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systematic-review-screener

Automated abstract screening tool for systematic literature reviews with PRISMA workflow support.

48

Quality

51%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./scientific-skills/Evidence Insight/systematic-review-screener/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%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 is action-oriented and executable with concrete commands and examples, but it is substantially padded with boilerplate, has no validation feedback loop in the batch-screening flow, and references a missing PDF, holding it near the midpoint.

Suggestions

Remove generic template boilerplate (Security Checklist, Evaluation Criteria, Lifecycle Status, Output Requirements, Response Template, User Checkpoints) that does not add skill-specific knowledge.

Add an explicit validate->fix->retry checkpoint to the screening workflow (e.g. run `python -m py_compile scripts/main.py`, confirm expected output files, re-run on parse failure) before declaring results.

Either add the missing references/prisma_2020_checklist.pdf or remove it from the References list so signaled paths resolve.

DimensionReasoningScore

Conciseness

The 348-line body is noticeably padded with generic template boilerplate (Security Checklist, Evaluation Criteria, Lifecycle Status, Risk Assessment, Output Requirements/Contract, Response Template, etc.) that restates obvious practices rather than adding domain knowledge Claude lacks, and it duplicates the identical `python scripts/main.py --help` command twice in the audit-ready block.

2 / 5

Actionability

It provides mostly executable guidance — concrete CLI invocations (`python scripts/main.py --input references.csv --criteria criteria.yaml --prisma`), a complete criteria YAML example, an output-file table, and a PRISMA JSON shape — with only minor gaps (e.g. `pip install -r requirements.txt` with no bundled requirements file, and duplicated help commands).

4 / 5

Workflow Clarity

A Workflow and Decision Algorithm are sequenced and there is a fallback path, but the batch/destructive screening operations lack an explicit validate-then-fix feedback loop with concrete checkpoints in the main flow; the rubric caps batch-operation skills without clear validation feedback loops at 3.

3 / 5

Progressive Disclosure

Structure is present with a Quick Check, References section pointing to criteria_template.yaml and sample_references.csv (both real), but one referenced file (references/prisma_2020_checklist.pdf) does not exist and navigation/signaling is inconsistent, leaving organization at the 'some structure but could be better organized' anchor.

3 / 5

Total

12

/

20

Passed

Description

53%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 domain-specific and states a clear capability, but it lacks an explicit 'Use when...' trigger clause and broad natural-synonym coverage, capping completeness and trigger quality at the midpoint.

Suggestions

Add an explicit 'when' clause, e.g. 'Use when screening PubMed/MEDLINE abstracts for a systematic review or building a PRISMA flow diagram.'

Expand trigger terms with natural synonyms and file extensions users actually say: 'systematic review', 'abstract screening', 'inclusion/exclusion criteria', 'PubMed', 'MEDLINE', '.csv', '.nbib'.

Surface 1-2 more concrete actions (confidence scoring, conflict flagging, PRISMA export) to raise specificity.

DimensionReasoningScore

Specificity

The description names the domain ('systematic literature reviews') and one concrete action ('abstract screening') plus the PRISMA workflow support, but does not enumerate multiple specific actions like generating flow diagrams or confidence scores, leaving it at the 'domain plus 1-2 concrete actions' anchor.

3 / 5

Completeness

It gives a clear 'what' (automated abstract screening with PRISMA workflow support) but provides no 'when' / 'Use when...' trigger clause, which the rubric explicitly caps at 3 when such guidance is missing.

3 / 5

Trigger Term Quality

It includes relevant keywords ('abstract screening', 'systematic literature reviews', 'PRISMA') but omits natural synonyms and file-type triggers a user might say (e.g. 'MEDLINE', 'PubMed', 'inclusion/exclusion criteria', '.csv'), so coverage is partial rather than comprehensive.

3 / 5

Distinctiveness Conflict Risk

The niche (systematic-review abstract screening with PRISMA) is fairly distinct with minimal overlap against generic literature tools; it is not a 5 only because the lack of trigger phrases leaves some ambiguity about exact invocation.

4 / 5

Total

13

/

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: 1 missing

Warning

Total

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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