darwinian-evolver

Evolve prompts/regex/SQL/code with Imbue's evolution loop.

Quality

71%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./optional-skills/research/darwinian-evolver/SKILL.md

Quality

Content

92%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a strong, lean, executable skill: concise, fully actionable with real shipped scripts, and a well-sequenced workflow with an explicit verification checkpoint. The only notable weakness is progressive disclosure — a referenced templates/ file does not exist in the bundle, leaving one broken path.

Suggestions

Add the referenced templates/custom_problem_template.py to the bundle, or remove the 'The skill ships templates/custom_problem_template.py' line to avoid a broken reference.

Consider moving the hyperparameter table or pitfalls into a reference file so SKILL.md stays an overview, since the rubric favors one-level-deep splitting for non-trivial skills.

Verify the OpenRouter quick-start command's SKILL_DIR path matches the actual install location so the copy-paste example resolves.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence: no preamble explaining what evolution or LLMs are, every section earns its place (install, quick start, hyperparameter table, pitfalls), and it avoids the padded-concept style of the level-1 anchor.	3 / 3
Actionability	Copy-paste-ready bash and Python commands throughout (install, parrot smoke test, OpenRouter driver invocation, snapshot inspection), concrete flag tables with defaults and change-guidance, and a fully shipped reference driver in scripts/parrot_openrouter.py — fully executable rather than pseudocode.	3 / 3
Workflow Clarity	Install → verify → smoke-test → custom-problem is clearly sequenced, with an explicit 'Verification' checkpoint ('exit code 0 from this is sufficient') and a numbered three-part Problem definition; the body also warns about destructive/batch pitfalls (aggressive concurrency, AGPL import) which is the feedback-loop care the rubric rewards.	3 / 3
Progressive Disclosure	Structure is good and references to real bundle files are clearly signaled (scripts/parrot_openrouter.py, scripts/show_snapshot.py both exist), but the body also references 'templates/custom_problem_template.py' which is not present in the bundle, and there are no references/ or assets/ — so a referenced path is broken, capping this at 2 rather than a clean level-3 split.	2 / 3
	Total	11 / 12 Passed

Description

50%

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 is concise and third-person with a concrete domain, but it omits any explicit 'when to use' trigger clause and natural trigger phrases that the body actually contains, capping completeness and trigger-term quality at 2. It is a clear level-2 description: accurate and specific enough, but not triggering guidance-rich.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks to optimize a prompt, evolve a regex/SQL query, or auto-improve a small code snippet against a scorer.'

Surface natural trigger terms the user would actually say ('optimize this prompt', 'auto-improve this code', 'evolve a regex') into the description rather than only listing artifact types.

Distinguish the skill from generic prompt-engineering by naming the fitness-function prerequisite in the description.

Dimension	Reasoning	Score
Specificity	Names a concrete domain ('prompts/regex/SQL/code') and the action ('Evolve') but does not enumerate the multiple specific operations (optimize, search, auto-improve) found in the body, so it sits at 'names domain and some actions, but not comprehensive' rather than the multi-action level 3.	2 / 3
Completeness	It clearly answers 'what does this do' ('Evolve prompts/regex/SQL/code with Imbue's evolution loop') but there is no 'when should Claude use it' clause — the rubric caps completeness at 2 when an explicit 'Use when...' trigger is missing.	2 / 3
Trigger Term Quality	'prompts/regex/SQL/code' are relevant keywords a user might mention, but there are no natural trigger phrases users would actually say ('optimize this prompt', 'evolve a regex'), missing common variations that the body itself contains.	2 / 3
Distinctiveness Conflict Risk	'Imbue's evolution loop' carves a fairly distinct niche unlikely to conflict broadly, but without explicit trigger guidance it could still overlap with general prompt-engineering or optimization skills, so it is 'somewhat specific but could still overlap' rather than a clear level-3 niche.	2 / 3
	Total	8 / 12 Passed

Validation

81%

Warnings & errors only

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

Validation — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: NousResearch/hermes-agent
Path: optional-skills/research/darwinian-evolver/SKILL.md
Commit: 4c9628e

Reviewed: about 15 hours ago

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