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tech-search

Self-contained deep tech research. WebSearch + WebFetch + Haiku workers. Pipeline: Query > Decompose > Parallel Search (Haiku) > Evaluate > Synthesize > Document. Zero external dependencies. MCPs optional. Salva em docs/research/{YYYY-MM-DD}-{slug}/.

60

Quality

68%

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SecuritybySnyk

High

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tessl review fix ./.claude/skills/tech-search/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

The body is highly actionable and the 6-phase workflow is clearly sequenced with validation checkpoints and feedback loops. Its main weaknesses are redundant constraint repetition across sections and a monolithic single-file structure that includes a dangling reference to a missing file.

Suggestions

De-duplicate the repeated constraints ('NEVER implement code', output structure, pipeline) into a single canonical section and reference it, cutting significant tokens to push conciseness toward 3.

Create the referenced prompts/page-extract.md or remove the reference so progressive-disclosure links resolve to real files.

Extract the worker prompt template and technology-detection lists into a reference file to reduce the monolithic body and improve navigation.

DimensionReasoningScore

Conciseness

The body is mostly operational and concrete, but the same constraints ('NEVER implement code', the output structure, the pipeline) are repeated 3-5 times across the CRITICAL, veto, constraints, security, and scope_boundaries sections, adding tokens that could be tightened; this falls short of the lean level-3 anchor without being padded with Claude-obvious concept explanations (level 1).

2 / 3

Actionability

Provides copy-paste-ready Task() calls with subagent_type and model, a full worker prompt template, JSON output schemas, numeric stopping thresholds (coverage_score >= 80, wave >= 2), and exact file paths, matching the fully-executable level-3 anchor.

3 / 3

Workflow Clarity

Six phases are clearly sequenced with an explicit coverage-evaluation checkpoint, hard/soft stopping rules, and feedback loops (failed workers re-run in main context; CONTINUE returns to Phase 3 with new queries), matching the level-3 anchor with validation steps and error-recovery loops.

3 / 3

Progressive Disclosure

The body is well-sectioned but monolithic (~430 lines) with no bundle files present, and inline content (the worker prompt template, technology-detection lists) could be split out; additionally the 'prompts/page-extract.md' reference points to a non-existent file, which prevents a level-3 score but is organized enough to clear level 1.

2 / 3

Total

10

/

12

Passed

Description

60%

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 concretely names tools and a phase pipeline, but leans on implementation jargon over natural trigger terms and omits any explicit 'when to use' guidance. It occupies a distinguishable niche yet could still overlap with general research skills.

Suggestions

Add an explicit trigger clause such as 'Use when the user asks to research, investigate, or compare technical topics' to raise completeness from 2 to 3.

Swap implementation jargon (WebFetch/Haiku/MCPs) for natural user language ('deep tech research', 'compare technologies', 'state of the art') so trigger terms match what users actually say.

Translate or drop the stray Portuguese ('Salva em docs/research/...') so the description reads consistently and the output-path detail remains user-comprehensible.

DimensionReasoningScore

Specificity

Lists concrete actions across a named pipeline ('Decompose > Parallel Search (Haiku) > Evaluate > Synthesize > Document') and cites specific tools (WebSearch, WebFetch, Haiku), matching the multiple-specific-actions anchor.

3 / 3

Completeness

Clearly states what the skill does but provides no 'Use when...' or equivalent explicit trigger guidance, so 'when' is only implied; the rubric caps completeness at 2 when such a clause is missing, ruling out level 3.

2 / 3

Trigger Term Quality

Contains one natural term ('deep tech research') but is dominated by implementation jargon ('WebSearch + WebFetch + Haiku workers', 'MCPs optional') rather than terms users would say; common variations like 'investigate' or 'compare' are missing, so it is not the jargon-only level 1 but falls short of level 3.

2 / 3

Distinctiveness Conflict Risk

'Self-contained deep tech research' carves a niche but it is broad and could overlap with other research skills, and there are no distinct user-facing triggers to separate it; not generic enough for level 1, lacking the distinct triggers needed for level 3.

2 / 3

Total

9

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
SynkraAI/aiox-core
Reviewed

Table of Contents

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