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

68%

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Securityby

Low

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

Quality

Content

65%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-structured, actionable orchestrator skill with concrete commands and a clear phased workflow. It is held back by the absence of validation/feedback loops for batch collection and by monolithic inline content with no progressive-disclosure bundle files.

Suggestions

Add an explicit validation/feedback step (e.g., verify each source returned valid JSON, retry or log failures, confirm the final briefing is non-empty before declaring success) to lift workflow clarity above the batch-operation cap.

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

Provide a concrete command or snippet for the LinkedIn (2E) source instead of only delegating verbally, to close the actionability gap.

Dimension	Reasoning	Score
Conciseness	The body is long (~360 lines) but mostly earns its tokens with actionable CLI commands, tables, and templates rather than explaining basics Claude already knows; a few sections (strategy patterns, full output template) could be trimmed or externalized.	4 / 5
Actionability	Mostly executable: concrete bash commands with real flags for 8 of 9 sources and a precise output template. Minor gaps — LinkedIn (2E) delegates without a concrete command, and 2A gives example queries rather than exact commands.	4 / 5
Workflow Clarity	A clear 5-phase sequence exists with dedup/categorize/filter quality control, but there is no explicit validation checkpoint or error-recovery feedback loop for this batch (multi-source) operation; per the rubric, missing validation in batch workflows caps this at 3.	3 / 5
Progressive Disclosure	No bundle files exist (references/, scripts/, assets/ are empty), and large blocks (output template, strategy patterns, all phases) are inlined in a single SKILL.md; references to other skills are clearly signaled but the skill itself is monolithic with only section-header structure.	3 / 5
	Total	14 / 20 Passed

Description

71%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 specific, capability-rich description with a useful boundary statement distinguishing it from sub-skills. Its main weakness is the absence of an explicit "Use when..." trigger clause, which caps completeness.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user wants a recurring industry scan, competitive intelligence briefing, or GTM opportunity mining for a client."

Include natural synonyms users might say ("market research", "competitive intel", "monitor competitors") to broaden trigger coverage.

Keep the concise third-person voice; avoid expanding into verbosity.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions across a clear domain: "Scans web, social media, news, blogs, and communities", "Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas", and "Orchestrates existing scraping skills" — comprehensive coverage of what it does.	5 / 5
Completeness	The "what" is clearly and comprehensively answered, but there is no "when" / "Use when..." clause; per the rubric, a missing explicit trigger clause caps completeness at 3.	3 / 5
Trigger Term Quality	Good natural-term coverage ("industry intelligence scanner", "web, social media, news, blogs", "GTM opportunity ideas") but lacks common synonyms a user might say (e.g., "market research", "competitive intel", "monitor") and omits a "Use when..." trigger phrase.	4 / 5
Distinctiveness Conflict Risk	The explicit boundary "Orchestrates existing scraping skills — does not reimplement data collection" carves a clear niche distinct from individual scrapers; minor overlap risk with generic research/monitoring skills.	4 / 5
	Total	16 / 20 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: 2523432

Reviewed: 7 days ago

Table of Contents

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