hypothesis-generation

Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Use when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.

Quality

92%

Does it follow best practices?

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Adds up to 20 points to the overall score

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Securityby

Passed

No findings from the security scan

Quality

Content

85%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable scientific-method skill with a clear sequenced workflow and clean progressive disclosure into verified bundle files. The main weakness is verbosity in the enumerated workflow sections.

Suggestions

Trim repetitive boundary and caution language across the 12 steps into a single consolidated checklist; several steps restate the same non-negotiable constraints.

Convert the longest per-step bullet enumerations (e.g. steps 5, 6, 8, 9) into tighter sub-checklists or push detail into the existing references to reduce token load.

Where a step only restates rules already covered in 'Non-negotiable boundaries', cross-reference that section instead of repeating the prose.

Dimension	Reasoning	Score
Conciseness	Dense and mostly free of concept primers, but the 12-step workflow with repeated enumerative bullet lists and recurring boundary/caution language could be tightened; closest to 'mostly efficient but some unnecessary or tightenable' rather than the lean level-3 anchor.	2 / 3
Actionability	Concrete CLI invocations with arguments (e.g. 'python3 scripts/check_operationalization.py local-operationalization.json'), named asset paths, exit-code semantics, and a task-asset-command table give copy-paste-ready executable guidance.	3 / 3
Workflow Clarity	A clearly numbered 12-step sequence with per-step record-checklists and validation checkpoints (scope/safety gate, exit-code feedback loops, before/after-outcome HARKing controls) matches the clear-sequence-with-explicit-validation anchor.	3 / 3
Progressive Disclosure	SKILL.md serves as a well-signaled overview with one-level-deep references to references/.md and assets/; every referenced path exists and is surfaced inline plus in a References section.	3 / 3
	Total	11 / 12 Passed

Description

100%

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 precise, third-person description that clearly states concrete capabilities and an explicit Use-when trigger, with a distinct scientific niche. It is on the longer side but every clause carries load.

Dimension	Reasoning	Score
Specificity	Enumerates concrete actions—questions, hypotheses, rival explanations, causal/associational claims, predictions, measurements, and preregistration-ready plans—matching the multi-action anchor rather than the partial level-2 example.	3 / 3
Completeness	Explicit 'Use when turning observations or preliminary findings into transparent, testable research plans...' answers both what it does and when to invoke it, satisfying the level-3 what-and-when anchor.	3 / 3
Trigger Term Quality	Natural triggers like 'observations,' 'preliminary findings,' 'research plans,' and 'hypotheses' cover what a user would say; academic but recognizable, above the level-2 'missing common variations' anchor.	3 / 3
Distinctiveness Conflict Risk	Scientific hypothesis generation is a narrow niche with distinct, domain-specific triggers unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/hypothesis-generation/SKILL.md
Commit: 757b63b

Reviewed: about 11 hours ago

Table of Contents

Discovery Implementation Validation

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