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doraval

Use doraval to validate, measure drift, and judge skills and plugins. Use when authoring or reviewing context engineering artifacts for AI coding agents (works for Codex too).

Quality

85%

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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 lean, command-first reference whose four exact doraval invocations make it immediately actionable, with a clear simple workflow and no unnecessary external references. Its main weakness is the marketing-style opening and self-referential meta sentence, plus absent guidance on interpreting command output.

Suggestions

Delete or compress the marketing opener ('Scale your AI context... Context engineering toolkit for AI coding agents') and the self-referential sentence into a single line, cutting ~4 lines of pure padding.

Add one line per command on what to do with its output (e.g., 'if drift is reported, update the rubric or the skill and re-run'), turning the command list into a validate-fix-retry loop.

Verify the referenced .agents/plugins/marketplace.json path exists in the bundle, and add short ## headers (Commands, Testing in Codex) to make the structure scannable.

DimensionReasoningScore

Conciseness

The opening paragraph — "Scale your AI context for coding agents. Make your next context work (skills, plugins & more) for your team, community, or self. Context engineering toolkit for AI coding agents." — is marketing tagline padding that repeats "for AI coding agents" and adds nothing actionable, and "This skill demonstrates a complete, self-referential example..." is meta commentary. The command list itself is tight, so this is 'mostly efficient but includes some unnecessary explanation', not 2 (only one padded paragraph) and not 4 (that paragraph could be cut entirely with no loss).

3 / 5

Actionability

Four copy-paste-ready commands with concrete paths ("doraval validate .", "doraval skill validate ./skills/doraval/", "doraval skill drift ./skills/doraval/", "doraval skill judge ./skills/doraval/") map each need to an exact invocation, and the closing rule "Always run `doraval validate` before sharing or publishing a plugin" is concrete. Not 4 — the commands cover all common cases with no gaps.

5 / 5

Workflow Clarity

"When you need to check a skill or Codex plugin:" pairs each scenario with an exact command, and the Codex test steps 1-4 form a clear sequence. Not 5 — there are no checkpoints on what to do with output (e.g., how to act on a drift report or failed validation); not 3 — sequences are explicit and complete rather than merely listed with implicit checkpoints.

4 / 5

Progressive Disclosure

The body is ~25 lines with no bundle files, so inline placement is appropriate, and content is logically grouped (commands, rule, test steps). Not 5 — there are no section headers to aid navigation, and it references ".agents/plugins/marketplace.json", a path that does not exist in this bundle; not 3 — given its size, nothing here clearly belongs in a separate file.

4 / 5

Total

16

/

20

Passed

Description

87%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: it names the tool, lists three concrete capabilities, and provides an explicit, trigger-rich 'Use when' clause for authoring or reviewing AI-agent skills/plugins. The only weakness is mild jargon ('context engineering artifacts') that may not match every user's phrasing.

DimensionReasoningScore

Specificity

"validate, measure drift, and judge skills and plugins" names the domain (doraval) and three concrete actions with explicit targets. Not 3 (more than 1-2 actions); not 5 (minor gaps — it never says what validation/judging entail, e.g., rubric-based scoring or lint rules).

4 / 5

Completeness

Both halves are explicit: what = "Use doraval to validate, measure drift, and judge skills and plugins"; when = "Use when authoring or reviewing context engineering artifacts for AI coding agents (works for Codex too)" with concrete trigger words. Not 4 — the when-clause is explicit and specific, not merely present-but-vague as the 4 anchor requires.

5 / 5

Trigger Term Quality

"skills and plugins", "authoring or reviewing", "AI coding agents", "Codex" give good coverage of natural terms a user would say. Not 5 (common variations like "check my skill's quality", "lint a plugin", or file-extension cues are missing); not 3 (keywords are relevant and go beyond a single generic phrase).

4 / 5

Distinctiveness Conflict Risk

A named tool (doraval) plus a clear niche — validating/judging AI agent skills and plugins — yields distinct triggers with minimal conflict risk; general code-review skills target code, not context artifacts. Not 4: the niche is clear and specific, not just "mostly distinct".

5 / 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

saif-shines/doraval

Path

test/fixtures/examples/my-codex-plugin/skills/doraval/SKILL.md

Reviewed

Table of Contents

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