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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.

46

Quality

48%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./scientific-skills/Evidence Insight/smart-journal-monitor/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

60%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 content provides real executable commands, a clear sequenced workflow with a verification checkpoint, and well-signaled one-level-deep references to genuine bundle files. Its main weakness is verbosity from generic boilerplate and redundant restatements of the description.

Suggestions

Remove the three near-duplicate restatements of the description in "When to Use" and "Key Features"; keep one concrete scoping statement.

Delete or move generic process boilerplate (Output Requirements, Response Template, Input Validation, Implementation Details) that reiterates concepts Claude already knows, keeping only skill-specific guidance.

Document the actual CLI flags (--demo, --articles file, --threshold) with a copy-paste example instead of only showing --help.

DimensionReasoningScore

Conciseness

The body is noticeably verbose: "When to Use" repeats the description verbatim three times, and sections like Implementation Details, Output Requirements, Response Template, Error Handling, and Input Validation restate generic process concepts Claude already knows rather than skill-specific value.

2 / 5

Actionability

Concrete executable commands are present ("python -m py_compile scripts/main.py", "python scripts/main.py --help") plus a parameters table and an input/output example, but the actual CLI flags (--demo, --articles, --threshold) are not surfaced in the body, leaving a minor gap.

4 / 5

Workflow Clarity

A sequenced 5-step Workflow and an Example run plan are present with a verification checkpoint (py_compile before deeper execution) and an explicit fallback path for failures; the missing validate→fix→retry loop keeps it just below a 5.

4 / 5

Progressive Disclosure

Structure is good with clearly signaled one-level-deep references (references/audit-reference.md and scripts/main.py both exist and are linked), but the SKILL.md still inlines substantial generic boilerplate that a leaner overview would offload.

4 / 5

Total

14

/

20

Passed

Description

37%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 names a domain but relies on abstract workflow-quality language instead of concrete actions or natural user trigger phrases. It is distinguishable but generic enough to risk overlap with similar insight/analysis skills.

Suggestions

Replace abstract qualities with concrete actions, e.g. "Monitors top journals via RSS and flags high-impact breakthrough articles with relevance scores and one-sentence takeaways."

Add concrete natural triggers, e.g. "Use when the user wants a research digest, to stay current with a field, or to find high-impact papers from Nature/Science/Cell/NEJM/Lancet."

Lead with the distinctive capability (RSS-based journal monitoring with breakthrough detection) so it does not read as a generic evidence-insight skill.

DimensionReasoningScore

Specificity

It names the domain ("smart journal monitor", "evidence insight workflows") but lists no concrete capabilities — "structured execution, explicit assumptions, and clear output boundaries" are abstract workflow qualities, not actions like ranking articles or generating a digest.

2 / 5

Completeness

A "Use ... for ..." clause gives explicit trigger form, but the "what" merely restates the skill name and the "when" is abstract workflow-quality language rather than concrete triggers, so it sits at the cap with a weak, non-concrete trigger.

3 / 5

Trigger Term Quality

Only one or two generic keywords ("journal", "evidence") appear; the natural phrases a user would say ("research digest", "stay current", "high-impact papers", "find papers") and synonyms/extensions are absent.

2 / 5

Distinctiveness Conflict Risk

The journal/evidence niche is somewhat distinctive, but the dominant language ("structured execution, explicit assumptions, clear output boundaries") is generic and could plausibly fire for other analytical or "insight" skills.

3 / 5

Total

10

/

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.

Validation15 / 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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