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smart-journal-monitor

Use smart journal monitor for evidence insight workflows that need structured execution, explicit assumptions, and clear output boundaries.

39

Quality

49%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Evidence Insight/smart-journal-monitor/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 wraps a small amount of genuinely useful material (Parameters table, Returns, Example, audit commands) in a large shell of template boilerplate. It reads as auto-generated filler with circular self-references and broken section pointers rather than skill-specific guidance.

Suggestions

Delete the boilerplate sections that add no task-specific information (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, and the 'See ## X above for related details' placeholders).

Show a complete, copy-paste run command with real arguments, e.g. 'python scripts/main.py --keywords "immunotherapy,checkpoint inhibitor" --frequency daily', instead of the placeholder 'Run python scripts/main.py with the validated inputs'.

Move the checklists and fallback boundaries that duplicate references/audit-reference.md into that file and keep SKILL.md as a concise overview that links to it, eliminating the duplicated content and the broken forward references.

DimensionReasoningScore

Conciseness

The body is heavily padded with boilerplate: 'Scope-focused workflow aligned to: Use smart journal monitor for...' circularly restates the description, and empty meta-sections ('See `## Prerequisites` above for related details', Risk Assessment, Lifecycle Status, Security Checklist) add no task-specific guidance. Roughly half the ~190 lines are template filler.

2 / 5

Actionability

Concrete executable commands exist ('python -m py_compile scripts/main.py', 'python scripts/main.py --help') and the Parameters table is specific, but there is no actual run invocation — 'Run `python scripts/main.py` with the validated inputs' never shows how keywords, journals, or alert_frequency are passed. The cd path with a date-stamped directory ('20260318/scientific-skills/...') is also not a reliably valid path.

3 / 5

Workflow Clarity

The 5-step Workflow has a scope-validation checkpoint and an explicit fallback, and the Quick Check provides a compile verification, but the steps are generic template language ('Use the packaged script path or the documented reasoning path') with no task-specific sequencing or output-validation checkpoint before delivering results.

3 / 5

Progressive Disclosure

references/audit-reference.md is real, one level deep, and clearly signaled in the References section, but its content (audit commands, fallback boundary) duplicates body sections verbatim. The body also inlines bulk material (Security Checklist, Risk Assessment, Evaluation Criteria) that belongs in references, and contains broken forward references ('See `## Prerequisites` above' appears before that section).

3 / 5

Total

11

/

20

Passed

Description

33%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 template-generated boilerplate that names the skill but says nothing concrete about its capabilities (personalized research digest from top journals via RSS+AI). Both the what and the trigger terms are abstract, giving it high overlap risk with similarly-templated skills.

Suggestions

State the concrete capability in the first clause, e.g. 'Generate a personalized research digest from top journals (Nature, Science, NEJM...) by scoring new RSS articles against user keywords'.

Replace abstract trigger language with natural user phrases: 'Use when the user wants a journal digest, research paper alerts, or to stay current with new publications in their field'.

Add distinguishing terms (RSS, journal monitoring, research digest, impact scoring) so the skill does not collide with other 'evidence insight' skills that share the same boilerplate.

DimensionReasoningScore

Specificity

The description names the domain ('smart journal monitor', 'evidence insight workflows') but contains no concrete actions — 'structured execution, explicit assumptions, and clear output boundaries' are pure abstractions. It never states what the skill actually does (personalized research digest from top journals).

2 / 5

Completeness

A when-style trigger clause is present ('Use smart journal monitor for evidence insight workflows that need...'), but the 'what' is only weakly implied by the skill name — the actual capability is never stated. Not a 4 because the 'what' is circular rather than concrete.

3 / 5

Trigger Term Quality

No natural user phrases are present; a user would say 'journal digest', 'research papers', 'RSS feed', or 'stay current with literature', not 'evidence insight workflows that need structured execution'. Only the domain name 'journal monitor' offers a weak keyword.

2 / 5

Distinctiveness Conflict Risk

'Evidence insight workflows that need structured execution, explicit assumptions, and clear output boundaries' is template boilerplate that would equally match any packaged evidence-insight skill. Nothing journal-, RSS-, or digest-specific distinguishes it from siblings.

2 / 5

Total

9

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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