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 huuanh20/awesome-ai-agent-skills --skill sr-specgit clone --depth 1 https://github.com/huuanh20/awesome-ai-agent-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/huuanh20/awesome-ai-agent-skills/sr-spec)<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/sr-spec"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-spec/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-spec"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-spec.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 | $0.00882 |
| Opus 5.5 | $0.00013 | $0.00353 |
| Sonnet 5.5 | $0.00006 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
sr:spec 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sr:spec
Goal: turn the brainstorm output into a structured, comprehensive spec. No word limit — every section must be fully written.
Step 0 — Identify Project
Ask user for the project slug (or detect from context):
AskUserQuestion: "Which project to write spec for? (slug name or path to brainstorm.md)"
Read projects/{slug}/brainstorm.md. If it doesn't exist, tell the user to run
/sr:brainstorm first.
Step 1 — Write spec.md
Write projects/{slug}/spec.md. No word limit. Every sub-section fully written.
§1 — Project Overview
- System name (confirmed in brainstorm)
- Problem statement (what problem does this solve?)
- Solution summary (what does the system do, for whom, how)
- Primary success metrics (how will we know it's working?)
§2 — Actors
One full entry per confirmed actor:
- Name and role
- Technical proficiency (non-technical | basic | intermediate | expert)
- Domain knowledge level
- Frequency and channel of use (web | mobile | API | all)
- Accessibility needs (if any)
- Data access scope (read | write | admin)
§3 — Features (IN Scope)
For each confirmed feature:
- Feature name + cluster
- Description in user's own words (verbatim from brainstorm)
- AI-expanded detail (what sub-capabilities does this imply?)
- Actors who use it
- Priority tier: Essential | Conditional | Optional
§4 — OUT of Scope
Table: Feature | Reason excluded | Planned for version Every item from brainstorm OUT scope list.
§5 — Technical Constraints
- Tech stack: languages, frameworks, runtime
- Hosting / deployment model
- Existing systems to integrate (name, protocol, direction)
- Security standards (auth model, encryption requirements)
- Compliance: applicable regulations + specific obligations
§6 — Business Rules
Numbered list. Each rule: precise, testable statement. Example: "BR-01: A user cannot place an order if their account balance is below the order total." Cover every rule surfaced in brainstorm Round 5.
§7 — NFR Baselines
Table format:
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 · 123 lines · 32 tokens per session scan A e60a2c5a60f1
sr:spec is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 882 once invoked, about $0.0001 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.