Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add matebenyovszky/agentplaybooks/plugin install agentplaybooksWrote 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/commands/matebenyovszky/agentplaybooks/doctor)<a href="https://agentmods.dev/commands/matebenyovszky/agentplaybooks/doctor"><img src="https://agentmods.dev/badge/commands/matebenyovszky/agentplaybooks/doctor/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/commands/matebenyovszky/agentplaybooks/doctor"><img src="https://agentmods.dev/badge/commands/matebenyovszky/agentplaybooks/doctor.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 | $0.00015 | $0.00163 |
| Opus 5 | $0.00008 | $0.00081 |
| Sonnet 5 | $0.00003 | $0.00033 |
| Haiku 4.5 | $0.00002 | $0.00016 |
Grade A, and why
doctor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Audit the project's agent configuration with the AgentPlaybooks doctor.
- Run:
node "${CLAUDE_PLUGIN_ROOT}/bin/agentplaybooks.js" doctor $ARGUMENTS --json(default to the current project root when no path is given). - Report the health score and the finding counts by severity.
- For each finding, show the source file (and line numbers if present) and a concrete fix. Group identical codes together.
- If there are
secret.hardcodedfindings, recommend moving the values to environment references — never print suspected secret values.
Doctor is read-only and local-only; it changes nothing.
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.
- 12d ago First seen · 17 lines · 15 tokens per session scan A 0176c204d751
doctor is a command published in the GitHub repository matebenyovszky/agentplaybooks (5 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 163 once invoked, about $0.0001 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.
Other commands, from other repositories
CHANGELOG
Command "CHANGELOG" from bytedance/UI-TARS-desktop, covering 0.4.0 2024-12-10 - add logging, 1.2.29, 1.2.28, 1.2.26 and 1.2.25.
ui-aqa-flow-test-report-analysis
Phase 7 Test Report Analysis of ui-aqa-flow.
api-aqa-flow-execution-and-report-analysis
Phase 6 Execution & Report Analysis of api-aqa-flow (USER INTERACTION REQUIRED).
troubleshoot-user
Cross-product troubleshooting of user connectivity across ZCC, ZDX, ZPA, and ZIA.
root-cause
Use when any test fails, bug appears, or behaviour surprises you, before proposing a fix - find the cause and prove it, by reading real evidence, tracing bad values back to their origin, comparing against a working case, and testing one hypothesis at a time.
preflight
Diagnostique l'environnement Cortex et guide la réparation (DB, extensions, modèles).