industry-scanner

Daily industry intelligence scanner. Scans web, social media, news, blogs, and communities for industry-relevant events, trends, and signals. Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas. Orchestrates existing scraping skills — does not reimplement data collection.

Quality

62%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/competitive-intel/composites/industry-scanner/SKILL.md

Quality

Content

65%

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 with concrete commands and a clear five-phase sequence, but it is long and monolithic, with no validation checkpoints for batch scrapes and no bundle files to offload the output template and strategy catalog. Splitting heavy reference material into files and adding source-verification steps would meaningfully improve it.

Suggestions

Move the full output template and strategy-patterns catalog into reference files (e.g. references/output-template.md, references/strategy-patterns.md) and link them from the body to improve progressive disclosure and conciseness.

Add an explicit validation/verification checkpoint in Phase 3 — e.g. confirm which sources returned data, flag failed scrapes, and abort or warn before consolidating — to satisfy the batch-operation feedback-loop requirement.

Trim redundant or padded passages in the strategy-patterns section, keeping it as genuinely inspirational pointers rather than a near-checklist.

Dimension	Reasoning	Score
Conciseness	It avoids explaining concepts Claude already knows, but at ~360 lines the extensive inline strategy-patterns catalog and full output template could be tightened or moved to references to better respect the token budget.	2 / 3
Actionability	Provides concrete, executable bash commands with real flags and config field names (e.g. '--urls', '--subreddit', '--days <lookback>'), plus a copy-paste-ready markdown output template.	3 / 3
Workflow Clarity	The five phases are clearly sequenced, but the batch scrape operations have no explicit validation or verification checkpoints and no feedback loops for failed sources, which caps workflow clarity at 2.	2 / 3
Progressive Disclosure	Sections are well organized and external skill references are clearly signaled one level deep, but no bundle files exist and the long output template plus strategy catalog are inline content that would be better split into references.	2 / 3
	Total	9 / 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 is specific and action-oriented with a clear orchestration framing, but it lacks an explicit 'Use when…' trigger clause and omits several common user phrasings. Adding trigger guidance and broader natural-language keywords would raise both completeness and trigger-term quality.

Suggestions

Add an explicit 'Use when…' clause naming common user triggers, e.g. 'Use when the user asks for industry scanning, competitive intelligence, competitor monitoring, or GTM opportunity research.'

Broaden trigger terms to include natural phrasings users actually say — 'competitive intelligence', 'market research', 'competitor monitoring', 'industry trends'.

Tighten the broad 'events, trends, and signals' phrasing to sharpen distinctiveness against generic research skills.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Scans web, social media, news, blogs, and communities', 'Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas', and 'Orchestrates existing scraping skills' — rather than vague language.	3 / 3
Completeness	Clearly answers what the skill does but provides no explicit 'Use when…' trigger guidance, which per the guidelines caps completeness at 2.	2 / 3
Trigger Term Quality	Contains relevant terms like 'industry intelligence scanner', 'trends, and signals', and 'GTM opportunity ideas', but misses common variations a user would naturally say such as 'competitive intelligence', 'market research', or 'competitor monitoring'.	2 / 3
Distinctiveness Conflict Risk	The 'Orchestrates existing scraping skills' framing gives a clear niche, but broad terms like 'industry-relevant events, trends, and signals' could still overlap with generic research or monitoring skills.	2 / 3
	Total	9 / 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: gooseworks-ai/goose-skills
Path: skills/competitive-intel/composites/industry-scanner/SKILL.md
Commit: 8866b2a

Reviewed: 1 day ago

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