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meta-abstract-screener

Screens research papers based on title/abstract and inclusion criteria, providing a structured Yes/No/Maybe decision. Use when you need to filter literature for meta-analysis or systematic reviews.

54

Quality

62%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/meta-abstract-screener/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

42%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 body has a clear workflow skeleton and points to specific scripts and references, but it is weighed down by generic boilerplate and relies on a referenced prompts file that is absent from the bundle, leaving the actual screening logic unspecified. Validation is also only optional, weakening the workflow.

Suggestions

Remove or condense the generic template sections ('When to Use', 'Key Features', 'Implementation Details', 'When Not to Use', 'Required Inputs', 'Output Contract', 'Validation and Safety Rules', 'Failure Handling', 'Input Validation') and keep only abstract-screening-specific guidance.

Either bundle 'references/screening_prompts.md' or inline the actual screening role/logic and a concrete example input abstract with its Yes/No/Maybe decision and 'Result'/'Reason' JSON output.

Make the validation step a required checkpoint with a fix-and-retry feedback loop rather than marking it 'Optional', since screening is typically run over batches of papers.

DimensionReasoningScore

Conciseness

The body is noticeably padded with generic boilerplate sections ('Use this skill when the request matches its documented task boundary', 'Execution model: validate the request, choose the packaged workflow') that restate process principles Claude already knows rather than skill-specific guidance.

2 / 5

Actionability

It provides some concrete guidance (specific commands like 'python scripts/screen_paper.py --help', an output schema of strictly 'Result' and 'Reason', and a 3-step workflow), but the core screening logic is delegated to 'references/screening_prompts.md', which is not present in the bundle, leaving key details missing.

3 / 5

Workflow Clarity

The Analysis/Formatting/Validation steps are sequenced, but validation is marked 'Optional' rather than an explicit checkpoint and there is no error-recovery feedback loop, so checkpoints are effectively missing.

3 / 5

Progressive Disclosure

There is section structure and one-level-deep signaled references ('references/screening_prompts.md', 'scripts/screen_paper.py'), but those referenced files do not exist in the bundle and substantial generic content is inlined rather than split out.

3 / 5

Total

11

/

20

Passed

Description

82%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.

The description is strong: it states a concrete purpose, gives an explicit 'Use when' trigger with domain-specific terms, and occupies a distinct niche. Its only weak spot is specificity, since it describes one screening action rather than a comprehensive set of capabilities.

DimensionReasoningScore

Specificity

It names the domain and concrete actions ('Screens research papers based on title/abstract and inclusion criteria', 'providing a structured Yes/No/Maybe decision'), but covers essentially one screening action rather than a list of several specific actions.

3 / 5

Completeness

It explicitly answers both what ('Screens research papers... providing a structured Yes/No/Maybe decision') and when ('Use when you need to filter literature for meta-analysis or systematic reviews') with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Natural terms a user would say are present ('research papers', 'title/abstract', 'inclusion criteria', 'filter literature', 'meta-analysis', 'systematic reviews'), giving good coverage though a few synonyms or file-type cues are missing.

4 / 5

Distinctiveness Conflict Risk

It carves a clear niche (literature screening for systematic reviews/meta-analyses) with distinct triggers, making conflict with other skills unlikely.

5 / 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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 11 missing

Warning

Total

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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