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auto-research

Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis

Quality

76%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./.claude/skills/auto-research/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%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.

This is a strong orchestration skill: the workflow is clearly phased with explicit checkpoints, error-recovery loops, and copy-paste-ready templates for both agent prompts and the final deliverable. Its weaknesses are repetition of the emerging-tech instructions across five sections and a monolithic single-file structure that inlines two large phase-specific templates. Neither weakness undermines executability, but both cost context-window efficiency.

Suggestions

Consolidate the emerging-tech guidance into one canonical statement (the agent prompt's methodology #6) and reference it from the other sections instead of restating search tactics, output fields, and rationale in Phase 1, the output structure, Recommended Actions, and the Example Decomposition.

Move the agent prompt template and the full output document skeleton into references/ (e.g. references/agent-prompt.md and references/output-template.md) and link them from their respective phases, keeping SKILL.md as a lean overview.

Trim Phase 1's thread descriptions to one line each and move the "Inspired by Karpathy's autoresearch" attribution and detailed sub-bullets into the single reference location for emerging-tech methodology.

DimensionReasoningScore

Conciseness

The body is mostly operational and does not explain concepts Claude already knows, but the emerging-tech guidance is repeated at length in at least five places (Phase 1 thread 7, the agent prompt's methodology #6, the "Emerging Tech & Architectures to Watch" output section, "Tech Bets" in Recommended Actions, and Example Decomposition thread 6), which is padded and could be consolidated. It is above 2 because the rest is tight, and below 4 because the duplication is substantial, not minor.

3 / 5

Actionability

Guidance is fully executable for an instruction-only skill: a copy-paste-ready agent prompt template with placeholders, a complete output document skeleton, concrete agent naming convention ("research-[thread-slug]"), exact save paths ("05-knowledge/research/YYYY-MM-DD-[slug].md"), a worked example decomposition, and fallback steps when web tools are unavailable. It matches the 'copy-paste ready, specific examples cover common cases' anchor.

5 / 5

Workflow Clarity

Four phases are clearly sequenced with timings and explicit validation checkpoints: user course-correction before agents launch (Phase 1), per-thread confidence levels with reasoning, retry-once-with-alternative-terms feedback loops, and documenting gaps rather than fabricating depth. Although spawning 5-7 agents is a batch operation, validation and feedback loops are present, so the cap at 3 does not apply.

5 / 5

Progressive Disclosure

There are no bundle files (references/, scripts/, assets/ are absent) and the body is well-sectioned, but at ~229 lines it far exceeds single-file scope: the ~40-line agent prompt template and ~70-line output document template are phase-specific content inlined in SKILL.md that would be better placed in one-level-deep reference files. This matches the 'some structure, content that should be separate is inline' anchor rather than 4, where most content would be appropriately placed across files.

3 / 5

Total

16

/

20

Passed

Description

66%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.

The description communicates a concrete, distinctive capability pipeline in third person, but it omits any 'when to use' trigger guidance, which both caps completeness and elevates routing ambiguity. Trigger-term coverage is good but misses natural synonyms like "deep dive" and "investigate". Adding an explicit 'Use when...' clause would resolve the description's weakest dimensions.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user asks for deep research, a deep dive, investigation, strategic analysis, or evidence-based analysis of market forces, competitive dynamics, or strategic options."

Include natural trigger synonyms users actually say — "deep dive", "investigate", "market analysis", "competitive analysis" — rather than only "research" and "strategic analysis".

State the key deliverables (scenarios, strategic options, recommended actions, consolidated sources) so the 'what' moves from several actions to comprehensive coverage.

DimensionReasoningScore

Specificity

"decomposes questions into parallel research threads", "spawns multiple agents", and "synthesizes into actionable strategic analysis" name three concrete actions in a clear domain, matching the 'several specific actions with minor gaps' anchor; it is not comprehensive (5) because downstream capabilities like scenario construction, saved research documents, and recommended actions are not stated.

4 / 5

Completeness

The 'what' is clear (decompose → spawn agents → synthesize), but there is no 'Use when...' clause or equivalent explicit trigger guidance in the description, which caps completeness at 3 per the judging guidelines. It is above 2 because the 'what' is specific and multi-part, and below 4 because 'when' is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

Natural user phrases are present — "strategic research", "research", "strategic analysis", "questions" — giving good keyword coverage, but common variations users would actually say such as "deep dive", "investigate", "market analysis", or "competitive analysis" are missing, so it falls just short of the comprehensive-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

"Deep strategic research engine" with a parallel multi-agent decomposition/synthesis pipeline carves a mostly distinct niche with minor overlap risk against generic research or web-search skills; it is not 5 because the broad 'research'/'analysis' vocabulary without 'when' framing could still collide with other research-oriented skills.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository

huytieu/COG-second-brain

Path

.claude/skills/auto-research/SKILL.md

Reviewed

Table of Contents

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