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.
git clone --depth 1 https://github.com/alipajand/agent-context-doctorWrote 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/alipajand/agent-context-doctor/verify)<a href="https://agentmods.dev/commands/alipajand/agent-context-doctor/verify"><img src="https://agentmods.dev/badge/commands/alipajand/agent-context-doctor/verify/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/alipajand/agent-context-doctor/verify"><img src="https://agentmods.dev/badge/commands/alipajand/agent-context-doctor/verify.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 | $0.00020 | $0.00138 |
| Opus 5.5 | $0.00008 | $0.00055 |
| Sonnet 5.5 | $0.00004 | $0.00028 |
| Haiku 4.5 | $0.00002 | $0.00014 |
Grade A, and why
verify 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 17d 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
Run these commands in order and stop at the first failure:
pnpm format:checkpnpm typecheckpnpm lintpnpm testpnpm build
Report each command with pass or fail. For a failure, show the relevant error lines and the file and line to fix. Do not change any files.
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.
- 17d ago First seen · 16 lines · 20 tokens per session scan A 57bf5b8dd28f
verify is a command published in the GitHub repository alipajand/agent-context-doctor (1 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 138 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 2026-09-24.
Other commands, from other repositories
aitask-qa
Run QA analysis on any task — analyze changes, discover test gaps, run tests, and create follow-up test tasks.
aitask-run-gates
Run a task's declared gates — the conversational front of the headless gate orchestrator engine. Dispatches unlocked machine-gate verifiers within their retry budgets, observes human gates without self-signalling, and reports.
aitask-audit-wrappers
Audit and port aitask skill wrappers across code-agent trees, plus helper-script whitelist coverage.
apex-quick
Quick Flow for bounded fixes - the full APEX route with Brainstorm skipped and Plan compressed to one task; Analyze trio, delegated execution, eLicit, Verify, challenger and full sniper always run.
test
Test commit. Use for add tests, update tests, test coverage, unit test, spec.
harness-eval
Run AI Harness Doctor phase 3 efficacy eval.