CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

inno-paper-reviewer

Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), ML/CS conference review forms (NeurIPS/ICML/ICLR/ACL style), and constructive feedback. Best for actual review writing and manuscript revision. To evaluate a research idea rather than a manuscript, use inno-idea-eval.

Quality

80%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/inno-paper-reviewer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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.

A well-structured, highly actionable review workflow with genuine bundle references and a clear staged process. Its main weakness is token efficiency: long checklists of broadly-known criteria and a padded presentation section that should be trimmed or moved to reference files.

Suggestions

Move the presentation-review checklists and example log to a new references/presentations.md, keeping only the mandatory image-conversion workflow and a concise criteria summary in SKILL.md.

Trim generic writing-quality questions ('Is grammar and spelling correct?', 'Is the passive voice overused?') and other criteria an expert model already knows, keeping only domain-specific checks.

De-duplicate the inline common-issues lists in the Results and Discussion sections by pointing to references/common_issues.md instead of restating the catalog.

DimensionReasoningScore

Conciseness

The ~550-line body enumerates many review questions a competent model already knows ('Is grammar and spelling correct?', 'Is the passive voice overused?'), the presentation section's example timestamped log is padding, and inline issue catalogs duplicate references/common_issues.md.

3 / 5

Actionability

Concrete, executable guidance throughout: staged workflow, numbered comment structure, specific ML review score scales ('soundness, presentation, and contribution (1-4 each)... confidence (1-5)'), and copy-paste-ready conversion commands (pdftoppm and PyMuPDF one-liners). Minor gaps remain, e.g. no complete sample review output.

4 / 5

Workflow Clarity

A clear 7-stage sequence, a mandatory presentation-conversion workflow with an explicit fallback ('If neither is available, ask the user to install one'), and a Final Checklist provide most checkpoints, though no explicit validate-fix-retry loops are specified.

4 / 5

Progressive Disclosure

Both bundle files (references/reporting_standards.md, references/common_issues.md) are real, clearly signaled, and one level deep (Stage 4 pointer plus a Resources section with descriptions). However, the ~150-line presentation section and inline issue catalogs are content that belongs in reference files.

4 / 5

Total

15

/

20

Passed

Description

87%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 capabilities, explicit use conditions, and even sibling-skill disambiguation. Its only weaknesses are modest: noun-phrase-heavy capability listing and a few missing colloquial trigger synonyms.

DimensionReasoningScore

Specificity

Lists several concrete capabilities ('methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE)', 'ML/CS conference review forms (NeurIPS/ICML/ICLR/ACL style)') but is noun-phrase-led rather than action-verb-led, leaving minor gaps versus the comprehensive action-verb anchor.

4 / 5

Completeness

Explicitly answers both what ('Structured manuscript/grant review with checklist-based evaluation') and when ('Use when writing formal peer reviews...'), with concrete trigger contexts and clear scope boundaries ('Best for actual review writing and manuscript revision').

5 / 5

Trigger Term Quality

Good natural-keyword coverage including 'peer review', 'manuscript', 'grant', CONSORT/STROBE, and venue names, but common variations like 'review a paper', 'referee report', or 'reviewer feedback' are missing.

4 / 5

Distinctiveness Conflict Risk

Clear peer-review niche with distinct triggers, plus explicit disambiguation against a sibling skill ('To evaluate a research idea rather than a manuscript, use inno-idea-eval'), minimizing conflict risk.

5 / 5

Total

18

/

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

skill_md_line_count

SKILL.md is long (564 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

Total

14

/

16

Passed

Repository

OpenLAIR/dr-claw

Path

skills/inno-paper-reviewer/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.