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pipeline-model-interpreter

解释 BK-CI 流水线或创作流的 Model JSON,帮助 AI 理解 Model -> Stage -> Container(Job) -> Element 的含义、启动参数、矩阵、Finally、审核与常见插件语义。用户贴出流水线 JSON、创作流 JSON、编排数据,或询问某个 Stage/Job/插件/atomCode/stepId 含义时使用。

72

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized, concise instruction skill with concrete field-level guidance and a clear multi-step workflow. Its main weakness is progressive disclosure: the extended-reading section points to reference/ files that are not present in the bundle.

Suggestions

Add the missing reference/ files referenced in 延伸阅读 (1-json-analysis-playbook.md, 2-common-plugin-and-container-hints.md, 3-classtype-and-enum-catalog.md) so the one-level-deep navigation actually resolves.

If the references are intentionally provided by another skill or external source, note that explicitly next to each path so Claude does not expect a local file.

Consider adding a brief inline example of a small Model JSON snippet mapped to the four-layer structure to lift actionability from concrete guidance to fully copy-paste-ready illustration.

DimensionReasoningScore

Conciseness

Lean and token-efficient with no padding and no re-explanation of concepts Claude already knows; every section (applicable/non-applicable scenarios, quick guidance, high-signal rules, pitfalls, extended reading) earns its place.

5 / 5

Actionability

Provides concrete, specific guidance — exact container types (trigger/vmBuild/normal), plugin types (linuxScript/marketBuild/subPipelineCall/manualReviewUserTask), and exact fields to inspect (@type/atomCode/data.input/data.output/additionalOptions) — but as interpretation guidance it lacks literal executable code, leaving a minor gap versus fully copy-paste-ready material.

4 / 5

Workflow Clarity

The 8-step 快速指导 gives a clear, ordered sequence with some checkpoints (step 6: don't fabricate, mark unknown atomCodes; step 7: don't mix enums across layers), but lacks explicit validate->fix->retry feedback loops, which is acceptable since this is interpretation rather than a destructive/batch operation.

4 / 5

Progressive Disclosure

The body is well-structured with clearly signaled one-level-deep references in 延伸阅读 (reference/1-json-analysis-playbook.md, reference/2-common-plugin-and-container-hints.md, reference/3-classtype-and-enum-catalog.md), but the referenced reference/ files do not exist in the bundle, breaking navigation.

3 / 5

Total

16

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A high-quality description that concisely states a specific capability and provides explicit, concrete trigger conditions in third-person voice. It clearly answers both what the skill does and when to use it.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — interpreting Model JSON, explaining Model->Stage->Container->Element semantics, startup params, matrix, Finally, review, and common plugin semantics — giving comprehensive coverage rather than vague language.

5 / 5

Completeness

Explicitly answers both what (解释...帮助 AI 理解...) and when ('用户贴出...或询问...时使用') with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Rich natural triggers users would say, including synonyms and specific field identifiers: '用户贴出流水线 JSON、创作流 JSON、编排数据' and '询问某个 Stage/Job/插件/atomCode/stepId 含义'.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (BK-CI pipeline/创作流 Model JSON interpretation) with distinct, specific triggers and minimal overlap risk with other skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
TencentBlueKing/bk-ci
Reviewed

Table of Contents

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