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-improvegit 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-improve)<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/sr-improve"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-improve/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-improve"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/sr-improve.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 | $0.00037 | $0.00793 |
| Opus 5.5 | $0.00015 | $0.00317 |
| Sonnet 5.5 | $0.00007 | $0.00159 |
| Haiku 4.5 | $0.00004 | $0.00079 |
Grade A, and why
sr:improve 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sr:improve
Goal: produce a candid improvement report — what was deferred, what carries risk, what should be resolved before development starts. Reference specific FR/NFR IDs.
Step 0 — Identify Project
AskUserQuestion: "Which project? (slug)"
Read from projects/{slug}/:
spec.md(for deferred features and open items)srs/appendix-b-open-issues.md(for all [TBD] items)srs/03-03-performance.md(for [TBD] NFRs)- Validator output if available (WARNs from
/sr:validate)
Step 1 — Write improvement-report.md
Write projects/{slug}/improvement-report.md. No word limit.
§1 — Deferred Features (Next Version Candidates)
List every feature marked OUT of scope in spec.md that the user mentioned but deferred. For each:
- Feature name
- Why deferred (user's reason from brainstorm, if stated)
- Estimated effort level (low | medium | high) — AI estimate only, not a commitment
- Suggested version: v1.1 | v2.0 | unknown
§2 — Technical Risks
For each unresolved [TBD] in NFRs:
- NFR-ID + description
- What data is needed to set the target
- Risk if unresolved: (A) test cannot be written (B) SLA cannot be committed (C) architecture decision blocked
- Suggested owner + resolve-by milestone
For each external integration in §3.1:
- Integration name + system
- Risk: dependency on third-party uptime / API versioning / rate limits
- Mitigation suggestion
§3 — FR Refinement Suggestions
Identify FRs that are:
- Too broad (combines multiple behaviors that should be separate FRs)
- Missing negative cases (what happens when it FAILS?)
- Missing actor variants (same action, different permission level)
List each with the suggested split or addition.
§4 — NFR Gaps
NFRs with [TBD] Response Measure → list with: what benchmark test would produce the real number. NFRs with adjective-only measure (should have been caught by validator) → rewrite suggestion.
§5 — Validation Warnings
Enumerate every WARN from /sr:validate with:
- Warning text
- Which file/FR/NFR it refers to
- Recommended resolution (specific action, not "review this")
- Urgency: must resolve before dev | should resolve before QA | can defer
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 · 107 lines · 37 tokens per session scan A 1fae8122cd01
sr:improve is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 793 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.