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bmad-eval

Runs the evals of a BMad skill through the agent harness the user works in and reports what they show: baseline against the bare model, variant against a stripped or prior version, quality against a rubric, and trigger accuracy of the description with an optional optimization loop. Use when the user asks to evaluate, benchmark, test the triggers of, grade, or compare versions of a skill, or when the bmad-toolsmith skill asks for an eval of a skill it built.

Quality

95%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

100%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 an exemplary orchestration skill body: fully executable commands for every mode, a numbered activation sequence with halt-on-failure validation, explicit exit-code and error-handling semantics, and clean one-level-deep delegation of detail to existing reference and script files. No padding or over-explanation competes for the context window.

DimensionReasoningScore

Conciseness

The body is lean and dense: every sentence carries a command, path, exit code, or policy ("Exit 0 is a complete run; 1 means a case errored or timed out... 3 that no harness is recorded"), with no concept explanations Claude already knows and nothing to trim.

5 / 5

Actionability

Complete, copy-paste-ready commands are given for each mode ("uv run {skill-root}/scripts/run_evals.py --cases <cases-file> --skill-path <skill> --output-dir <dir> --mode quality|baseline|variant [--variant-path <skill>]") plus config-resolution, conversion, and aggregation commands, covering all common cases.

5 / 5

Workflow Clarity

"On activation" is a numbered sequence with explicit validation checkpoints ("halt with a clear error if not", "If nothing is found, halt and say so"), exit-code semantics, and error-recovery feedback loops (a grader error marks the case `grading_error`, "never a default verdict").

5 / 5

Progressive Disclosure

The body is a clear overview — a mode table mapping each mode to its script and reference — with deep material explicitly delegated one level deep to real bundle files ("The full shape and the strong-versus-weak expectation taxonomy are in references/eval-format.md", plus grader.md, harness.md, description-optimization.md, self-improvement.md), all of which exist.

5 / 5

Total

20

/

20

Passed

Description

88%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 description that explicitly states both what the skill does and when to use it, with concrete mode-by-mode capabilities and a mostly natural set of trigger phrases. The only weaknesses are a couple of missing natural trigger synonyms and slight genericness in the when-clause that could overlap with other skill-evaluation skills.

DimensionReasoningScore

Specificity

The description enumerates four concrete, distinct capabilities — "baseline against the bare model, variant against a stripped or prior version, quality against a rubric, and trigger accuracy of the description with an optional optimization loop" — which is comprehensive coverage of the skill's modes rather than minor gaps.

5 / 5

Completeness

It explicitly answers what ("Runs the evals of a BMad skill through the agent harness the user works in and reports what they show") and when ("Use when the user asks to evaluate, benchmark, test the triggers of, grade, or compare versions of a skill") with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Natural phrases like "evaluate, benchmark, test the triggers of, grade, or compare versions of a skill" give good synonym coverage, but a few natural user phrasings (e.g., "run the evals", "test this skill") are missing, placing it at the 4 rather than 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The BMad-skill eval niche is clear, but the trigger clause "of a skill" is generic enough that requests to evaluate or benchmark any skill could overlap with other evaluation skills — minor overlap risk, matching the 4 anchor rather than the minimal-conflict 5.

4 / 5

Total

18

/

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

bmad-code-org/BMAD-METHOD

Path

skills/bmad-eval/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.