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-features-listgit 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-features-list)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-features-list"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-features-list/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-features-list"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-features-list.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 | $0.00098 | $0.08571 |
| Opus 5 | $0.00049 | $0.04286 |
| Sonnet 5 | $0.00020 | $0.01714 |
| Haiku 4.5 | $0.00010 | $0.00857 |
Grade A, and why
pm-features-list 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 — 717 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - Features List
Agent mode (--agent)
Supports --agent: runs autonomously in a subagent, drafts the artifact 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.- Review required: the artifact contains commitments - after drafting, require the user's review before finalizing; do not close decisions autonomously.
What this skill does
Phase 5 / Step 1-3. Takes the product scope from PRD Business Capabilities and produces:
- FDD Feature List (
features/feature_list.md) - Live Register 4. All features in FDD format ([Action] [Result] [Object]), organized in 3-level hierarchy: Domain -> Feature Set -> Feature. With actor, priority, dependencies, MVP flag, and stripe assignment. - Dependency Map - which features block which, critical path, parallelizable tracks
- KANO Analysis - must-be / performance / delighter / indifferent classification per feature
- Value vs. Complexity Matrix - Quick Win / Big Bet / Fill-in / Time Waster scoring per feature
- Stub Feature Cards - one per feature, created automatically in
/features/cards/FEAT-[DOMAIN]-[NUMBER].mdwith status1_Backlog
After user approval: push the complete feature inventory to Notion as the initial product backlog.
This is the direct input for pm-mvp-scope, which makes the MVP cut per feature and assigns features to Delivery Stripes.
Prioritization methods used
KANO Analysis
Classifies each feature by the type of value it delivers to the customer:
| Category | What it means | MVP implication |
|---|---|---|
| Must-be | Expected baseline - absence causes dissatisfaction, presence is not noticed | Always in MVP. Non-negotiable. |
| Performance | More = better. Customer notices and values improvements linearly. | Core differentiators. Include key ones in MVP. |
| Delighter | Unexpected positive surprise. Not expected but appreciated when present. | Post-MVP. Ship after Must-be and Performance are solid. |
| Indifferent | Customer does not care either way. | Cut. Do not build. |
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 · 717 lines · 98 tokens per session scan A fbc82a84110d
pm-features-list is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed today), licensed MIT. It adds 98 tokens to every session and 8,571 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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