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 joshukraine/dotfiles --skill model-triagegit clone --depth 1 https://github.com/joshukraine/dotfilesWrote 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/joshukraine/dotfiles/model-triage)<a href="https://agentmods.dev/skills/joshukraine/dotfiles/model-triage"><img src="https://agentmods.dev/badge/skills/joshukraine/dotfiles/model-triage/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/skills/joshukraine/dotfiles/model-triage"><img src="https://agentmods.dev/badge/skills/joshukraine/dotfiles/model-triage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.02701 |
| Opus 5.5 | $0.00000 | $0.01080 |
| Sonnet 5.5 | $0.00000 | $0.00540 |
| Haiku 4.5 | $0.00000 | $0.00270 |
Grade A, and why
model-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 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.
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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Triage
Roll the per-issue model-selection convention into a repository: tier each open issue, then apply the model: labels, the board's Model field, and any body callouts — all behind a single approval gate. The convention, its heuristic, and the manual runbook this encodes live in ~/.claude/docs/model-selection-strategy.md; the label vocabulary lives in ~/.claude/docs/label-taxonomy.md.
This is a rollout tool, not a routine one. Model labels are assigned at issue creation alongside the type label. Run this skill once when adopting the convention in a repo that already has open issues, and after that only in maintenance mode when drift has accumulated.
Where this runs
From the target repository's checkout — you need the issues and the code, because tiering an issue means judging what a fix would actually touch. If you must run from elsewhere, every gh issue call needs --repo <owner>/<name>; without it the command silently targets whatever repo you are standing in.
Arguments
- (no args) — full rollout: tier every open issue that should carry a label.
--maintenance— sweep mode: tier only issues missing a label, reconcile label ↔ board-field drift, and refresh stale label descriptions. Leaves existing label assignments alone unless an issue's scope has visibly changed.
The tiering heuristic
Assign a tier by asking what a wrong answer costs and how far the reasoning reaches. Full treatment in the strategy doc; the working summary:
- Fable (flagship) — a wrong answer would silently corrupt canonical/persistent data with no error surface. This is the insurance case, and only that case. Expect it rare, and expect each one to have a nameable reason. (Multi-module reasoning with non-obvious ripple used to qualify here too; Opus 5 absorbed it and the clause was cut on 2026-07-27.)
- Opus (workhorse) — well-specified features with a test scaffold and a contained blast radius; migrations / data-model; thin specs; security-adjacent work. The default when you genuinely can't tell.
- Sonnet (light) — docs, a single regression test, i18n / copy, mechanical pattern-following where the spec leaves little to interpret and failure is visible.
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 · 173 lines · 0 tokens per session scan A 6bfaf0b9dfb0
model-triage is a skill published in the GitHub repository joshukraine/dotfiles (429 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,701 tokens. 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 2026-08-30.
Other skills, from other repositories
morning-coffee
Open or refresh the all-day Morning Coffee engineering workspace with reviews, calendar, incidents, RFCs, chosen work, local tasks and project tags. Use for morning check-ins, daily planning, intraday refreshes or an engineering overview.
factory-mcp
Use the Warp Factory MCP to hand work to a software factory and collaborate with it — bundle local work and send it to the cloud, find factory tasks from a Slack thread / Linear ticket / description, and pull a task down to test or iterate locally and hand it back.
oz-notify-user
Send a progress notification to the user who triggered this Oz task (e.g., via Slack or Linear).
oz-finish-task
Report task completion or failure back to the Oz platform when done with a task.
mbo-plan
Plan a new objective end-to-end in this repo's docs/mbo Management-By-Objective system — turn a GitHub issue or a gss draft-PR worktree into consistent design/spec/plan artifacts and track it in docs/mbo/index.md. Use this whenever the user wants to START planning or designing a new feature, skill, CLI, or service…
issue-grooming
Use when the user wants to groom, triage, prioritize, or clean up the GitHub issue backlog of a repo: "groom the issues", "triage the backlog", "which issues are already done", "prioritize the open issues", "close stale issues", "label issues 1-5", "refactor old issues to match the repo", or a periodic backlog review…