Borrowing it
Nothing to install: this file belongs to robconery/kolea. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/robconery/kolea/main/.claude/skills/user-stories/SKILL.mdgit clone --depth 1 https://github.com/robconery/koleaWrote 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/robconery/kolea/user-stories)<a href="https://agentmods.dev/skills/robconery/kolea/user-stories"><img src="https://agentmods.dev/badge/skills/robconery/kolea/user-stories/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/robconery/kolea/user-stories"><img src="https://agentmods.dev/badge/skills/robconery/kolea/user-stories.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 | $0.00147 | $0.01443 |
| Opus 5.5 | $0.00059 | $0.00577 |
| Sonnet 5.5 | $0.00029 | $0.00289 |
| Haiku 4.5 | $0.00015 | $0.00144 |
Grade A, and why
user-stories 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 2mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- user-stories — 100% identical, 0 lines differ
- user-stories — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Stories
Turn product intent into a structured, testable backlog in /docs/STORIES.md. The
output is the input to the bdd-specs skill, so the structure here is not
cosmetic — it is a contract. Get the format right and stories flow into
executable specs and then code with no manual reshaping.
The pipeline you sit in
product intent ──▶ [user-stories] ──▶ /docs/STORIES.md ──▶ [bdd-specs] ──▶ spec files ──▶ code
bdd-specs reads /docs/STORIES.md and /docs/PLAN.md and generates nested
specs: Feature > Scenario > Specification, where each Scenario arranges its
data once and every Specification makes exactly one assertion, happy paths first
and exhaustively, sad paths in their own block.
So map deliberately:
| Story artifact | Becomes in bdd-specs |
|---|---|
| One story | One Feature |
| One acceptance criterion | One Scenario |
| Given / When / Then steps | The Scenario's arrange / act / assert |
| Each distinct Then | One Specification (one assertion) |
| Happy-path criteria | Listed first, exhaustively |
| Error / edge criteria | A separate "sad path" group |
Write acceptance criteria as Given/When/Then from the start. That single habit is what makes the handoff clean.
Workflow
1. Establish context before writing
A story carries product knowledge the codebase does not. Do not invent the role, the goal, or the value. If the user hands you a vague feature ("add notifications"), interview rather than guess:
- Who is this for? (the role — be specific: "billing admin", not "user")
- What do they want to do?
- Why — what outcome or pain does it address? A story whose "so that" is hollow ("...so that I can use the feature") is usually a task, not a story.
- What does done look like? What must be observably true?
- What is explicitly out of scope for this story?
Ask the smallest number of questions that unblock you. If the user says "just
draft it and I'll correct it", do that — draft, mark assumptions with
> ASSUMPTION: lines, and let them react. Reacting is faster than specifying.
What ships with it
2 files 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.
- 2mo ago First seen · 132 lines · 147 tokens per session scan A f15c6e8d3623
user-stories is a skill published in the GitHub repository robconery/kolea (11 stars, last pushed 28d ago), licensed MIT. It adds 147 tokens to every session and 1,443 once invoked, about $0.0006 per session on Opus 5.5. 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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