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/alexander-vyh/claude-profilesWrote 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/alexander-vyh/claude-profiles/doctor)<a href="https://agentmods.dev/commands/alexander-vyh/claude-profiles/doctor"><img src="https://agentmods.dev/badge/commands/alexander-vyh/claude-profiles/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/alexander-vyh/claude-profiles/doctor"><img src="https://agentmods.dev/badge/commands/alexander-vyh/claude-profiles/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 | $0.00009 | $0.00832 |
| Opus 5.5 | $0.00004 | $0.00333 |
| Sonnet 5.5 | $0.00002 | $0.00166 |
| Haiku 4.5 | $0.00001 | $0.00083 |
Grade A, and why
doctor scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Run per-profile diagnostics across every profile in `~/.claude/llm-profiles/`. Reports schema conformance, helper-shim presence and executability (without running the helper — per invariant #8), sidecar vs settings-file The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 51 lines · 9 tokens per session scan A 32c71a4a0c6d
doctor is a command published in the GitHub repository alexander-vyh/claude-profiles (1 stars, last pushed 3mo ago), licensed GPL-3.0. It adds 9 tokens to every session and 832 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
debug
Systematic root-cause investigation, then fix with TDD — never proposes a fix before finding the cause; resumable diagnosis + regression test in .orc/ state. Workspace-aware. For a quick one-off look without session state, prefer the bundled /debug.
ccc-debug-session
Run a structured debug session: gather context, rank hypotheses, test them without editing code, then fix with a regression test and record the lesson. Use when a bug's cause is unclear.
ci
Diagnose and fix a red CI run — dispatches orc-ci-investigator, then routes on its verdict: auto-fix via orc-code-fixer, flake re-run, infra escalation, or /orc:debug hand-off.
bifrost-debug
Diagnose why the Bifrost gateway, memory injection, or skill discovery isn't working.
perf
Structured performance investigation with baselines, profiling, and evidence-backed decisions.
bug-fix
Streamlines bug fixing by creating a GitHub issue first, then a feature branch for implementing and thoroughly testing the solution before merging.