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experiment-designer

Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.

60

Quality

75%

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tessl review fix ./.gemini/skills/experiment-designer/SKILL.md

The canonical home for this skill is experiment-designer in alirezarezvani/claude-skills

SKILL.md
Quality
Evals
Security

Quality

Content

60%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 body with a clear six-step workflow and mostly concrete guidance, dragged down by a broken bundle: all three referenced files (two references and the sample-size script) are missing, so the primary executable tooling and the progressive-disclosure layer don't actually work. Fixing the dangling files would lift both actionability and progressive disclosure substantially.

Suggestions

Ship the referenced bundle files — 'references/experiment-playbook.md', 'references/statistics-reference.md', and 'scripts/sample_size_calculator.py' — or remove the references; currently all three paths are dangling.

Signal what each reference contains at the point of reference (e.g., '**Playbook**: end-to-end experiment design walkthrough in references/experiment-playbook.md') and move the 'See:' list to a purpose-labeled section.

Make the sample-size guidance executable without the script: show the calculator's expected output, and/or inline the sample-size formula as a fallback so the workflow's step 3 is actionable even if the script is unavailable.

DimensionReasoningScore

Conciseness

The body is lean and list-driven with no padded paragraphs, but a few lines re-teach concepts Claude already knows (ICE component definitions like 'Impact: potential upside', and 'p-value < alpha indicates evidence against null'), matching the efficient-with-minor-trims anchor at 4 rather than fully lean at 5.

4 / 5

Actionability

Guidance is concrete in shape — an If/Then/Because template with placeholders, the ICE formula, and two bash invocations with flags — but every command calls 'scripts/sample_size_calculator.py', which does not exist in the bundle, and no expected output or fallback formula is given, so the central tooling is not executable as shipped. This is a key missing detail (anchor 3) rather than a minor gap (anchor 4).

3 / 5

Workflow Clarity

The Core Workflow gives a clear six-step sequence (hypothesis → metrics → sample size → prioritize → launch with stopping rules → interpret) and the Hypothesis Quality Checklist provides a checkpoint, but the checklist is not wired into the flow and pre-launch validation (e.g., a sample-ratio-mismatch check, mentioned only as a pitfall) is implicit — matching the most-checkpoints-with-minor-gaps anchor at 4.

4 / 5

Progressive Disclosure

The 'See:' section points to 'references/experiment-playbook.md' and 'references/statistics-reference.md' and the tooling section relies on 'scripts/sample_size_calculator.py', yet none of these files exist in the bundle — the disclosure promise is broken by dangling references, and the bare 'See:' list gives no signal of each file's contents. This falls below the poorly-signaled-but-present-references anchor at 3, closer to the broken-structure anchor at 2.

2 / 5

Total

13

/

20

Passed

Description

80%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 strong, concise, third-person description with explicit trigger guidance and five specific capabilities covering the whole experiment lifecycle. Its main limitation is that the 'what' is only embedded inside the 'Use when' gerund list rather than stated as a distinct capability sentence, and a few natural trigger synonyms (e.g., 'A/B test', 'split test') are absent.

Suggestions

Add a leading capability sentence (e.g., 'Designs and evaluates product A/B experiments end-to-end.') so the 'what' is explicit rather than inferred from the 'Use when' clause.

Include common trigger synonyms such as 'A/B test', 'split test', or 'experiment results' to broaden natural-term coverage.

DimensionReasoningScore

Specificity

The description lists five concrete actions spanning the full experimentation workflow — 'planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes' — which matches the comprehensive-coverage anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

The 'when' is explicit and trigger-phrase-driven ('Use when planning product experiments, writing testable hypotheses...'), and the gerund actions double as an implicit 'what', but there is no standalone capability statement, so it falls short of the explicit what+when anchor at 5 and above the weakly-implied-'what' anchor at 3.

4 / 5

Trigger Term Quality

Natural phrases like 'sample size', 'A/B outcomes', 'testable hypotheses', and 'prioritizing tests' are present, but common variations users would say ('A/B test', 'split test', 'experiment results', 'hypothesis testing') are missing, matching good-but-incomplete coverage rather than comprehensive at 5.

4 / 5

Distinctiveness Conflict Risk

The product-experimentation niche with triggers like sample size estimation and A/B outcome interpretation is mostly distinct, with only minor overlap risk against a general statistics or data-analysis skill, matching the 4 anchor.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 5 missing

Warning

Total

15

/

16

Passed

Repository

alirezarezvani/claude-skills

Path

.gemini/skills/experiment-designer/SKILL.md

Reviewed

Table of Contents

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