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cccskills
免费在 GitHub 公开

review-pr

Review a specified Marin pull request for newly introduced defects, repository instruction violations, and concrete maintenance problems. Receive findings backed by code evidence, with optional posting of review comments to GitHub.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Independently review an identified Marin pull request for correctness, design fit, and consequences outside the diff. Supports correctness comments and holistic overviews.

集成工具GitHub
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适用场景

  • Check a pull request for newly introduced defects
  • Verify compliance with repository instructions
  • Review test quality and consistency across call sites
  • Post validated review findings to GitHub

包含的文件(3)

  • SKILL.md3.6 KB
  • references/correctness.md3.0 KB
  • references/holistic.md16.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Review a pull request

Review the requested pull request at the exact head named by the caller. The review is read-only except for comments posted when --comment is requested.

Review standard

A reviewable Marin pull request:

  • Implements the behavior claimed by its title and description without an introduced correctness, security, state-transition, or error-handling defect.
  • Follows the root and path-scoped AGENTS.md or CLAUDE.md instructions. If tests change, it also follows root TESTING.md and any scoped testing guide.
  • Keeps public interfaces, invariants, dependency direction, configuration, and types coherent across every changed call site. Marin does not preserve backward compatibility unless the request explicitly requires it.
  • Uses tests for behavior rather than implementation details, incidental prose, private state, tautologies, or mocks below an I/O boundary.
  • Keeps abstraction proportional to demonstrated reuse. Flag a maintainability problem only when the change creates a concrete structural obstacle, hidden assumption, or distant coupling that materially constrains nearby work.
  • Keeps documentation synchronized with behavior. The pull-request title and body must follow docs/dev-guide/writing-style/pull-requests.md; the body is the squash-merge commit message, not a template, file inventory, or test log.

Report only actionable defects introduced by the pull request. Validate every finding against the diff, relevant surrounding code, and applicable instructions. Do not report style preferences, speculative failures, harmless duplication in experiments/grug, or pre-existing problems. If the evidence is uncertain, omit the finding.

Choose the review mode

For a normal review, assess correctness and the whole design together. Scale the surrounding-code investigation to the size and risk of the change. Return one set of actionable findings; do not manufacture a second pass. For a substantial design change, use the holistic reference's review questions to examine callers, defaults, and consequences outside the diff.

When automation or the user requests a particular reporting contract, load only its reference:

  • Correctness review: certain defects, inline comments, and the correctness-review idempotency marker.
  • Holistic review: whole-change walkthrough, cross-boundary design findings, and a maintained overview with stable finding numbers. Its re-review gates and mechanical cleanup handoff apply only to this mode.

With --comment, choose the requested contract; default to correctness comments when no contract is named. Without --comment, return findings in the conversation and emit the selected mode's telemetry event; a normal review uses the correctness event. Keep the mode-specific telemetry names and comment markers: automation and historical dashboards use those protocol identifiers.

Reviewing never authorizes code edits. Use simplify-code only when the task explicitly asks for cleanup; manage-pr owns author-side fixes and publication.

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同一仓库的技能

Compare Zephyr changes using the same prepared dataset and matching execution settings. Analyze Finelog metrics for each processing stage to distinguish CPU efficiency, elapsed time, and peak memory changes, then report improvements, regressions, or tradeoffs.

中文简介正在准备中。当前显示英语简介。

  • Compare Zephyr performance before and after a PR
  • Assess speed gains against additional CPU usage
  • Check peak memory and out-of-memory regressions
marin-community/marin40042026年10月23日 更新

Register Hugging Face datasets for Marin by inspecting their structure without downloading the full dataset. Identify text fields, configurations, and data splits, then add a dataset module and validate the mapping with a sample.

中文简介正在准备中。当前显示英语简介。

  • Registering a Hugging Face dataset for Marin
  • Inspecting text fields without a full dataset download
  • Checking configurations and data splits
marin-community/marin40042026年10月23日 更新

add-grant

免费

Turn a specified GCP access request into a reviewable Pulumi change and pull request. Select the narrowest suitable role and encrypt personal email identities, covering resource permissions and Cloud Run viewer access through IAP, an access gateway.

中文简介正在准备中。当前显示英语简介。

  • Prepare a request for GCS bucket read access
  • Add a viewer to a Cloud Run service protected by IAP
  • Prepare service account impersonation permissions
marin-community/marin40042026年10月23日 更新

Add or update Pallas/Mosaic kernels, specialized computation routines for JAX. The skill covers reference implementations, output and gradient checks, public wrappers, fallback behavior, performance benchmarks, and hardware-specific tuning when requested.

中文简介正在准备中。当前显示英语简介。

  • Adding a Pallas kernel for a JAX computation
  • Checking outputs and gradients against a reference
  • Maintaining backend selection and fallback behavior
marin-community/marin40042026年10月23日 更新

Try model or training changes in a copied Grug or Grugformer experiment, document the differences, and bring successful changes back into the base template while removing superseded experiment code and checking behavior.

中文简介正在准备中。当前显示英语简介。

  • Try changes to attention or masking
  • Experiment with optimizers or training loops
  • Bring successful changes into the base template
marin-community/marin40042026年10月23日 更新

Organize Marin experiment reports into a maintained index, or archive explicitly named older experiments using lasting tags and issue references. Existing conclusions and canonical links are preserved so experiment records remain traceable.

中文简介正在准备中。当前显示英语简介。

  • Organizing an index of experiment reports
  • Consolidating canonical report entries
  • Archiving named legacy experiments
marin-community/marin40042026年10月23日 更新

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