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 The-AI-Directory-Company/agents-and-skills --skill user-story-mappinggit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/the-ai-directory-company/agents-and-skills/user-story-mapping)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/user-story-mapping"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/user-story-mapping/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/the-ai-directory-company/agents-and-skills/user-story-mapping"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/user-story-mapping.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 | $0.00032 | $0.01236 |
| Opus 5 | $0.00016 | $0.00618 |
| Sonnet 5 | $0.00006 | $0.00247 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
user-story-mapping 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 9d 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Story Mapping
Before you start
Gather the following from the user:
- What product/feature area are we mapping?
- Who are the users? (List specific personas or segments, not "users")
- What is the goal? (Are we mapping for an MVP? A new feature? A redesign?)
- What constraints exist? (Timeline, team size, technical limitations)
If the user gives you a vague scope ("map our product"), narrow it: "Which user journey should we focus on first?"
Step 1: Identify the backbone (Activities)
Activities are the high-level things users do. They read left-to-right as a narrative.
Rules for activities:
- Use verb phrases: "Discover agents", "Configure workspace", "Monitor performance"
- Keep to 4-8 activities for a single feature area
- Order them chronologically as the user would experience them
- Each activity should be completable in one session
[Discover agents] → [Evaluate agent] → [Install agent] → [Configure agent] → [Monitor usage]
Step 2: Break activities into tasks
Each activity contains 2-5 tasks. Tasks are the steps a user takes within an activity.
Rules for tasks:
- Tasks are smaller verb phrases: "Search catalog", "Read reviews", "Compare options"
- Order them top-to-bottom by typical sequence
- Every task should map to an observable user action
Activity: Discover agents
├── Search catalog
├── Browse categories
├── View trending
└── Read recommendations
Step 3: Generate stories under each task
Stories are the specific, implementable items. Write them in standard format:
As a [persona], I want [action] so that [outcome].
Rules for stories:
- Each story must be independently deliverable
- Each story must be testable (you can write an acceptance criterion)
- Avoid technical stories at this stage — frame everything from the user's perspective
- It's okay to have 3-10 stories per task
Activity: Discover agents
├── Task: Search catalog
│ ├── As a developer, I want to search agents by keyword so that I can find relevant tools quickly
│ ├── As a developer, I want to filter search results by category so that I can narrow down options
│ └── As a developer, I want to see search results ranked by relevance so that the best matches appear first
What ships with it
1 file 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.
- 9d ago First seen · 143 lines · 32 tokens per session scan A f40e21f85817
user-story-mapping is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 1,236 once invoked, about $0.0002 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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