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aris-research-wiki

Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.

62

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/aris-research-wiki/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 well-organized, largely actionable instruction-only skill with concrete schemas, budgets, and per-subcommand workflows. Its weaknesses are moderate length with some repetition (triple Karpathy attribution) and zero progressive disclosure — the page schemas and cross-skill hook specs would live better in reference files.

Suggestions

Move the detailed page schemas (paper, and the implied idea/experiment/claim schemas) into references/ files (e.g. references/page-schemas.md) and keep SKILL.md as an overview with one-level-deep, clearly signaled links — this directly addresses the lowest-scoring dimension, progressive_disclosure.

Extract the three integration-hook pseudocode blocks into a references/integration-hooks.md so the main body stays a concise subcommand reference, and replace the duplicated Karpathy attribution (Overview, inspiration line, and Acknowledgements) with a single mention to tighten conciseness.

Add an explicit verification checkpoint to the ingest and update workflows (e.g., confirm edges.jsonl is valid JSONL and the rebuilt query_pack is under 8000 chars before finishing) to lift workflow_clarity from good to exemplary.

DimensionReasoningScore

Conciseness

The body is dense with tables, schemas, and budget specs and assumes Claude's competence throughout, but carries minor redundancy: the Karpathy attribution with the same gist link/quote appears in the Overview, the inspiration line, and again in Acknowledgements. It fits anchor 4 (efficient with minor trimmable instances) rather than 5, where every token earns its place.

4 / 5

Actionability

Concrete guidance is consistent: an exact directory layout, a full copy-paste paper-page schema, per-subcommand numbered steps, a char-budget table with pruning rules, explicit update command examples, and six named lint checks. The integration-hook blocks are pseudocode rather than executable commands, keeping it below the fully copy-paste-ready anchor 5.

4 / 5

Workflow Clarity

Each subcommand has a clearly numbered sequence (ingest has 10 steps including a dedup check), query_pack generation has a hard budget with explicit pruning priority, and the lint subcommand is itself a validation pass producing a report. Minor validation gaps (e.g., no explicit verify step after appending edges or regenerating pages) hold it at anchor 4 rather than 5.

4 / 5

Progressive Disclosure

No bundle files (references/, scripts/, assets/) exist, so everything is inline in a ~290-line body. Sections are well-headed, but content that belongs in separate reference files — the full paper-page schema and the three pseudocode integration hooks for other skills — is inlined with no external references to signal navigation. This matches anchor 3 (structure present, but content that should be separate is inline) rather than 4, where most content is appropriately placed across files.

3 / 5

Total

15

/

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.

A strong description with a clear capability statement and an explicit, natural (and bilingual) trigger clause. The main gap is specificity: it describes what the knowledge base holds rather than the concrete operations it performs (ingest, query, update, lint, stats).

DimensionReasoningScore

Specificity

"Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships" names the domain and entities, and "build/query a persistent field map" gives a concrete action, but the main verbs stay generic and the actual operations (ingest, lint, stats, update) never appear. It matches anchor 3 (domain plus 1-2 concrete actions) rather than 4, which requires several specific listed actions with only minor gaps.

3 / 5

Completeness

It clearly answers "what" (a persistent knowledge base accumulating papers, ideas, experiments, claims, and relationships across the research lifecycle) and "when" via the explicit "Use when user says ... or wants to build/query a persistent field map" clause with concrete trigger phrases. This matches the anchor-5 example pattern of capability statement plus explicit 'Use when' with named triggers.

5 / 5

Trigger Term Quality

Trigger phrases "知识库", "research wiki", "add paper", "wiki query", "查知识库" are natural things a user would say, with good bilingual coverage. Common synonyms like "literature", "ingest paper", or "knowledge graph" are missing, so it falls just short of anchor 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

The persistent-research-wiki/field-map niche with its distinct trigger terms is clearly distinguishable, with only minor overlap risk against general literature-survey or note-taking skills. Not anchor 5 because phrases like "add paper" could plausibly fire in a general citation-management context.

4 / 5

Total

16

/

20

Passed

Validation

87%

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

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
OpenLAIR/dr-claw
Reviewed

Table of Contents

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