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 secondary-researchgit 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/secondary-research)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/secondary-research"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/secondary-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/stanislavnianko/product-discovery-claude-skills/secondary-research"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/secondary-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 | $0.00060 | $0.00960 |
| Opus 5 | $0.00030 | $0.00480 |
| Sonnet 5 | $0.00012 | $0.00192 |
| Haiku 4.5 | $0.00006 | $0.00096 |
Grade A, and why
secondary-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 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secondary Research
Part of the discovery-phase skill pack ·
evidencegroup · readsdiscovery-context.md(runprofile-builderfirst if missing).
Pull from published sources when primary research is constrained or unavailable. Standard tool for pre-sale discovery (no time/budget for primary), regulated domains (interview restrictions), and analogous-domain framing.
Step 1 — Read discovery context
Read discovery-context.md (sections 1. Client → Domain, 2. Product / Initiative, 6. Constraints) and problem-canvas.md if it exists.
If discovery-context.md is missing, ask the BA inline: "(a) client domain / sector; (b) any regulatory constraints (GDPR / HIPAA / SOC2 / none)?" — tag the output [ASSUMED DOMAIN]. Never block; recommend profile-builder for high-stakes work.
Step 2 — Decide research scope
| Scope | Signal |
|---|---|
| Industry baseline | "We need to know what 'normal' looks like" |
| Best practice / state-of-the-art | "What have leading orgs done about this?" |
| Regulatory / compliance | "What's required vs forbidden?" |
| Analogous domain | "No data in our domain — can we borrow from <adjacent>?" |
| Sizing / TAM | "Is the opportunity even commercially worth it?" |
A good secondary-research run usually picks 2-3 of these.
Step 3 — Delegate to web-research skills if available
If deep-research / exa-search / market-research are installed:
"Use
deep-researchfor<scope>in<client domain>. Surface:<3-5 sub-questions>. Output cited."
Without those, fall back to: industry analyst reports (Gartner, Forrester, McKinsey, BCG public excerpts), regulatory body publications (FDA, GDPR-EU, FCA, etc.), academic search (Google Scholar, arXiv), vendor whitepapers (treat with skepticism), conference proceedings, public earnings call transcripts (surprisingly rich for sizing).
Step 4 — Capture findings with provenance
Per finding, capture:
- Claim — the specific assertion
- Source — URL, title, author, date
- Source quality — primary research / analyst report / vendor blog / forum / academic
- Recency — within 12 months / 1-3 years / older
- Implication for our hypothesis — supports / contradicts / orthogonal
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 · 79 lines · 60 tokens per session scan A 9d4a3e020dde
secondary-research is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 60 tokens to every session and 960 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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