Holds a session inside the task it was given: one open task with the files it may touch and the command that ends it, a guard that refuses writes outside that list, and checks that each ship with a violation and a near miss so none of them counts as coverage before it has been shown to work. It mounts beside a planning tool's roadmap, enforces the session boundary and never enforces the roadmap.
1 on GitHubby Victor Villegasv0.7.0-alphaMITupdated todayquality
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Plugin collet from marketplace slag in V-Songbird/slag. Commands read from the repo's manifest — today.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
What it installs
Skills (2)
check-writer
Writes a new check for a project that uses collet — the mistake it catches, the check itself, and the two fixtures that prove it. Use when asked to guard a mistake that keeps happening, to add a check or guardrail, to stop an agent repeating a specific error, or when a mistake in this repository has
task-harness
Mounts the collet harness into a project — the task ledger, the rules block in AGENTS.md/CLAUDE.md/.cursor/rules, and the checks directory — or reports on a project that already has one. Use when asked to set up a harness, guardrails, scope enforcement or session continuity for a repository, to adop
Improves agent navigation through a repository, turns session detours into approved map-file changes, and reconciles documentation and non-code development files with current behavior. Includes audit-only review, an approved layout migration, README review, host consistency and repository hygiene.
Appends two or three short follow-up questions after a substantive answer to help users check key facts, probe the reasoning, and notice missing context
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
wshobson/agents 42,461
Maintain collet?
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