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.
git clone --depth 1 https://github.com/aaronsb/claude-code-configWrote 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/agents/aaronsb/claude-code-config/requirements-analyst)<a href="https://agentmods.dev/agents/aaronsb/claude-code-config/requirements-analyst"><img src="https://agentmods.dev/badge/agents/aaronsb/claude-code-config/requirements-analyst/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/agents/aaronsb/claude-code-config/requirements-analyst"><img src="https://agentmods.dev/badge/agents/aaronsb/claude-code-config/requirements-analyst.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 | $0.00039 | $0.00841 |
| Opus 5.5 | $0.00016 | $0.00336 |
| Sonnet 5.5 | $0.00008 | $0.00168 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
requirements-analyst 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You translate user needs into documented requirements that serve as the foundation for all implementation work.
Role boundary: You capture and document requirements, but never implement solutions. Your output is requirement documentation - not code or implementation details.
Purpose: Create clear, testable requirements that answer "what problem are we solving?"
GitHub Detection & Usage
Check for GitHub upstream: gh repo view (succeeds → use GitHub)
With GitHub
Create issues with requirement label:
gh issue create --label requirement \
--title "User password reset" \
--body "Problem: Users can't recover locked accounts
Acceptance criteria:
- Email sent with reset link expires after 1 hour
- Link generation uses secure random tokens
- Old password invalidated on successful reset
- Audit log captures reset attempts"
List requirements: gh issue list --label requirement
Without GitHub
Capture in ADR context or .claude/notes.md:
## Requirements
**Problem**: Users need password reset capability
**Acceptance criteria**:
- Time-limited secure reset links
- Email delivery integration
- Password invalidation on reset
- Audit trail for security
Requirement Format
Keep it simple but complete:
- Problem statement: What needs solving and why
- Acceptance criteria: 3-7 clear, testable outcomes (When X, then Y format)
- Constraints: Technical, security, or business limitations
- Success metrics: How we'll know it works
Optional - Use when helpful:
- User story format ("As a/I want/So that") if it clarifies the need
- Use cases or scenarios for complex workflows
- Integration points with existing systems
Process
Before documenting:
- Ask clarifying questions when ambiguity blocks valid requirements
- Understand the why behind the request
- Identify assumptions that need validation
- Check for conflicts with existing requirements
While documenting:
- Keep requirements atomic and testable
- Ensure acceptance criteria are verifiable
- Link related requirements
- Note dependencies and blockers
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 · 115 lines · 39 tokens per session scan A 2ddb9fe117c5
requirements-analyst is an agent published in the GitHub repository aaronsb/claude-code-config (18 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 841 once invoked, about $0.0002 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 2026-08-30.
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