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 Juliocbm/beacon-docs --skill beacon-doctorgit clone --depth 1 https://github.com/Juliocbm/beacon-docsWrote 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/juliocbm/beacon-docs/beacon-doctor)<a href="https://agentmods.dev/skills/juliocbm/beacon-docs/beacon-doctor"><img src="https://agentmods.dev/badge/skills/juliocbm/beacon-docs/beacon-doctor.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.02332 |
| Opus 5 | $0.00028 | $0.01166 |
| Sonnet 5 | $0.00011 | $0.00466 |
| Haiku 4.5 | $0.00006 | $0.00233 |
Grade A, and why
beacon-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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/beacon:beacon-doctor
Runs beacon doctor, parses findings, proposes informed actions per finding, executes only on user confirmation. This skill turns the CLI's text output into an actionable workflow — but every destructive action requires explicit consent.
Core principle
Tools propose. Users decide. Agents execute.
The CLI's suggestion field on each finding is a hypothesis, not a command. Your job is to (a) parse what the doctor saw, (b) gather enough context to make the proposal informed, (c) ask for confirmation, (d) execute only on yes.
Mandate: always use --json
Run beacon doctor --json, never plain beacon doctor.
The text output is for humans reading their terminal. You need the structured array of {area, check, target?, observation, suggestion} objects to iterate over findings and propose specific actions. Parsing pretty-printed text with regex is fragile (CLI formatting can change); JSON is the stable contract.
beacon doctor --json
Reformatting JSON into human-readable output for your reply is trivial — that's what you're already good at. Rule: if a CLI offers --json and you need to act on the output, use it.
The all-clear case
When findings is empty (or []):
✔ All checks passed. (N areas inspected, M findings.)
Relay this and STOP. No padding. No "while we're here, want me to also run lint?" No preventive-measures suggestions. No offer to schedule periodic re-runs.
The user asked one question; they got the answer. The pull to add padding ("I should earn this turn") is a calibration bug, not a service to the user. A good doctor's visit ends with "you're fine, see you next year" — not invented follow-ups.
Per-finding flow (the normal case)
For each finding in findings[]:
Step 1 — Group by area, present concisely
Render findings grouped by area (activity / decisions / snapshots / balance). Each finding shows:
- The target (file path or "project-wide")
- The observation
- The CLI's suggestion (verbatim, so the user sees what beacon thinks)
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.
- 8d ago First seen · 166 lines · 57 tokens per session scan A ecd625c20154
beacon-doctor is a skill published in the GitHub repository Juliocbm/beacon-docs (6 stars, last pushed 3mo ago), licensed MIT. It adds 57 tokens to every session and 2,332 once invoked, about $0.0003 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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