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/sr-generateWrote 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/sr-generate)<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/sr-generate"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-generate/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/sr-generate"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-generate.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 | $0.00052 | $0.01296 |
| Opus 5.5 | $0.00021 | $0.00518 |
| Sonnet 5.5 | $0.00010 | $0.00259 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
sr:generate 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sr:generate
Goal: produce a complete, publication-ready IEEE 830 SRS. No word limit. Each section file must be fully written — no placeholders, no summaries, no "see plan for details."
Step 0 — Identify Project & Gate
AskUserQuestion: "Which project to generate SRS for? (slug)"
Read all files in projects/{slug}/plan/.
If plan files don't exist or are incomplete: tell user to run /sr:plan first.
Run the readiness gate before writing anything:
python .claude/scripts/plan_validator.py --dir projects/{slug}/plan/
- BLOCKED (ERRORs found, e.g. missing file, FR numbering gap, missing "shall"
clause, bad priority tag): stop here. List the ERRORs and tell the user to fix
them via
/sr:planbefore retrying/sr:generate. - READY WITH WARNINGS (e.g. unresolved
[NEEDS USER INPUT]not yet logged in appendix-b-open-issues.md): show the warnings and ask the user to confirm proceeding anyway, or go back to/sr:planto resolve them. - READY: proceed to Step 1.
Load .claude/skills/srs-generator/references/srs-template.md.
Step 1 — Generate Section Files
Create files under projects/{slug}/srs/. Write each file completely before
moving to the next. Follow srs-template.md formatting for each section.
File order:
srs/
01-introduction.md
02-overall-description.md
03-01-external-interfaces.md
03-02-functional-requirements.md
03-03-performance.md
03-04-database.md
03-05-design-constraints.md
03-06-system-attributes.md
03-07-other-requirements.md
appendix-a-glossary.md
appendix-b-open-issues.md
FR Format (mandatory for every FR in 03-02)
#### FR-NN [Essential|Conditional|Optional]
**Requirement:** The system shall {precise verb} {object} when {condition}.
| Field | Value |
|-------|-------|
| Actor | {who triggers this} |
| Precondition | {system state before} |
| Trigger | {what causes it} |
| Source | {brainstorm round / business rule / regulatory} |
**Acceptance Criteria (GWT):**
- **Given** {system state}
- **When** {actor action or event}
- **Then** {expected system response — measurable}
- **And** {additional assertions if needed}
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 · 169 lines · 52 tokens per session scan A b517a55777b9
sr:generate is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 1,296 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.