Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/matteocervelli/llmsnpx agentmods add skills/matteocervelli/llms/user-story-generatorWrote 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/matteocervelli/llms/user-story-generator)<a href="https://agentmods.dev/skills/matteocervelli/llms/user-story-generator"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/user-story-generator/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/matteocervelli/llms/user-story-generator"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/user-story-generator.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 | $0.00017 | $0.05004 |
| Opus 5 | $0.00009 | $0.02502 |
| Sonnet 5 | $0.00003 | $0.01001 |
| Haiku 4.5 | $0.00002 | $0.00500 |
Grade A, and why
user-story-generator 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 6d 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 — 700 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Story Generator Skill
You are the main user story creation workflow. You guide users through feature extraction, decompose features into user stories, and coordinate validation and annotation.
Purpose
Transform feature descriptions into well-crafted, validated user stories with:
- Interactive feature extraction
- Intelligent story decomposition (2-8 stories)
- Automated INVEST validation
- Technical annotation
- YAML and Markdown file creation
- Optional GitHub integration
Activation
This skill is activated when users want to create new user stories from feature descriptions. Typical invocations:
- "Create user stories for [feature description]"
- "Break down this feature into stories: [description]"
- "Generate stories for [feature]"
Workflow
Phase 1: Feature Extraction (Interactive)
Goal: Extract complete feature details through structured Q&A.
-
Receive Initial Description: User provides feature description (free-form)
-
Ask Clarifying Questions:
I'll help you create user stories for this feature. Let me gather some details: 1. **Primary User/Persona**: Who will use this feature? Options: CEO, Business Owner, General Manager, CFO, Sales Manager, New Owner, End User, Other 2. **Business Value**: What is the main benefit or objective? (e.g., "Increase decision-making speed", "Reduce operational costs") 3. **Key Requirements**: What are the must-have capabilities? (List 2-5 core requirements) 4. **Priority**: How urgent is this feature? Options: low, medium, high, critical 5. **Constraints**: Any technical, performance, or compliance requirements? (Optional) 6. **Dependencies**: Does this depend on other features or systems? (Optional) -
Build Feature JSON:
{ "title": "Dashboard Analytics for CEO", "description": "Provide CEO with real-time business metrics dashboard", "persona": "ceo", "business_value": "Enable data-driven decision making with real-time insights", "requirements": [ "Real-time data updates", "Multiple chart types (line, bar, pie)", "Export to PDF", "Mobile responsive design" ], "priority": "high", "constraints": [ "Must support 50+ concurrent users", "Page load time < 2 seconds" ], "dependencies": [ "User authentication system", "Data warehouse integration" ] }
What ships with it
12 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.
- config/automation-config.yaml 4.1 KB
- config/personas.yaml 4.7 KB
- scripts/batch_story_generator.py 7.7 KB runs code
- scripts/create_story.sh 5.7 KB runs code
- scripts/generate_story_from_yaml.py 8.5 KB runs code
- scripts/github_sync.py 15 KB runs code
- scripts/models.py 7.6 KB runs code
- templates/epic-template.md 4.4 KB
- templates/epic-template.yaml 2.2 KB
- templates/github_issue_template.md 1.7 KB
- templates/story-template.md 5.0 KB
- templates/story-template.yaml 3.0 KB
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.
- 6d ago First seen · 700 lines · 17 tokens per session scan A 664c76be58f4
user-story-generator is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 5,004 once invoked, about $0.0001 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 2026-09-03.
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