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/bartolli/kmd/triagenpx skills add bartolli/kmd --skill triagegit clone --depth 1 https://github.com/bartolli/kmdWrote 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/bartolli/kmd/triage)<a href="https://agentmods.dev/skills/bartolli/kmd/triage"><img src="https://agentmods.dev/badge/skills/bartolli/kmd/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 | $0.00212 | $0.03915 |
| Opus 5 | $0.00106 | $0.01958 |
| Sonnet 5 | $0.00042 | $0.00783 |
| Haiku 4.5 | $0.00021 | $0.00392 |
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 today.
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 — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Triage — Move Stories Through the State Machine
A small state machine over wiki story files. Lifts Matt Pocock's triage pedagogy onto the wiki's kind: story artifact.
Prerequisites
WIKI_SCOPE: <scope>declared in the project instructions. If missing, suggest/wiki.- At least one intent under
projects/<scope>/intent/or one story file underprojects/<scope>/plan/<plan-name>/. With neither, suggest/to-stories.
Roles
Intents carry no triage labels; their state is status plus one outcome field ([[adr-intent-kind]]):
draft— filed, unread by triageactive— scheduled: accepted, story not yet writtenarchivedwith exactly one ofpromoted_to(story slug),dismissed(reason),fixed_by(regression test path)supersededwithsuperseded_by— merged into another intent, whosesightingsabsorbed the count
Stories carry two label roles.
Two category roles (story has exactly one):
bug— something is brokenenhancement— new feature or improvement
Five state roles (story has exactly one, lives in triage_state frontmatter):
needs-triage— story needs evaluationneeds-info— agent waits on user clarification (in solo+Claude context: Claude is blocked on a user decision)ready-for-agent— fully specified, AFK-ready (an agent can pick it up with no human context)ready-for-human— needs human implementation (judgment, external access, hardware, design review)wontfix— will not be actioned
State transitions: an unlabeled or needs-triage story moves to needs-info, ready-for-agent, ready-for-human, or wontfix. needs-info returns to needs-triage once the user provides the missing input. The user can override at any time — flag transitions that look unusual and confirm before proceeding.
AI disclaimer (GH/GitLab mode only)
When WIKI_ISSUE_TRACKER is github or gitlab, every comment posted to the remote tracker during triage must start with:
> *This was generated by AI during triage.*
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.
- today Changed · +69 lines · +46 tokens per session 15c0d5db9362
- 4d ago First seen · 290 lines · 166 tokens per session scan A 4528a18a7cf9
triage is a skill published in the GitHub repository bartolli/kmd (7 stars, last pushed today), licensed MIT. It adds 212 tokens to every session and 3,915 once invoked, about $0.0011 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…