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 agentmods add skills/matthewye/opencode-toolbox/audit-autopilotnpx skills add MatthewYe/opencode-toolbox --skill audit-autopilotgit clone --depth 1 https://github.com/MatthewYe/opencode-toolboxWrote 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/matthewye/opencode-toolbox/audit-autopilot)<a href="https://agentmods.dev/skills/matthewye/opencode-toolbox/audit-autopilot"><img src="https://agentmods.dev/badge/skills/matthewye/opencode-toolbox/audit-autopilot.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 | $0.00087 | $0.01503 |
| Opus 5 | $0.00044 | $0.00751 |
| Sonnet 5 | $0.00017 | $0.00301 |
| Haiku 4.5 | $0.00009 | $0.00150 |
Grade A, and why
audit-autopilot 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 4d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Autopilot
Audit an autopilot execution by analyzing its OpenCode session trace. The audit evaluates three layers of fidelity, producing a structured scorecard with evidence anchors back to the raw session data.
When to use
Run after an /autopilot session completes. User provides the orchestrator session ID (find it with opencode session list). Do not use for non-autopilot sessions.
Workflow
Step 0: Gather inputs
The session ID may come from the command argument (/audit-autopilot <session-id>) or be stated directly in the user's prompt. If already provided, skip asking and proceed.
If not provided, ask the user for:
- Orchestrator session ID (required) — the session where
/autopilotwas invoked - Project directory (optional, defaults to cwd) — where
.scratch/issues and contracts live
If the user doesn't know the session ID, help them find it:
opencode session list --format json
Look for sessions with titles matching autopilot invocations or issue names.
If the user has already specified subagent session IDs or contract file paths, use them directly rather than re-discovering them.
Step 1: Export and parse sessions
Export the orchestrator session:
opencode export <session-id> > /tmp/audit-orchestrator.json
Parse this JSON to extract key metadata:
- Issue sources: Find paths like
.scratch/<feature>/issues/<NN-slug>/or GitHub issue numbers in the user's initial messages - Subagent session IDs: Scan all
tasktool calls — each one hasstate.metadata.sessionIdgiving the child session ID. Track which session mapped to which agent type (implementer / reviewer) and round number - Contract files: From the orchestrator's dispatch prompts, locate
AGENT-BRIEF.mdandissue.mdpaths
For GitHub issues, the contract is embedded in the orchestrator's prompt text — extract it directly.
If the user already specified subagent session IDs, skip the discovery step and use the provided IDs directly. Export each subagent session:
opencode export <sub-session-id> > /tmp/audit-<agent>-r<round>.json
What ships with it
7 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.
- 4d ago First seen · 110 lines · 87 tokens per session scan A f66b4fce2a78
audit-autopilot is a skill published in the GitHub repository MatthewYe/opencode-toolbox (5 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 1,503 once invoked, about $0.0004 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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