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prompt-governance

Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer).

67

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

67%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-structured, information-dense governance skill: concrete schemas, numeric thresholds, and a gated 8-step lifecycle. The main deductions are duplicated guidance between the Proactive Triggers and Anti-Patterns sections, prose-only (never concretized) descriptions of the eval runner and database registry, and no reference-file layering despite ~225 lines of single-file content.

Suggestions

Merge the Proactive Triggers and Anti-Patterns sections into one table (Anti-Pattern | Why It Fails | Better Approach | Flag When Seen) — four of the six rows currently duplicate content that appears in both sections, saving roughly 20 lines.

Concretize the two core Mode 2 deliverables: replace the prose 'The eval runner accepts a prompt version and golden dataset, calls the LLM for each example...' and 'To execute evals, build a runner that iterates...' with one concrete runner interface (function signature or example invocation) and expected result shape, and give the database-backed registry an actual table schema like the file-based registry's YAML example.

Move the A/B testing statistics guidance, the eval-types reference table, and the anti-pattern catalog into a references/ file (e.g., references/eval-types.md, references/ab-testing.md) with clearly signaled one-level-deep links from SKILL.md, keeping the main file as a lean overview of the three modes.

DimensionReasoningScore

Conciseness

Mostly efficient — tables and terse bullets, no explanation of concepts Claude already knows — but there is real duplication: 'Prompts hardcoded in application code', 'No golden dataset', 'No prompt rollback capability', and 'One person owns all prompt knowledge' each appear in both Proactive Triggers and Anti-Patterns; and 'The eval runner accepts a prompt version...' is restated almost verbatim by 'To execute evals, build a runner that iterates through the golden dataset...'. Not 4 because the redundancy is more than minor trimmable instances; not 2 because the bulk of the body is dense and earns its tokens.

3 / 5

Actionability

Largely concrete guidance: an exact directory layout, a full registry YAML schema, numeric pass thresholds ('95% or higher exact match', '100% schema validation'), and specific A/B parameters ('minimum 1 week or 1,000 requests per variant', 'p<0.05'). Not 5 because the two core implementation artifacts are only described, never specified — the database-backed registry is 'key tables for prompts and prompt_versions tracking slug, content, model, environment, eval_score' with no DDL or schema, and the eval runner is characterized ('returns a result with pass_rate, avg_score') without any interface or example; not 3 because everything around those gaps is executable-level specific.

4 / 5

Workflow Clarity

The Mode 3 lifecycle is a clearly sequenced 8 steps (BRANCH through ROLLBACK) with gates ('EVAL -- Run eval pipeline... automated in CI', 'COMPARE... vs. current production score', 'MONITOR... 24-48h post-deploy'), and rollback includes verification ('then verify by re-running evals against the restored version'). Not 5 because explicit error-recovery loops are missing — there is no stated action when evals fail or a promotion gate is missed — leaving validation mostly as gates rather than validate/fix/retry feedback loops.

4 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/), and the single-file body is well organized with clearly headed, navigable sections covering three modes. Not 5 because there are no one-level-deep reference files at all while roughly a third of the body (the A/B testing statistics guidance, the eval-type reference table, the anti-pattern catalog) is exactly the detail-level material the rubric expects split into well-signaled references; not 3 because what is inline is clearly sectioned and easy to navigate rather than a wall of misplaced content.

4 / 5

Total

15

/

20

Passed

Description

92%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 model description: explicit 'Use when' clause, enumerated concrete capabilities, a quoted trigger list, and negative boundaries redirecting to three sibling skills. Only weakness is a few missing natural trigger variations ('prompt management', 'prompt testing').

DimensionReasoningScore

Specificity

Lists five concrete actions — 'versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines' — giving comprehensive, non-abstract coverage of the skill's capabilities. Not a 4 because coverage is comprehensive rather than having minor gaps; not below 5 since no action listed is vague.

5 / 5

Completeness

Clearly answers both what (versioning, A/B tests, registries, regression prevention, eval pipelines) and when — an explicit 'Use when managing prompts in production at scale' clause plus a concrete 'Triggers:' list. Not 4 because the 'when' is fully explicit with concrete trigger phrases rather than merely present.

5 / 5

Trigger Term Quality

Explicit trigger list ('manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline') covers the natural phrases a user with this need would say. Not 5 because common variations like 'prompt management', 'prompt testing', 'prompt deployment', or 'golden dataset' are missing; not 3 because the listed terms go beyond merely 'some relevant keywords' and are phrases users would actually type.

4 / 5

Distinctiveness Conflict Risk

Owns a clear niche (production prompt governance) and explicitly fences off adjacent skills: 'NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design... NOT for LLM cost reduction'. Not 4 because the negative boundaries leave minimal overlap risk with the closest related skills.

5 / 5

Total

19

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

alirezarezvani/claude-skills

Path

engineering/prompt-governance/skills/prompt-governance/SKILL.md

Reviewed

Table of Contents

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