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 KhazixW2/Everything-Maa --skill maa-diagnosegit clone --depth 1 https://github.com/KhazixW2/Everything-MaaWrote 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/khazixw2/everything-maa/maa-diagnose)<a href="https://agentmods.dev/skills/khazixw2/everything-maa/maa-diagnose"><img src="https://agentmods.dev/badge/skills/khazixw2/everything-maa/maa-diagnose/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/khazixw2/everything-maa/maa-diagnose"><img src="https://agentmods.dev/badge/skills/khazixw2/everything-maa/maa-diagnose.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 | $0.00170 | $0.01492 |
| Opus 5 | $0.00085 | $0.00746 |
| Sonnet 5 | $0.00034 | $0.00298 |
| Haiku 4.5 | $0.00017 | $0.00149 |
Grade A, and why
maa-diagnose 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maa Diagnose
Drive the externally managed latest diagnostic runtime to turn an unexplained MaaFramework failure into normalized evidence and one bounded failure owner. This skill owns discovery, invocation, and normalization. It does not parse MaaFramework logs itself and does not contain a diagnostic engine.
Read references/runtime-discovery.md before the first invocation. Read references/failure-map.md before reporting an owner.
Decide whether to diagnose
Run this skill only when the failing owner is still unknown after the evidence already in hand.
- Do not run it when
$maa-pipeline-testingalready attributed the failure to a node, option, state model, or integration defect. Route that evidence to the owner directly. - Do not run it as a routine phase of every workflow, and do not run it before a failure exists.
- Do not run it for project scaffold or managed-file health; that is
$maa-project-createdoctor. - Do not run it for Project Interface schema review; that is
$maa-interface-guide.
Broad diagnosis is for cross-tool correlation: a runtime failure whose cause could live in the logs, the static project definition, the environment, or the harness.
Treat maafw.log, maafw.bak.<timestamp>.log, and another maafw.*.log path as diagnostic input only when the failure owner is still unknown.
Load the authoritative upstream Skill
Before composing a MaaEvidenceKit command, locate and read the authoritative upstream maa-evidence Skill. This handoff is part of a legitimate diagnosis; it does not broaden this Skill into an entry point for evidence extraction when no failure needs diagnosis.
- If the user supplies a MaaEvidenceKit checkout, package root, skill directory, or
SKILL.md, pass each candidate to the locator with--root PATH. - Run
node scripts/find-maa-evidence-skill.mjs. The read-only locator searches installed standalone skills, project and user installations, and npm/pnpm global packages while excluding this Skill's own root. - For every locator result, read the latest formal GitHub Release of
Windsland52/MaaEvidenceKit, preferring its integratedmaa-evidenceSkill and falling back to its README. The locator result reports local candidates; it never makes a localskillPathauthoritative for the latest runtime. - If the latest formal release does not expose the integrated Skill or README, use the disclosed default-branch handoff.
What ships with it
4 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.
- yesterday Changed · -1 lines · +2 tokens per session 7e478dd4d901
- 9d ago First seen · 89 lines · 168 tokens per session scan A c725293909bd
maa-diagnose is a skill published in the GitHub repository KhazixW2/Everything-Maa (12 stars, last pushed 2d ago), licensed MIT. It adds 170 tokens to every session and 1,492 once invoked, about $0.0009 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 2026-08-30.
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