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-discovery-interviewgit 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-discovery-interview)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-discovery-interview"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-discovery-interview/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-discovery-interview"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-discovery-interview.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 | $0.00105 | $0.05416 |
| Opus 5 | $0.00053 | $0.02708 |
| Sonnet 5 | $0.00021 | $0.01083 |
| Haiku 4.5 | $0.00011 | $0.00542 |
Grade A, and why
pm-discovery-interview 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 — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - Discovery Interview Prep
Agent mode (--agent)
Supports --agent: runs autonomously in a subagent, drafts the agenda 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
Prepares you for a live discovery session. It does NOT run the interview - the interview happens in the room, guided by the agenda this skill produces. This skill:
- Reads what discovery has already covered (prior
meetings/notes, Track A-D artifacts, the Discovery Report if one exists) - Builds a coverage map - which discovery areas are done, thin, or untouched
- Compiles a session agenda targeting the biggest gaps, with the actual questions, follow-ups, and techniques written out in full
- Saves the agenda to
meetings/prep/so it pairs with the meeting note thatpm-meetingproduces afterward
Self-contained (no external file needed): the complete question bank and technique library are embedded in this skill, in the Question bank section at the bottom. The skill depends on nothing outside itself - no companion document, no docs/ file. Run it standalone at any time: to compile a targeted agenda, to walk the full set of questions live with a client, or to proof-check your own idea by being your own toughest client.
Standalone agenda output: the agenda it produces is also self-contained - every question, follow-up, red-flag answer, and technique is written out in full, not referenced by module number. Print the agenda and walk into the session with nothing else; no laptop, no file, no Claude running during the session itself.
The coverage areas (module map)
Each area maps to a module in the Question bank below. Use this to decide what a session should target; pull the actual questions from the matching module.
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 · 346 lines · 105 tokens per session scan A 512ddc67f4df
pm-discovery-interview is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed yesterday), licensed MIT. It adds 105 tokens to every session and 5,416 once invoked, about $0.0005 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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