Borrowing it
Nothing to install: this file belongs to a9a4k/tour. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/a9a4k/tour/main/.agents/skills/triage/SKILL.mdgit clone --depth 1 https://github.com/a9a4k/tourWrote 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/a9a4k/tour/triage)<a href="https://agentmods.dev/skills/a9a4k/tour/triage"><img src="https://agentmods.dev/badge/skills/a9a4k/tour/triage.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 | $0.00049 | $0.01162 |
| Opus 5 | $0.00024 | $0.00581 |
| Sonnet 5 | $0.00010 | $0.00232 |
| Haiku 4.5 | $0.00005 | $0.00116 |
Grade A, and why
triage 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 7d 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.
This is a copy
84% identical to triage — 69 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Triage
Move issues on the project issue tracker through a small state machine of triage roles.
Every comment or issue posted to the issue tracker during triage must start with this disclaimer:
> *This was generated by AI during triage.*
Reference docs
- AGENT-BRIEF.md — how to write durable agent briefs
- OUT-OF-SCOPE.md — how the
.out-of-scope/knowledge base works
Roles
Two category roles:
bug— something is brokenenhancement— new feature or improvement
Five state roles:
needs-triage— maintainer needs to evaluateneeds-info— waiting on reporter for more informationready-for-agent— fully specified, ready for an AFK agentready-for-human— needs human implementationwontfix— will not be actioned
Every triaged issue should carry exactly one category role and one state role. If state roles conflict, flag it and ask the maintainer before doing anything else.
These are canonical role names — the actual label strings used in the issue tracker may differ. The mapping should have been provided to you - run /setup-matt-pocock-skills if not.
State transitions: an unlabeled issue normally goes to needs-triage first; from there it moves to needs-info, ready-for-agent, ready-for-human, or wontfix. needs-info returns to needs-triage once the reporter replies. The maintainer can override at any time — flag transitions that look unusual and ask before proceeding.
Invocation
The maintainer invokes /triage and describes what they want in natural language. Interpret the request and act. Examples:
- "Show me anything that needs my attention"
- "Let's look at #42"
- "Move #42 to ready-for-agent"
- "What's ready for agents to pick up?"
Show what needs attention
Query the issue tracker and present three buckets, oldest first:
- Unlabeled — never triaged.
needs-triage— evaluation in progress.needs-infowith reporter activity since the last triage notes — needs re-evaluation.
What ships with it
2 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.
- 7d ago First seen · 106 lines · 49 tokens per session scan A 78ef79063cb7
triage is a skill published in the GitHub repository a9a4k/tour (5 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 1,162 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to triage, differing in 69 lines, and is treated as a copy.
Other skills, from other repositories
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loop
Full execution protocol for MODE: LOOP — the compound-engineering loop: brainstorm → plan → build → review → improve, iterating under defense-in-depth stop conditions with generator/critic separation, durable resumable state, and mandatory compounding learning capture. Loaded on demand by the architect when the loop…
parallel-work-check
Apply before starting work on an existing branch. Checks for parallel work by other agents or developers that may supersede or conflict with your planned changes. Prevents wasted effort on stale branches.
issue-ingest
Full execution protocol for MODE: ISSUEINGEST -- GitHub issue intake, localization, spec generation, and transition to the full fix workflow.
phase-wrap
Claude Code adapter for MODE: PHASE-WRAP. Delegates to the canonical opencode-swarm phase boundary protocol.
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Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.