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lncrna-regulatory-network-construction-analysis

Use this bioinformatics data analysis skill to construct a database-driven lncRNA-mRNA regulatory network from target lncRNA and/or gene lists by projecting shared miRNA evidence from local ceRNA reference tables. It does not infer networks from expression matrices.

68

Quality

83%

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

88%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 a well-organized CLI skill overview with executable examples, an explicit execution sequence with validation, and clean one-level-deep references. The main gaps are minor redundancy of the scope boundary across sections and a broken reference to a non-existent tests/data/ directory.

Suggestions

Create the referenced tests/data/ directory (or remove the tests/data/ row from the 'When to Read External Files' table) so every referenced bundle path resolves.

Consolidate the out-of-scope guidance into a single section to remove the repetition across 'When to Use', 'Out-of-Scope Response Pattern', and 'Scope Limits'.

DimensionReasoningScore

Conciseness

The body is largely lean and token-efficient (tables for args/outputs/errors, no explanations of bioinformatics concepts), but the out-of-scope boundary is restated across 'When to Use', 'Out-of-Scope Response Pattern', and 'Scope Limits', which could be trimmed.

4 / 5

Actionability

Fully executable, copy-paste-ready Rscript commands with complete argument lists cover the common cases (gene-driven, lncRNA-driven, focused bipartite, visualization reuse, and testing).

5 / 5

Workflow Clarity

A clear 9-step Execution Model with an explicit validation checkpoint ('Before --mode visualize, confirm that ... lncrna_network.rda already exists') plus an error-code → meaning → solution table and an Agent Response Contract that define a feedback loop for reruns.

5 / 5

Progressive Disclosure

Good structure with a 'When to Read External Files' table signaling one-level-deep references (algorithm.md, troubleshooting.md, cli-guide.md, scripts/main.R), all verified present, but 'tests/data/' is referenced as a demo-input source yet the tests/ directory does not exist in the bundle.

4 / 5

Total

18

/

20

Passed

Description

78%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 specific, domain-rich, and well-bounded, clearly communicating a distinct database-driven workflow and its exclusion of expression-based inference. Its main weakness is the absence of an explicit 'Use when the user mentions ...' trigger clause that would lift completeness and trigger-term quality to the top anchor.

Suggestions

Add an explicit trigger clause such as 'Use when the user asks to build an lncRNA-mRNA ceRNA regulatory network from a target gene or lncRNA list, or mentions shared-miRNA/ceRNA projection.'

Surface a few more natural synonyms users might say (e.g. 'ceRNA network', 'miRNA sponge', 'competing endogenous RNA') to broaden trigger coverage.

DimensionReasoningScore

Specificity

Names the domain and concrete actions ('construct a database-driven lncRNA-mRNA regulatory network', 'projecting shared miRNA evidence from local ceRNA reference tables') with a clear negative boundary, though it is essentially one composite action rather than several distinct ones.

4 / 5

Completeness

Clear 'what' (construct the network via shared-miRNA projection from local tables) and an actionable 'when' via 'Use this ... skill to construct ... from target lncRNA and/or gene lists' plus the expression-matrix exclusion, but the 'when' lacks an explicit 'Use when the user mentions ...' trigger clause.

4 / 5

Trigger Term Quality

Rich natural domain keywords a user would actually say ('lncRNA', 'mRNA', 'regulatory network', 'miRNA', 'ceRNA', 'gene lists') with synonyms, but no file-extension or broader phrase variants, leaving a few natural terms uncovered.

4 / 5

Distinctiveness Conflict Risk

A clearly defined niche (database-driven ceRNA projection) with distinct triggers and an explicit negative boundary ('does not infer networks from expression matrices'), giving minimal conflict risk with other skills.

5 / 5

Total

17

/

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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