ai-seo

When the user wants to build programmatic SEO with AI, create competitor alternative pages, optimize for AI Overviews, or scale content production. Also use when the user mentions 'SEO,' 'programmatic SEO,' 'AI content,' 'competitor alternative pages,' 'AI Overviews,' 'search optimization,' 'DataForSEO,' 'content at scale,' 'keyword strategy,' or 'organic traffic.' This skill covers AI-powered SEO strategy from keyword research through programmatic page generation. Do NOT use for technical implementation, code review, or software architecture.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

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 with strong workflow sequencing and validation feedback loops for a batch/programmatic-operation skill, but it is verbose and padded with time-sensitive pricing/stats and concept framing Claude already knows. Its weakest point is progressive disclosure: a single monolithic file with no bundle references to offload the dense tool/template material.

Suggestions

Move the full tool comparison tables, pricing, and template library into reference files (e.g., references/tool-stack.md, references/page-templates.md) and keep SKILL.md as a concise overview with clearly signaled one-level-deep links to improve progressive_disclosure.

Trim time-sensitive 2025 pricing and platform user-count stats, or relocate them to an 'old patterns' / versioned reference section, to reduce verbosity and avoid stale-data risk (conciseness).

Cut conceptual framing Claude already knows (e.g., why BOFU converts higher, what AI Overviews are) and keep only the decision matrices, thresholds, and templates that drive action.

Dimension	Reasoning	Score
Conciseness	The ~465-line body is padded with tool pricing tables ('Pricing (2025)', '$99-219/mo'), platform scale figures ('800M+ weekly users'), ASCII diagrams, and conversion-rate lore that Claude largely already knows; time-sensitive 2025/2026 data appears without a deprecated/old-patterns section, so it is mostly useful but could be tightened rather than fully lean.	2 / 3
Actionability	Provides concrete executable guidance — bash MCP setup commands, decision matrices, KD/volume thresholds, content brief template, P0–P4 prioritization table, and tool-stack-by-budget — that is directly usable despite template placeholders; as an instruction-heavy skill the specific, actionable guidance earns the top anchor rather than the pseudocode level.	3 / 3
Workflow Clarity	Multi-step workflows (Agent workflow pattern, AirOps workflow, Monthly Iteration Cycle) are clearly sequenced with explicit validation checkpoints (uniqueness > 70%, GSC index monitoring, manual review sample) and feedback loops for batch operations (detect not-cited/unindexed -> restructure/resubmit), plus checklists — matching the clear-sequence-with-validation anchor.	3 / 3
Progressive Disclosure	No bundle files exist and none are referenced; everything (tool reference tables, template library, multiple frameworks) is inline in a single ~465-line file, so content that should be separate is inline and references are absent — better than a monolithic nested mess but not the well-signaled one-level-deep split that earns a 3.	2 / 3
	Total	10 / 12 Passed

Description

100%

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 well-crafted: third-person voice, multiple concrete actions, broad natural trigger terms, explicit what-and-when guidance, and a clear exclusion clause that bounds its scope. It cleanly satisfies every dimension at the top anchor.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'build programmatic SEO with AI, create competitor alternative pages, optimize for AI Overviews, or scale content production' plus 'AI-powered SEO strategy from keyword research through programmatic page generation' — matching the anchor for listing several specific concrete actions rather than a partial set.	3 / 3
Completeness	Explicitly answers what ('AI-powered SEO strategy from keyword research through programmatic page generation') and when ('Also use when the user mentions...') with concrete triggers and a 'Do NOT use' exclusion, satisfying the both-what-and-when-with-explicit-triggers anchor rather than the implied-when level.	3 / 3
Trigger Term Quality	Provides broad, natural coverage of terms users would actually say — 'SEO,' 'programmatic SEO,' 'AI content,' 'competitor alternative pages,' 'AI Overviews,' 'search optimization,' 'DataForSEO,' 'content at scale,' 'keyword strategy,' 'organic traffic' — so it exceeds the 'some relevant keywords' bar.	3 / 3
Distinctiveness Conflict Risk	Occupies a clear niche (AI-powered programmatic SEO) with distinct triggers and an explicit exclusion ('Do NOT use for technical implementation, code review, or software architecture'), making overlap with other skills unlikely.	3 / 3
	Total	12 / 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: tech-leads-club/agent-skills
Commit: 9026164

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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