cross-disciplinary-bridge-finder

Use when identifying collaboration opportunities across fields, finding experts in complementary disciplines, translating methodologies between scientific domains, or building interdisciplinary research teams. Identifies synergies between scientific disciplines, matches researchers with complementary expertise, and facilitates cross-domain collaborations. Supports interdisciplinary grant applications and innovative research team formation.

Quality

60%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Evidence Insight/cross-disciplinary-bridge-finder/SKILL.md

Quality

Content

31%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 structurally sectioned but severely undermined by verbatim description duplication, generic boilerplate, and code/CLI/reference examples that do not match the actual bundled `scripts/main.py` or `references/`. It reads as templated padding rather than skill-specific executable guidance.

Suggestions

Replace the Quick Start and Command Line Usage examples with the real API: `scripts/main.py` with `--source`, `--target`, `--mode {bridge,complete-graph,hypothesis,landscape}`, `--output {json,markdown}`, and reference the actual classes (BridgeAnalyzer, KnowledgeGraph) instead of the non-existent CollaborationFinder.

Remove the verbatim re-pastes of the description from "When to Use" and "Key Features", and trim the generic Output Requirements / Error Handling / Input Validation / Response Template boilerplate to only skill-specific points.

Fix the References section: delete the duplicated block and remove the non-existent `guide.md`, `examples/`, and `api-docs/` entries, keeping only the real `references/audit-reference.md` (or create the files if they are intended to exist).

Dimension	Reasoning	Score
Conciseness	The frontmatter description is pasted verbatim into both "When to Use" and "Key Features", and the body carries large generic boilerplate blocks (Output Requirements, Error Handling, Input Validation, Response Template, Implementation Details) that restate process guidance Claude already knows, making it noticeably verbose with several padded sections.	2 / 5
Actionability	The Quick Start imports `from scripts.interdisciplinary import CollaborationFinder` and the CLI example uses `--my-field/--find-collaborators`, but the actual bundle is `scripts/main.py` exposing `BridgeAnalyzer`/`KnowledgeGraph` with flags `--source/--target/--mode/--output`, so the headline code and command examples are non-executable fabrications rather than copy-paste-ready guidance.	2 / 5
Workflow Clarity	A sequenced 5-step Workflow and an example run plan exist with a scope-validation gate and a documented fallback path, plus a Quick Check (`py_compile`), but the steps are generic process boilerplate unrelated to the actual bridge-finding analysis and lack checkpoints tied to the script's real output validation.	3 / 5
Progressive Disclosure	The body claims `references/guide.md`, `references/examples/`, and `references/api-docs/` which do not exist (only `references/audit-reference.md` is real), and the References section is duplicated (lines 174-178 and 206-208), so navigation is misleading despite the presence of section headers.	2 / 5
	Total	9 / 20 Passed

Description

88%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.

A well-formed description with an explicit 'Use when' trigger clause, third-person voice, and a comprehensive set of concrete cross-disciplinary collaboration actions. It is slightly repetitive and could add a few common synonyms, but clearly communicates both purpose and triggering contexts.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — "identifying collaboration opportunities", "finding experts in complementary disciplines", "translating methodologies", "building interdisciplinary research teams", "identifies synergies", "matches researchers", "facilitates cross-domain collaborations", "supports ... grant applications" — giving comprehensive coverage with no real gaps.	5 / 5
Completeness	Explicitly answers both halves: "Use when ..." gives concrete triggers and "Identifies synergies ... matches researchers ... facilitates cross-domain collaborations" states what it does, matching the anchor for clearly answering both what and when.	5 / 5
Trigger Term Quality	Strong natural trigger phrases ("collaboration opportunities across fields", "experts in complementary disciplines", "interdisciplinary research teams", "interdisciplinary grant applications"), but missing common synonyms a user might say such as "co-authorship", "research partners", or "team building".	4 / 5
Distinctiveness Conflict Risk	The cross-disciplinary / cross-domain framing carves a fairly distinct niche, but "collaboration" and "research teams" are broad enough to risk minor overlap with general research-networking or grant-writing skills, so it is mostly distinct rather than minimal-conflict.	4 / 5
	Total	18 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 3 missing	Warning

	Total	14 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Evidence Insight/cross-disciplinary-bridge-finder/SKILL.md
Commit: 63c61d3

Reviewed: 4 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.