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academic-paper-reviewer

Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정.

63

Quality

76%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

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

Quality

Content

56%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 skill body presents a well-sequenced multi-agent review workflow with explicit checkpoints and Iron Rules, but it is dense with repeated disclaimers and version-tag prose, and it references agent, template, script, and example files that are not present in the bundle, weakening both actionability and navigation.

Suggestions

Ship the referenced bundle files (agents/*.md, templates/*.md, scripts/*.py, examples/*.md) or remove their tables, so the Agent File References, Templates, Examples, and script citations resolve to real files.

Deduplicate the Devil's-Advocate-CRITICAL rule — state it once in Checkpoint Rules and link from Anti-Patterns and Quality Standards rather than repeating the full #574 B1 wording three times.

Move the dense Cross-Model Reviewer Track and Model Tiering detail into reference files, keeping only a one-line summary plus a link in SKILL.md to reduce token load.

DimensionReasoningScore

Conciseness

The body is mostly operational signal (agents, phases, modes, checkpoints), but it carries noticeable padding — the Devil's-Advocate-CRITICAL rule is restated in Checkpoint Rules, Anti-Patterns, and Quality Standards, and the Cross-Model Reviewer Track and Model Tiering sections are dense with version-tag prose that could be trimmed or moved to references.

3 / 5

Actionability

The Mode Selection Logic input→mode table and the ASCII orchestration workflow are concrete guidance, but the Quick Start is abstract ('Review this paper: [paste paper]') and the agent definition files, scripts, and templates referenced throughout (agents/*.md, scripts/*.py, templates/*.md) are not present in the bundle, leaving execution incomplete.

3 / 5

Workflow Clarity

The 3-phase workflow (Phase 0 → 1 → 2 → 2.5) is clearly sequenced with explicit checkpoints (present Reviewer Configuration Card to user) and Iron Rules acting as checklists, plus a re-review feedback loop; held below 5 because the actual per-agent dispatch mechanics and slash-command syntax are underspecified in the body.

4 / 5

Progressive Disclosure

Structure is decent — dedicated tables for Reference Files, Templates, Agent File References, and Examples with one-level-deep links — but navigation is broken for the Agent File References, Templates, Examples, scripts/, and shared/ tables whose targets are not shipped in the bundle, so several signaled references point nowhere.

3 / 5

Total

13

/

20

Passed

Description

96%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, third-person description that clearly states what the skill does and when to use it, with extensive multi-language trigger coverage. Slightly dense due to an embedded honesty disclaimer and the long trigger list, but every element earns its place.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — '5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate)' plus six named modes (full, re-review, quick, methodology focus, Socratic guided, calibration) — giving comprehensive coverage of what the skill does.

5 / 5

Completeness

Explicitly answers both what ('Multi-perspective academic paper review... Runs a 5-seat... panel') and when ('Triggers on: review paper, peer review...'), with concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural-keyword coverage including synonyms across three languages — 'review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review...' plus Korean and Traditional Chinese equivalents — matching the kind of phrases users actually say.

5 / 5

Distinctiveness Conflict Risk

The 'academic paper review' niche is clear with domain-specific triggers (peer review, manuscript review, referee report, calibrate reviewer), but the bare phrase 'review paper' could overlap with other review skills in a large ecosystem, so it sits just below the minimal-conflict anchor.

4 / 5

Total

19

/

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

referenced_paths_exist

Referenced path issues: 5 missing

Warning

Total

14

/

16

Passed

Repository
Imbad0202/academic-research-skills
Reviewed

Table of Contents

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