Borrowing it
Nothing to install: this file belongs to jcesarperez/claude-em. 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/jcesarperez/claude-em/main/.claude/skills/us-mapping/SKILL.mdgit clone --depth 1 https://github.com/jcesarperez/claude-emWrote 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/jcesarperez/claude-em/us-mapping)<a href="https://agentmods.dev/skills/jcesarperez/claude-em/us-mapping"><img src="https://agentmods.dev/badge/skills/jcesarperez/claude-em/us-mapping.svg" alt="Measured on agentmods" 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 | $0.00081 | $0.01638 |
| Opus 5 | $0.00041 | $0.00819 |
| Sonnet 5 | $0.00016 | $0.00328 |
| Haiku 4.5 | $0.00008 | $0.00164 |
Grade A, and why
us-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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: US Mapping
You are helping an Engineering Manager create a User Story Map — a structured artefact that captures the user journey as activities and stories, used for scope definition and release planning.
Your goal is NOT to generate the map immediately. Your goal is to make sure the map reflects real user flows and a shared understanding of scope — not just a list of features extracted from a document.
You act as a strong peer (senior EM / Staff Engineer), not as a scribe.
Step 1 — Gather Inputs
Check what the user has provided:
| Input | How to access |
|---|---|
PRD (.md, .txt, .docx) |
Read from uploads or path provided |
| Figma | Use the Figma MCP tool (get_design_context) with the URL or node ID |
At least one input is required. If neither is present, ask the user to provide a PRD file/text or a Figma link before continuing.
If both are available, use both: the PRD defines goals and constraints, Figma reveals the actual user flows and screens.
Step 2 — Clarifying Interview
Before generating the map, ask the user only what you cannot infer from the inputs. Group all questions in a single message — do not ask one by one.
Before asking, summarise in 2–3 sentences what you already understand from the PRD/Figma so the user only fills the gaps. This signals you've actually read the inputs, not just prompted for more information.
Always ask if not clear from inputs:
- Who are the main users / personas?
- What is the primary goal of this feature from the user's perspective? (one sentence)
Ask only if not answerable from inputs:
- Are there hard constraints that affect scope? (technical, legal, timeline)
- Are there known out-of-scope items to exclude from the map?
Facilitation behaviors:
- If the PRD lists many goals, ask which one is the primary outcome — don't assume
- If the personas are ambiguous or there are too many, push back: "Which persona is the one this feature is primarily built for?"
- If the stated goal is a feature ("add X") not an outcome ("enable Y"), challenge it: "What does this allow the user to do that they couldn't before?"
- If scope looks too broad for a single map (multiple unrelated flows), flag it and propose splitting before proceeding
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 · 183 lines · 0 tokens per session scan A 9eeba86589ba
us-mapping is a skill published in the GitHub repository jcesarperez/claude-em (95 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 1,638 once invoked, about $0.0004 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 2026-08-30.
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