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github-workflow-automation

Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.

44

Quality

46%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/github-workflow-automation/SKILL.md

The canonical home for this skill is github-workflow-automation in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

57%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.

The content is rich with concrete, actionable GitHub Actions examples and clear topical sections, but it is over-long for a single SKILL.md and lacks validation checkpoints around its destructive git operations. Splitting workflows into reference files and adding verify-before-proceed steps would materially raise quality.

Suggestions

Add explicit validation/feedback-loop steps before destructive actions: verify rebase success before force-push, confirm rollback target is stable before checkout, and re-validate after cherry-pick conflicts.

Move the full workflow YAML files into a references/ or scripts/ bundle and keep SKILL.md as an overview with one-level-deep links, reducing the inlined token load.

Define or stub the helper functions (analyzeIssue, callAI, ai.analyze/chat/resolveConflict) so the TypeScript examples are fully executable rather than illustrative.

DimensionReasoningScore

Conciseness

The body is mostly executable code with little padded prose, but ~840 lines inlining six-plus full workflow files is a heavy token load that could be tightened or split into reference files.

3 / 5

Actionability

Abundant concrete, copy-pasteable YAML and TypeScript, but several examples call undefined helpers (analyzeIssue, callAI, ai.analyze, ai.chat, ai.resolveConflict), leaving minor execution gaps.

4 / 5

Workflow Clarity

Sections are well organized, but destructive/batch operations (force-push rebase, rollback, cherry-pick, branch cleanup) lack validation checkpoints, capping workflow clarity at 3 per the rubric.

3 / 5

Progressive Disclosure

No bundle files exist and all content is inlined in SKILL.md; section headers give structure, but full workflows that belong in separate files are inline with no internal references.

3 / 5

Total

13

/

20

Passed

Description

36%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.

The description names its domain but relies on generic language ("patterns", "automating") and omits any explicit use-when trigger guidance. It is recognizable but not specific enough to reliably surface or distinguish from related DevOps skills.

Suggestions

Replace "Patterns for automating" with concrete actions, e.g. "Automates PR reviews, issue triage, and CI/CD validation with AI in GitHub Actions workflows."

Add an explicit trigger clause: "Use when setting up AI-assisted GitHub Actions, automating PR review or issue triage, or integrating AI into CI/CD pipelines."

Include natural user keywords such as "GitHub Actions", "CI/CD", "PR review", and "issue triage" to improve trigger matching.

DimensionReasoningScore

Specificity

"Patterns for automating GitHub workflows with AI assistance" names the domain but the actions are generic ("patterns", "automating") with no concrete operations listed.

2 / 5

Completeness

The "what" is vague ("Patterns for automating...") and there is no "when"/"Use when" trigger clause at all, matching a vague what with absent when.

2 / 5

Trigger Term Quality

Terms like "GitHub workflows", "AI assistance", and "DevOps" are relevant but miss common natural variations a user would say ("GitHub Actions", "PR review", "CI/CD").

3 / 5

Distinctiveness Conflict Risk

The GitHub + AI + workflow-automation niche is somewhat specific, but the broad "patterns"/"DevOps" framing leaves overlap risk with general DevOps skills.

3 / 5

Total

10

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (850 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

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