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 stanislavnianko/product-discovery-claude-skills --skill opportunity-mappinggit clone --depth 1 https://github.com/stanislavnianko/product-discovery-claude-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/stanislavnianko/product-discovery-claude-skills/opportunity-mapping)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/opportunity-mapping"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/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/stanislavnianko/product-discovery-claude-skills/opportunity-mapping"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/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 | $0.00067 | $0.01215 |
| Opus 5 | $0.00034 | $0.00607 |
| Sonnet 5 | $0.00013 | $0.00243 |
| Haiku 4.5 | $0.00007 | $0.00121 |
Grade A, and why
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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Opportunity Mapping
Part of the discovery-phase skill pack ·
synthesisgroup · readsdiscovery-context.md(runprofile-builderfirst if missing).
Turns the top pain points into opportunities and forces multiple candidate solutions before the team locks in. Two modes depending on whether the client already proposed a solution.
Step 1 — Read discovery context + insights
Read discovery-context.md (section 2. Product / Initiative → Solution already proposed by client — drives mode selection) and insight-matrix.md (anchors the tree against ranked insights).
If discovery-context.md is missing, ask the BA inline: "did the client propose a specific solution, or are we generating cold?" — picks Generate-mode vs Validate-mode; tag output [ASSUMED] on uncertainty. If insight-matrix.md is missing, ask: "name the top 1–3 pains in one sentence each" — or proceed with every leaf tagged [NO-EVIDENCE-ANCHOR]. Never block; recommend profile-builder / insight-synthesis for high-stakes work.
Step 2 — Pick mode
| Section 2 says | Mode |
|---|---|
| No solution proposed | Generate mode — open brainstorm of solutions |
| Solution proposed by client | Validate mode — frame the proposed solution as ONE candidate, generate 2-3 alternatives, force comparison |
Tell the BA which mode is active and why. In Validate mode, this skill's job is partly political: the team needs to walk into the proposal/SoW with evidence either supporting the client's solution OR proposing a better one — silence equals "yes" to the client's existing idea.
Step 3 — State the desired outcome
One sentence: metric + direction + timeframe. Pull from problem-canvas.md success signal, sharpened with insight-matrix evidence.
"Reduce time-to-first-value from 3 days to under 1 hour, this quarter."
Step 4 — Hang the opportunities
Each top-3 pain from insight-matrix becomes an opportunity branch. In user language, not solution language.
- ❌ "Add bulk import"
- ✅ "I spend 2 hours/day re-typing data from CSVs"
What ships with it
1 file 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 · 106 lines · 67 tokens per session scan A 683b684e95cd
opportunity-mapping is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 67 tokens to every session and 1,215 once invoked, about $0.0003 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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