labtasker

In the author's own words, from each skill's SKILL.md.

• labtasker

  Use Labtasker v2 to queue and run ML inference, evaluation, or experiment Tasks; set experimental Task dependencies; migrate pipelines; design routes and Workers; inspect Task demand and Worker activity; and archive or recover Tasks. GPU allocation, cluster management, and artifact storage remain external.

  skills/labtasker/SKILL.md on GitHub (opens in a new tab)

• documentation

  Write or revise Labtasker's README and user documentation, especially product positioning, tutorials, guides, examples, case studies, and navigation. Preserve the project's direct, plain-English style for ML researchers, agent-friendly workflow, and contract accuracy. Do not use for code-only work; pair observable behavior changes with the public-contract-change skill.

  .agents/skills/documentation/SKILL.md on GitHub (opens in a new tab)

• public-contract-change

  Change Labtasker's public Task lifecycle, HTTP API, Python API, CLI, configuration, query language, or persisted schema while keeping every public surface and invariant aligned. Do not use for internal refactors with no observable behavior change.

  .agents/skills/public-contract-change/SKILL.md on GitHub (opens in a new tab)

• release

  Prepare, validate, tag, or publish a Labtasker release. Use for version bumps, release readiness, release artifacts, tags, GitHub releases, or PyPI publication; do not use for ordinary development builds.

  .agents/skills/release/SKILL.md on GitHub (opens in a new tab)

• skill-development

  Develop and regression-test Labtasker's public Agent Skill with concise real-user requests, independent examiner and candidate agents, outcome checks, and bounded self-revision. Use when changing skills/labtasker, evaluating its usability, or adding feature workflow coverage; not for product unit/integration tests or ordinary documentation alone.

  .agents/skills/skill-development/SKILL.md on GitHub (opens in a new tab)

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