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aris-research-refine-pipeline

Run an end-to-end workflow that chains `aris-research-refine` and `aris-experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.

68

Quality

82%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

81%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 body presents a clear, well-validated five-phase pipeline with concrete templates, output paths, and explicit gates, while staying lean. Its main weaknesses are minor redundancy in listing output files and references to sibling skills that cannot be verified within the provided bundle.

DimensionReasoningScore

Conciseness

The body is lean — checklists, short bullets, and templates with no explanation of concepts Claude already knows. Minor trimming is possible: the output file list appears in both "Default Outputs" and the Phase 4 template, and the Phase 5 summary block repeats it again.

4 / 5

Actionability

Guidance is concrete: exact file paths to check ("refine-logs/FINAL_PROPOSAL.md"), explicit exit criteria, a complete copy-paste-ready PIPELINE_SUMMARY template, and exact text for the final user summary. Minor gap: it never specifies how to invoke the sibling workflows (slash command vs. reading their SKILL.md).

4 / 5

Workflow Clarity

Phases 0-5 are clearly sequenced with explicit validation checkpoints: Phase 0 triages the existing proposal and loops back to re-run refinement if stale or mismatched, Phase 2 is a five-question gate check with a corrective action ("If these answers are not crisp, tighten the final proposal first"), and Phase 1 has explicit exit criteria. This matches the anchor 5 pattern of clear sequence, validation, and checklists.

5 / 5

Progressive Disclosure

Structure is good: stage detail is delegated one level deep and clearly signaled ("read these sibling skills only when needed"), and the body is well-sectioned at appropriate length. However, no bundle files exist (no references/, scripts/, or assets/) and the referenced sibling paths ("../research-refine/SKILL.md", "../experiment-plan/SKILL.md") are not resolvable within this bundle, leaving a minor organization gap.

4 / 5

Total

17

/

20

Passed

Description

83%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.

The description clearly states what the skill does and when to use it, with natural trigger phrases (including a Chinese-language one) and concrete deliverables. It is specific and distinct, with only minor gaps in action coverage and trigger synonym breadth.

DimensionReasoningScore

Specificity

"Run an end-to-end workflow that chains `aris-research-refine` and `aris-experiment-plan`" names the exact composition, and "focused final proposal plus detailed experiment roadmap" names concrete deliverables. It falls between anchor 3 (only 1-2 actions) and anchor 5 (multiple comprehensive actions), listing several specific actions with minor gaps such as not mentioning the pipeline summary output.

4 / 5

Completeness

Both what ("Run an end-to-end workflow that chains... one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap") and when ("Use when the user wants... or asks to '串起来', build a pipeline, do it end-to-end") are explicitly stated with concrete trigger phrases, matching the anchor 5 example.

5 / 5

Trigger Term Quality

"build a pipeline", "do it end-to-end", "串起来", and "generate both the method and experiment plan together" are natural phrases users would say. Coverage is good but misses common variations like "plan the experiments" or "refine then plan".

4 / 5

Distinctiveness Conflict Risk

Triggers like "generate both the method and experiment plan together" and "one-shot pipeline" carve a clear niche distinct from the staged skills, and the body explicitly routes single-stage requests elsewhere. Minor overlap risk remains with the two component skills for phrases like "build a pipeline".

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

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

15

/

16

Passed

Repository
OpenLAIR/dr-claw
Reviewed

Table of Contents

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