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 Uxcel-Lab/product-skills --skill user-storygit clone --depth 1 https://github.com/Uxcel-Lab/product-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/uxcel-lab/product-skills/user-story)<a href="https://agentmods.dev/skills/uxcel-lab/product-skills/user-story"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/user-story/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/uxcel-lab/product-skills/user-story"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/user-story.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 | $0.00140 | $0.02488 |
| Opus 5 | $0.00070 | $0.01244 |
| Sonnet 5 | $0.00028 | $0.00498 |
| Haiku 4.5 | $0.00014 | $0.00249 |
Grade A, and why
pm-user-story 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 11d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Story Skill
How this skill behaves (read first)
This is a generative skill, and user stories are where requirements quietly turn back into a task list. The default move is to restate a feature as a story — "Add login feature," or the hollow "As a user, I want a button so I can submit" — describing what to build instead of who needs what and why. A real user story is a small, testable unit of user value, grounded in a real persona's need, that gives the team a shared who/what/why — and the discipline to not write one when it adds nothing the spec already says. So this skill gates:
- Establish whose need this is, whether it's real, and what the story feeds — a story with no grounded user is an assumption in costume.
- Apply the always-true core — frame from user value, keep the story small with detail pushed to acceptance criteria, make it INVEST/testable, map stories across the journey, and cut stories that add no clarity.
- Surface the context-dependent decisions (strict formula vs. free-form, write-a-story-at-all, acceptance-criteria depth, splitting into a map, communication framing) with trade-offs.
Then it hands off to pm-spec-quality-audit (which flags task-stories, untestable stories, and broken traceability) and pm-assumption-rigor-audit (is the user need evidenced or assumed?).
Scope: this skill owns the user-story artifact. It defers building the persona to pm-personas-jtbd, framing the underlying problem to pm-problem-statement, and the full spec/PRD and acceptance-criteria depth to pm-product-spec (audited by pm-spec-quality-audit). Agile ceremonies, backlog grooming, and sprint mechanics are out of scope.
Step 0 — Establish context before writing stories
Ask if not known; state the assumption if proceeding without an answer:
- Whose need is this, and is it real? A story starts from a research-grounded persona and a validated need — "As Maria, who has no time to configure settings…" beats "users prefer automation." If the persona or need is assumed, say so; an ungrounded story propagates the assumption into the backlog. (Build the persona in
pm-personas-jtbd.) - How complex is the need? A single discrete need fits the "As a [persona], I want [action], so that [benefit]" formula; a feature spanning multiple user types or layered benefits may need to be split or written free-form.
- Does a story add clarity the PRD/spec doesn't already have? If the team gets full context elsewhere, a story is documentation for its own sake. Write it only when it earns its place.
- What does it feed? A backlog, a spec, or an imminent sprint — this sets how much acceptance-criteria detail to attach now.
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.
- 11d ago First seen · 99 lines · 140 tokens per session scan A b7199d076dd7
pm-user-story is a skill published in the GitHub repository Uxcel-Lab/product-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 140 tokens to every session and 2,488 once invoked, about $0.0007 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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