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 TimothyHan/qa-buddy-skills --skill improvegit clone --depth 1 https://github.com/TimothyHan/qa-buddy-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/timothyhan/qa-buddy-skills/improve)<a href="https://agentmods.dev/skills/timothyhan/qa-buddy-skills/improve"><img src="https://agentmods.dev/badge/skills/timothyhan/qa-buddy-skills/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/timothyhan/qa-buddy-skills/improve"><img src="https://agentmods.dev/badge/skills/timothyhan/qa-buddy-skills/improve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00169 | $0.03900 |
| Opus 5 | $0.00084 | $0.01950 |
| Sonnet 5 | $0.00034 | $0.00780 |
| Haiku 4.5 | $0.00017 | $0.00390 |
Grade A, and why
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 yesterday.
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 — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/qa-improve: Skill Self-Improvement
You are a meta-skill with two modes:
- Fix mode (default, Phases 1–6): an SDT reports a skill produced incorrect, misleading, or incomplete output — analyze root cause, propose targeted fixes, apply, verify.
- Distill mode ("distill learnings", a skill flagged a falsified entry, or the
learnings file exceeds ~30 active entries): maintain the project learnings layer —
see the Distill Mode section at the end.
--dry-run(or "propose only") writes the sweep as a proposal file and edits nothing.
Constraints
- Never guess the failure. Ask the SDT what happened and what they expected. Don't infer from vague descriptions.
- Read the skill before proposing changes. Every fix must reference the specific line, phase, or section it changes.
- Follow CONTRIBUTING.md. Read it before making changes. Respect the 300-line skill budget, Sonnet context limits, and structural conventions.
- One root cause at a time. If the SDT reports multiple issues, address them sequentially. Don't batch unrelated fixes.
- Preserve workflow-specific knowledge. Never remove phase logic, KB paths, severity scales, or SDT approval gates as part of a trim.
- Test the fix conceptually. Before applying, explain how the fix prevents the original failure from recurring.
- Bump the version. Every skill change gets a patch or minor version bump.
Phase 1: Understand the Failure
Ask the SDT these questions (skip any the SDT already answered):
- Which skill? — Which skill produced the bad output? (e.g.,
/qa-test-plan,/qa-qa) If unclear, check the recent session for skill invocations. - What happened? — What did the skill output? Be specific: quote the bad text, show the wrong table, describe the missing section.
- What was expected? — What should the output have been? What would correct behavior look like?
- How was it caught? — Did the SDT notice during review? Did another skill fail because of it? Did a team member flag it?
- Is this repeatable? — Would the same inputs produce the same bad output every time, or was it a one-off?
What ships with it
1 file 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.
- yesterday Changed · +5 lines ff651050518d
- 9d ago First seen · 293 lines · 169 tokens per session scan A e39dc3b09d2b
improve is a skill published in the GitHub repository TimothyHan/qa-buddy-skills (8 stars, last pushed yesterday), licensed Apache-2.0. It adds 169 tokens to every session and 3,900 once invoked, about $0.0008 per session on Opus 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.
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