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inno-code-survey

Acquires missing code repositories for the selected idea (Phase A) and conducts comprehensive code survey mapping academic concepts to implementations (Phase B). Outputs acquired_code_repos, updated_prepare_res, and model_survey for downstream use by inno-implementation-plan.

55

Quality

62%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/inno-code-survey/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable with concrete commands and schemas and a clear two-phase workflow, but it carries some redundant inline content and references a non-existent prompts/ directory, weakening both conciseness and progressive disclosure.

Suggestions

Create the referenced prompts/ directory with build_repo_acquisition_query.md and build_code_survey_query.md, or remove those references and the directory diagram entries to match the actual bundle.

Add an explicit Phase B validation checkpoint (e.g., verify every atomic concept has a located implementation before finalizing the survey) to close the missing feedback loop for the batch survey.

De-duplicate the path-conventions table and move the full survey query template out of the body to the referenced prompt file to tighten conciseness.

DimensionReasoningScore

Conciseness

Largely actionable and dense, but repeats path conventions already in the references and reproduces the full survey query template and long cache JSON blocks inline, which could be tightened.

2 / 3

Actionability

Provides copy-paste-ready commands (git clone --depth 1, curl to the GitHub API, python scripts/github_search_clone.py with concrete flags), concrete JSON cache schemas, exact file paths, and a tool-replacement table.

3 / 3

Workflow Clarity

Clear two-phase numbered sequence with per-phase checklists and an A4 clone-verification step, but Phase B's batch survey lacks an explicit validation/feedback loop, which caps batch-operation workflow clarity at 2.

2 / 3

Progressive Disclosure

Good overview with one-level-deep references to real files (references/*.md, scripts/*.py), but the body and directory diagram repeatedly reference a prompts/ directory and two prompt .md files that do not exist in the bundle.

2 / 3

Total

9

/

12

Passed

Description

60%

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 specific about actions and outputs but omits any explicit "when to use" trigger and relies on pipeline-internal terminology rather than natural user keywords.

Suggestions

Add a 'Use when...' clause stating the natural trigger conditions (e.g., when a selected research idea needs reference codebases surveyed or missing GitHub repos acquired).

Replace or supplement pipeline jargon ('Phase A/B', 'inno-implementation-plan') with terms a user would naturally say, such as 'code survey', 'find reference repositories', 'map paper concepts to code'.

Sharpen distinctiveness by contrasting with sibling skills so it is unlikely to fire for the wrong pipeline stage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ("Acquires missing code repositories", "conducts comprehensive code survey mapping academic concepts to implementations") and names specific output artifacts (acquired_code_repos, updated_prepare_res, model_survey).

3 / 3

Completeness

Clearly answers "what" the skill does but provides no "Use when..." trigger guidance, so "when" is entirely missing — which caps completeness at 2.

2 / 3

Trigger Term Quality

Contains relevant terms ("code repositories", "code survey", "academic concepts") but leans on pipeline-internal jargon ("Phase A", "inno-implementation-plan") rather than natural user phrasing, missing common variations.

2 / 3

Distinctiveness Conflict Risk

The research-pipeline niche is fairly distinct, but the pipeline-stage framing ("Phase A/B", "inno-implementation-plan") leaves moderate overlap risk with sibling inno-* skills rather than a fully distinct trigger.

2 / 3

Total

9

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 3 missing, 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository
OpenLAIR/dr-claw
Reviewed

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