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research-lit

Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.

82

Quality

77%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/skills-codex/research-lit/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Discovery

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong skill description that clearly communicates its capabilities, provides explicit trigger guidance with natural user phrases, and is well-scoped to the academic research domain. It follows the recommended pattern of listing concrete actions followed by a 'Use when...' clause with multiple trigger terms. The description is concise without being vague.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Search and analyze research papers, find related work, summarize key ideas.' These are distinct, actionable capabilities.

3 / 3

Completeness

Clearly answers both 'what' (search, analyze, find related work, summarize) and 'when' with an explicit 'Use when...' clause listing specific trigger phrases and a general condition.

3 / 3

Trigger Term Quality

Includes natural keywords users would actually say: 'find papers', 'related work', 'literature review', 'what does this paper say', 'academic papers'. These cover a good range of natural user phrasings.

3 / 3

Distinctiveness Conflict Risk

Clearly scoped to academic/research paper domain with distinct triggers like 'literature review', 'related work', and 'academic papers'. Unlikely to conflict with general document or summarization skills due to the academic focus.

3 / 3

Total

12

/

12

Passed

Implementation

55%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill is highly actionable with excellent workflow clarity, providing concrete executable commands and a well-sequenced multi-step process with proper error handling. However, it is severely bloated — the repetitive script-location patterns, redundant de-duplication explanations for each source, and extensive inline examples make it far too long for a SKILL.md overview. The content desperately needs progressive disclosure, splitting source-specific details into separate reference files.

Suggestions

Extract the per-source bash script blocks (arXiv, Semantic Scholar, DeepXiv, Exa) into a separate SOURCES.md reference file, keeping only a summary table and one-line descriptions in the main SKILL.md.

Create a shared template for the script-location pattern (ARIS_REPO lookup → tools/ fallback → ~/.codex/ fallback) instead of repeating it verbatim for every source.

Move the extensive source selection examples and override syntax into a separate USAGE.md or collapse them into a compact table — the 12+ example lines are redundant given the source table already explains valid IDs.

Consolidate the de-duplication logic into a single section rather than repeating similar instructions (match by arXiv ID, then normalized title) for each source independently.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~300+ lines. It over-explains source selection with redundant examples, repeats de-duplication logic for every source, and includes lengthy bash script blocks for locating helper scripts that follow nearly identical patterns. Much of this could be condensed into a table or template pattern.

1 / 3

Actionability

The skill provides fully executable bash commands for each data source, concrete glob patterns for file discovery, specific API field lists, and clear output format (markdown table with defined columns). The code examples are copy-paste ready with fallback chains.

3 / 3

Workflow Clarity

The workflow is clearly sequenced (Steps 0a through 6) with explicit validation checkpoints: de-duplication between sources, PDF size verification (>10KB), rate limiting, and clear error handling (stop and report vs skip silently). Feedback loops are present for missing configurations.

3 / 3

Progressive Disclosure

Everything is crammed into a single monolithic file with no references to external documentation. The detailed bash scripts for each source (arXiv, Semantic Scholar, DeepXiv, Exa), the source selection examples, and the override syntax could all be split into separate reference files. The single file is overwhelming.

1 / 3

Total

8

/

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.

Validation11 / 11 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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