competitor-intel

Competitor intelligence system. Research competitors across web, Reddit, Twitter/X, LinkedIn, and blogs. Build deep competitor profiles, monitor content and positioning changes, track what gets traction, and identify competitive gaps. Covers data collection, content tracking, and strategy analysis. Pure research skill — uses web search, web fetch, and optionally Apify for social scraping. No scripts required.

Quality

75%

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Securityby

Low

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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-structured, actionable research workflow with concrete search strings, fetch targets, and output templates, and no wasted concept explanations. Its main weaknesses are the total absence of progressive disclosure (everything inlined, no references/) and only implicit verification checkpoints.

Suggestions

Move the two full output templates (competitor profile and landscape summary) into references/ files (e.g. references/profile-template.md, references/landscape-template.md) and keep one condensed example inline in SKILL.md.

Add an explicit verification step, e.g. cross-check pricing/positioning claims across at least two sources and flag data older than 6 months in each profile.

Make the Apify section concrete: name the actors or search patterns to use for Reddit, Twitter/X, and LinkedIn scraping, and what to do if a scrape returns nothing.

Dimension	Reasoning	Score
Conciseness	The body is checklist- and template-driven with essentially no explanation of concepts Claude already knows, but the "Three layers" section restates the frontmatter description and lines like "Without Apify, web search covers the basics — just less structured" are trimmable. Efficient with minor over-explanation, matching anchor 4.	4 / 5
Actionability	Gives exact search queries ("[company] funding", "[company] G2 reviews"), exact pages to fetch (/vs/, /alternatives/, /careers, /integrations), and complete output templates — highly actionable for an instruction-only skill. Not 5 because the Apify section says "scrape deeper data" without naming actors or concrete call patterns.	4 / 5
Workflow Clarity	A clear five-phase sequence (Intake → Profile Research → Profile Output → Landscape Summary → Monitoring) with concrete sub-steps per dimension. Not 5 because verification is implicit — no explicit source-triangulation or data-staleness checkpoints — though no destructive or batch operations require feedback loops.	4 / 5
Progressive Disclosure	Section headers are clear, but no reference files exist at all and the two full markdown output templates (~90 lines) are inlined in a ~190-line body where they could live in references/. Matches anchor 3 — content that should be separate is inline — rather than 4, which requires an appropriate reference split.	3 / 5
	Total	15 / 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.

A specific, well-scoped description with concrete named actions and channels, but it omits any explicit "Use when..." trigger guidance, which caps completeness and slightly weakens trigger-term coverage. Distinctiveness within the competitor-research niche is good.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user asks to research competitors, build competitor profiles, run a competitive landscape analysis, or monitor competitor content and positioning."

Include natural synonym phrasings users actually say — "competitive analysis", "market landscape", "rivals", "compare us to [competitor]" — to strengthen trigger-term coverage.

Tighten abstract phrases like "track what gets traction" into concrete actions (e.g., "identify competitors' top-engaged content and your content gaps").

Dimension	Reasoning	Score
Specificity	"Research competitors across web, Reddit, Twitter/X, LinkedIn, and blogs. Build deep competitor profiles, monitor content and positioning changes, track what gets traction, and identify competitive gaps" lists several specific concrete actions across named channels. Falls short of 5 due to minor gaps and mildly abstract phrasing like "track what gets traction".	4 / 5
Completeness	The "what" is clear and detailed (research, profile building, monitoring, gap analysis), but there is no "Use when..." clause or equivalent explicit trigger guidance anywhere in the description, which caps completeness at 3 per the judging guidelines.	3 / 5
Trigger Term Quality	Includes natural phrases users would say ("Research competitors", "competitor profiles", "positioning changes", "competitive gaps") but misses common variations such as "competitive analysis", "market landscape", or "rivals". Good coverage with a few natural terms missing, matching anchor 4.	4 / 5
Distinctiveness Conflict Risk	Clear niche (competitor intelligence) with distinct triggers around competitor research and positioning. Minor overlap risk with generic web-research or market-analysis skills, slightly elevated by the absent when-clause, so anchor 4 fits better than 5.	4 / 5
	Total	15 / 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/competitor-intel/SKILL.md
Commit: cc3e518

Reviewed: 7 days ago

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