist/product-opportunity-mapping/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/tjboudreaux/cc-plugin-product-strategist/product-opportunity-mapping"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-plugin-product-strategist/product-opportunity-mapping.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 | $0.00028 | $0.00331 |
| Opus 5 | $0.00014 | $0.00166 |
| Sonnet 5 | $0.00006 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
product-opportunity-mapping 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.
What it actually says
Opportunity Landscape Mapping
Intent
- Detect emerging wants, friction points, and timing windows across consumer categories, platforms, and geographies.
- Translate diffuse signals into crisp problem statements and opportunity theses.
Inputs
- Macro trend library (culture, tech, regulatory, commerce, creator economy, web3, gaming).
- Behavioral data: search terms, app store reviews, social chatter, marketplace data, support tickets.
- Jobs-to-be-done interviews or transcripts.
Workflow
- Frame the arena
- Define target segment, contexts of use, and competing alternatives.
- Capture constraints (distribution, tech stack, platform rules).
- Signal harvesting
- Pull at least three independent data sources (quant + qual).
- Tag signals by magnitude (market size), urgency, and underserved intensity.
- Opportunity scoring
- Score each thesis on desirability, feasibility, timing, and strategic fit (0–5 scale).
- Highlight contrarian or under-served jobs with high desirability but low current satisfaction.
- Narrative articulation
- Produce a one-page brief: user tension, evidence, why-now drivers, first wedge.
- List unknowns that require experiments vs. desk research.
Verification
- Ensure each opportunity thesis cites at least two evidentiary sources.
- Review scores with a peer strategist or PM for bias.
- Archive briefs in shared knowledge base for reuse.
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 · 35 lines · 28 tokens per session scan A 4d8e7da2f5cd
product-opportunity-mapping is a skill published in the GitHub repository tjboudreaux/cc-plugin-product-strategist (2 stars, last pushed 7mo ago), licensed MIT. It adds 28 tokens to every session and 331 once invoked, about $0.0001 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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