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research-review

Get a deep critical review of research from Claude via claude-review MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.

69

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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 clear, actionable multi-round review workflow with concrete tool names, an executable install command, and explicit polling/convergence checkpoints. Its weaknesses are redundant prompt content that bloats the token budget and a monolithic structure with no progressive disclosure to reference files.

Suggestions

De-duplicate the initial-review prompt: keep the full template in the Prompt Templates section and reference it from Step 2 instead of restating it inline.

Tighten the Key Rules section by removing items already implied by the workflow steps (e.g., "Send comprehensive context in Round 1" duplicates Step 1).

Move the prompt templates into a referenced file (e.g., references/prompts.md) with a one-line pointer so SKILL.md stays a lean overview and improves progressive disclosure.

DimensionReasoningScore

Conciseness

The body is mostly efficient and avoids explaining concepts Claude already knows, but the "senior ML reviewer (NeurIPS/ICML level)" prompt appears in both Step 2 and the Prompt Templates section, and the Key Rules restate guidance already in the workflow, so it could be tightened.

2 / 3

Actionability

It gives concrete MCP tool identifiers (review_start, review_reply_start, review_status), a copy-paste install command, a precise polling protocol (save jobId, poll with bounded waitSeconds until done=true, reuse threadId), and specific prompt templates — fully actionable guidance.

3 / 3

Workflow Clarity

Five steps are clearly sequenced with an explicit async-completion checkpoint (poll review_status until done=true), convergence stop-conditions in Step 4, and an iterative dialogue feedback loop for responding to criticisms.

3 / 3

Progressive Disclosure

The body is well-organized into sections but is a single ~100-line monolithic file with no reference files and inline prompt templates that could be split out, so it does not reach the one-level-deep reference structure of the level-3 anchor.

2 / 3

Total

10

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12

Passed

Description

90%

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 well-constructed: it states a concrete capability, supplies natural trigger phrases, and gives explicit "Use when" guidance with a distinct niche. Its only limitation is that it names one main action rather than enumerating several specific actions.

DimensionReasoningScore

Specificity

"Get a deep critical review of research from Claude via claude-review MCP" names the domain and the primary action, but it describes a single action rather than listing multiple specific concrete actions as the level-3 anchor requires.

2 / 3

Completeness

It answers both what ("deep critical review of research from Claude via claude-review MCP") and when with an explicit "Use when user says ..." trigger clause, satisfying the level-3 anchor.

3 / 3

Trigger Term Quality

The quoted triggers — "review my research", "help me review", "get external review", and "critical feedback on research ideas, papers, or experimental results" — are natural, varied phrases a user would actually say, matching the good-coverage anchor.

3 / 3

Distinctiveness Conflict Risk

The external-Claude-reviewer framing and research-specific triggers ("review my research", "get external review") carve a clear niche unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
wanshuiyin/Auto-claude-code-research-in-sleep
Reviewed

Table of Contents

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