creative-thinking-for-research

Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.

Quality

73%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/vendor-ai-research/creative-thinking-for-research/SKILL.md

Quality

Content

63%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.

A thorough, well-structured instruction skill with concrete per-framework workflows and validation checklists. The main weaknesses are redundant explanation of well-known cognitive-science concepts and a monolithic single-file structure that could benefit from reference splitting.

Suggestions

Trim the definitional 'Why it works' sentences for frameworks Claude already knows (Koestler, Gentner, Boden, TRIZ, Polya, Kauffman) and keep only the CS-application value-add to improve conciseness.

Split the larger example tables and per-framework deep-dives into one-level-deep reference files (e.g., references/frameworks.md, references/examples.md) linked from a leaner SKILL.md overview to improve progressive disclosure.

Add explicit 'only proceed when the Self-Check passes' gating language to the combined protocol so validation checkpoints are enforced rather than optional.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with actionable workflows and tables, but it re-explains cognitive-science concepts Claude already knows (Koestler's bisociation, Gentner's structure-mapping, Boden's framework, TRIZ, Polya) via 'Why it works' and definitional sentences that could be trimmed.	3 / 5
Actionability	Each framework ships a numbered, concrete workflow plus CS-specific example tables, cross-product matrices, and self-checks — actionable guidance with only minor gaps (e.g., the combined protocol steps lack measurable completion criteria beyond time budgets).	4 / 5
Workflow Clarity	Multi-step workflows are clearly sequenced with explicit validation checkpoints (Self-Check checkboxes, Validation Checklists, Quality Tests) and a phased protocol with time budgets; a few frameworks omit an explicit 'only proceed when check passes' gate.	4 / 5
Progressive Disclosure	Well-organized into eight labeled framework sections with a combined-protocol overview, but the entire ~365-line body is inlined in SKILL.md with no bundle files and no one-level-deep references that the longer reference material (example tables, framework deep-dives) could split into.	3 / 5
	Total	14 / 20 Passed

Description

83%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 strong, third-person description that cleanly states both capability and trigger conditions with concrete strategy names. Minor gains are possible by adding more colloquial trigger synonyms and sharpening the action verbs.

Dimension	Reasoning	Score
Specificity	Lists several concrete strategies ('combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies') rather than vague language, though the named items are frameworks rather than discrete operations like 'extract' or 'fill'.	4 / 5
Completeness	Explicitly answers both 'what' ('Applies cognitive science frameworks for creative thinking to CS and AI research ideation') and 'when' ('Use when seeking genuinely novel research directions') with concrete trigger phrasing.	5 / 5
Trigger Term Quality	Good natural-phrase coverage ('creative thinking', 'novel research directions', 'research ideation') that a user might actually say, though some terms like 'combinatorial creativity' lean technical and a few common synonyms are missing.	4 / 5
Distinctiveness Conflict Risk	The CS/AI research-ideation niche with cognitive-science framing is mostly distinct, with minor overlap risk against a general 'brainstorming-research-ideas' skill (which the body itself flags).	4 / 5
	Total	17 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: OpenRaiser/NanoResearch
Path: skills/vendor-ai-research/creative-thinking-for-research/SKILL.md
Commit: 9d3b440

Reviewed: ~21 hours ago

Table of Contents

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