nanoresearch-ideation

Search academic literature and generate research hypotheses

Quality

61%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/nanoresearch-ideation/SKILL.md

Quality

Content

72%

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

The content is concise and well-organized for a simple skill, scoring well on token efficiency and structure. Its weakness is actionability and workflow robustness: it describes a process rather than giving executable examples, ranking heuristics, or validation checkpoints.

Suggestions

Add a concrete example of generating search queries from a sample topic, and an example tool invocation with expected arguments and output shape.

Specify how papers are deduplicated and ranked for relevance (e.g., citation count, recency, semantic similarity) so the ranking step is reproducible.

Add a validation/checkpoint step after the search and ranking phase (e.g., confirm enough relevant papers were found before proceeding to gap analysis), since this is a batch operation.

Dimension	Reasoning	Score
Conciseness	The body is lean and sectioned (Purpose, Tools Required, Input, Process, Output) with no padding or explanation of concepts Claude already knows, matching the score-3 anchor of efficient content where every token earns its place.	3 / 3
Actionability	It names concrete tools (search_arxiv, search_semantic_scholar) and a numbered process with quantities (5-8 queries, 2-4 hypotheses) but provides no executable examples, query templates, ranking criteria, or output schema details, matching the score-2 anchor of concrete-but-incomplete guidance.	2 / 3
Workflow Clarity	The 6-step process is clearly sequenced, but there are no validation or feedback checkpoints for what is effectively a batch search/rank operation, which per the guidelines caps workflow_clarity at 2.	2 / 3
Progressive Disclosure	The skill is under 50 lines, single-purpose, and organized into clear labeled sections with no need for external references, satisfying the simple-skills scoring note that allows a 3 without separate files.	3 / 3
	Total	10 / 12 Passed

Description

50%

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 concise and names concrete actions but is uniformly mid-tier: it lacks explicit "Use when" trigger guidance, common natural keyword variations, and a clear distinguishing niche. It reads as a serviceable but unoptimized description.

Suggestions

Add an explicit "Use when..." trigger clause (e.g., "Use when the user wants a literature review, gap analysis, or novel research hypotheses on a topic").

Include natural terms users would actually say, such as "papers", "arXiv", "Semantic Scholar", "literature review", or "research ideas".

Mention the gap-analysis step in the description so the stated capability matches the body's process.

Dimension	Reasoning	Score
Specificity	Names two concrete actions ("Search academic literature" and "generate research hypotheses") but omits gap analysis mentioned in the body, so it is not comprehensive — matches the score-2 anchor of naming a domain and some actions.	2 / 3
Completeness	It states what the skill does but provides no "Use when..." clause or explicit trigger guidance, which per the judging guidelines caps completeness at 2.	2 / 3
Trigger Term Quality	Includes relevant phrases like "academic literature" and "research hypotheses" but lacks common variations a user would naturally say (papers, arXiv, Semantic Scholar, literature review), matching the score-2 anchor of some keywords but missing common variations.	2 / 3
Distinctiveness Conflict Risk	The literature-search niche is somewhat specific but could still overlap with general search or research skills, matching the score-2 anchor; it is not generic enough for a 1 but lacks distinct triggers for a 3.	2 / 3
	Total	8 / 12 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/nanoresearch-ideation/SKILL.md
Commit: 7144364

Reviewed: about 14 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.