landing-page-intel

Extract competitor and customer intelligence from any company's landing page HTML. Discovers tech stack, analytics tools, ad pixels, customer logos, SEO metadata, CTAs, hidden elements, and more. No API keys required.

Quality

91%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

100%

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

The skill body is concise, immediately actionable with executable commands, and well-organized as a self-contained overview with a real bundled script. It is a strong, token-efficient skill document.

Dimension	Reasoning	Score
Conciseness	The body is lean and table-driven with no explanation of concepts Claude already knows; every section (Quick Start, What It Extracts, CLI Reference, Use Cases, Cost) earns its place.	3 / 3
Actionability	Provides fully executable `python3 skills/.../scrape_landing_page.py` commands with real flags and a CLI reference table with defaults, making the guidance copy-paste ready.	3 / 3
Workflow Clarity	This is a simple single-task skill (run one script) with an unambiguous invocation sequence shown in Quick Start; no destructive or batch operation requires validation checkpoints, so the simple-skill exception applies.	3 / 3
Progressive Disclosure	A single self-contained SKILL.md with well-organized sections and one real bundle script (scripts/scrape_landing_page.py) referenced by path; no nested references, fitting the simple-skill allowance for a 3.	3 / 3
	Total	12 / 12 Passed

Description

82%

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, well-targeted, and rich in natural trigger terms, but it lacks an explicit 'Use when...' clause stating when Claude should invoke the skill. Adding a trigger clause would lift completeness to the top level.

Suggestions

Append an explicit trigger clause such as 'Use when researching a company's website for competitive intel, prospecting before a sales call, or mapping a competitor's tech stack and customers.'

Add common user phrasings ('analyze a website', 'scrape a landing page') to broaden trigger-term coverage.

Consider dropping 'and more' since it is vague filler that adds no actionable capability.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete extraction actions ("tech stack, analytics tools, ad pixels, customer logos, SEO metadata, CTAs, hidden elements") rather than vague language, matching the multi-action anchor.	3 / 3
Completeness	Clearly answers what the skill does, but there is no "Use when..." or equivalent explicit trigger clause, so the 'when' guidance is absent and completeness is capped at 2 per the rubric.	2 / 3
Trigger Term Quality	Includes natural GTM terms a user would say ("landing page", "competitor", "customer intelligence", "tech stack", "ad pixels", "SEO metadata") with good coverage; not merely jargon.	3 / 3
Distinctiveness Conflict Risk	Targets a clear niche (landing-page HTML scraping for GTM intelligence) with distinct triggers unlikely to overlap with unrelated skills.	3 / 3
	Total	11 / 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/capabilities/landing-page-intel/SKILL.md
Commit: 8866b2a

Reviewed: 1 day ago

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