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/huuanh20/awesome-ai-agent-skillsnpx agentmods add skills/huuanh20/awesome-ai-agent-skills/srs-workflowWrote 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/huuanh20/awesome-ai-agent-skills/srs-workflow)<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/srs-workflow"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/srs-workflow/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/huuanh20/awesome-ai-agent-skills/srs-workflow"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/srs-workflow.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 | $0.00051 | $0.02593 |
| Opus 5.5 | $0.00020 | $0.01037 |
| Sonnet 5.5 | $0.00010 | $0.00519 |
| Haiku 4.5 | $0.00005 | $0.00259 |
Grade A, and why
cl:srs-flow 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 1mo 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 — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cl:srs-flow — Full SRS Workflow
Phase 0 Topic Intake
Phase 1 Deep Brainstorm ← multi-round, categorized, options-driven
Phase 2 Spec Writing ← no word limit
Phase 3 Options Gate ← user chooses next action
Phase 4 Plan Writing ← 1 .md file per SRS section
Phase 5 User Review ← iterate until approved
Phase 6 SRS Generation ← 1 .md file per section, full detail
Phase 7 Auto-Validate ← .claude/scripts/srs_validator.py
Phase 8 Improvement Report
Phase 9 Context Save
Output directory: projects/{slug}/
Phase 0 — Topic Intake
Receive the user's topic (1 sentence to 1 paragraph). Do NOT ask questions yet.
Identify:
- Domain (e-commerce, healthcare, fintech, internal tool, SaaS, etc.)
- Scale signals (startup, enterprise, MVP, etc.)
- Any constraints mentioned
Echo back a 3-line summary:
Topic: {topic}
Domain: {detected domain}
Scale: {detected scale or "unknown"}
Then state: "Starting deep brainstorm. I will ask questions by category before writing anything." Proceed to Phase 1.
Phase 1 — Deep Brainstorm
Hard rule: AI must not proceed to Phase 2 until it can confidently answer ALL of:
- Who are ALL actors (primary + secondary + external systems)?
- What are ALL core features (not just mentioned ones — infer and confirm)?
- What are the explicit system boundaries (in scope / out of scope)?
- What are the technical constraints?
- What are the business rules and compliance requirements?
Load .claude/skills/srs-workflow/references/brainstorm-guide.md for domain-specific question sets.
Round structure
Each round: ask ONE category of questions using AskUserQuestion.
Maximum 5 questions per round. Present concrete options wherever possible — never ask
open-ended questions when a multiple-choice with "Other" covers the space.
Mandatory rounds (in order):
Round 1 — Actors & Users Ask about: primary users, secondary users, admin roles, external systems/APIs. For each actor type: present role options with descriptions. Wait for answers.
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.
- 1mo ago First seen · 326 lines · 51 tokens per session scan A 4e794f9bed84
cl:srs-flow is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 51 tokens to every session and 2,593 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 2026-08-31.
Other skills, from other repositories
loop
Work through the taskboard unattended for hours, pacing against the usage limits and filling the gap before a reset with CPU-only jobs. Use when asked to run all day, work unattended, or loop over tickets.
learn
Record a correction, decision, finding or failed attempt in the wiki. Use when the user corrects you, when a decision is made with a reason, when an experiment returns a verdict, or when you learn something the next session would otherwise re-derive.
wrap-up
Close out a task by folding what it taught into the wiki, updating the taskboard, and linting. Use at the end of a task, before clearing a session, or when asked to wrap up.
handoff
Write one self-contained goal that a fresh session can continue from. Use when context is running out, before clearing a session, when usage passes 95% on a long run, or when asked for a handoff.
init
Set up Dory in this repo by exploring it, creating wiki/ from the template, and connecting the usage statusline. Use when a project has no wiki/ yet, or when asked to set up Dory.
check-mcp-json
Safely review, triage, repair, and merge ToolSDK MCP Registry package JSON pull requests. Use when an agent needs to validate files under packages/, detect duplicate registry keys, classify community PRs, make authorized fixes on contributor branches, close invalid or duplicate PRs, or squash-merge approved PRs.