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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.

Quality

84%

Does it follow best practices?

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SecuritybySnyk

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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 content is a well-structured orchestration skill: lean, actionable, with an exceptionally clear phased workflow that includes triage, a planning gate, and error-recovery rules. Progressive disclosure is handled well through sibling-skill references, with only minor organization gaps such as the inlined Phase 4 template.

DimensionReasoningScore

Conciseness

The body is efficient and assumes Claude's competence — no known-concept explanations — with concrete file paths and a fill-in template. Minor trimming is possible (the 'Composing with Other Skills' section and some Key Rules restate the sibling-skill pointers from the Overview), so it fits anchor 4 rather than 5.

4 / 5

Actionability

Guidance is concrete for an instruction-only skill: named output files per phase, explicit exit criteria for Phase 1, a gate checklist for Phase 2, and a copy-ready PIPELINE_SUMMARY.md template. Per the rubric's code-vs-instruction note the absence of code is not penalized, but execution detail ultimately depends on the sibling skills, keeping it at anchor 4.

4 / 5

Workflow Clarity

Phases 0-5 are clearly sequenced with explicit validation checkpoints: Phase 0 checks whether FINAL_PROPOSAL.md exists, is stale, or misaligned; Phase 2 is a dedicated planning gate with the fallback 'If these answers are not crisp, tighten the final proposal first'; Phase 0 also has an in-doubt recovery rule ('prefer re-running aris-research-refine'). This matches the anchor-5 pattern of explicit validation steps and error-recovery feedback loops.

5 / 5

Progressive Disclosure

The body is a well-sectioned overview that defers stage detail to clearly signaled, one-level-deep sibling-skill links ('read these sibling skills only when needed'), and no bundle files exist to organize. It falls short of anchor 5 because the references point outside the bundle and the long Phase 4 summary template is inlined rather than split out.

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.

A strong description that clearly states what the skill does and when to use it, with a good set of natural trigger phrases including a Chinese synonym. The only weaknesses are minor: it could enumerate deliverables more comprehensively and has slight overlap risk with the two single-stage component skills it names.

DimensionReasoningScore

Specificity

The description names the two chained workflows ('aris-research-refine' and 'aris-experiment-plan') and both concrete outputs ('focused final proposal plus detailed experiment roadmap'), going beyond 1-2 actions. It stops short of comprehensive coverage (e.g., review history and tracker deliverables are not mentioned), matching anchor 4 rather than 5.

4 / 5

Completeness

It explicitly answers both questions: the 'what' ('Run an end-to-end workflow that chains... to focused final proposal plus detailed experiment roadmap') and the 'when' ('Use when the user wants a one-shot pipeline... or asks to 串起来, build a pipeline, do it end-to-end...') with concrete trigger phrases, matching the anchor-5 example structure.

5 / 5

Trigger Term Quality

Natural trigger phrases are well covered: 'one-shot pipeline', 'build a pipeline', 'do it end-to-end', 'generate both the method and experiment plan together', plus the Chinese synonym '串起来'. A few natural variants (e.g., 'experiment design', 'research roadmap') are missing, so it fits anchor 4 rather than 5.

4 / 5

Distinctiveness Conflict Risk

The integrated-pipeline niche is mostly distinct, with triggers ('pipeline', 'end-to-end', '串起来', 'generate both') clearly differing from single-stage use. There is minor overlap risk because the description names the two component skills that exist as separate skills, fitting anchor 4 rather than 5.

4 / 5

Total

17

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

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

Warning

relative_links

Relative link issues: 2 suspicious

Warning

Total

14

/

16

Passed

Repository

OpenLAIR/dr-claw

Path

skills/aris-research-refine-pipeline/SKILL.md

Reviewed

Table of Contents

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