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Scan Competitor AI Presence

scan_competitor_ai_presence
Read-onlyIdempotent

Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsNoWhich models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKeyNoOptional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe.
contextNoOptional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names.
entitiesYesArray of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors.

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, non-destructive. Description adds behavioral context: probes each entity with ai_visibility_check, ranks by score, treats first entity as 'subject' for narrative. Beyond annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with core function, efficient use of words. Every sentence adds value. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Describes inputs, processing, and output (ranked list with score, confidence, signal density). Lacks explicit error handling or edge-case behavior, but sufficient given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description adds value by explaining that first entity in 'entities' array is treated as subject for narrative. Other parameters are well-covered by schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it compares AI visibility across multiple entities side-by-side, using ai_visibility_check, ranking by score, and identifying most/least recognized. Distinguishes itself from sibling 'ai_visibility_check' which handles single entities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear use case: competitive AI-marketing audits. Gives example question. Implies alternative for single entity (sibling ai_visibility_check), though no explicit when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation2/5

Many tools cluster around the same purpose: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to similar data sources, and the polymarket_* family has several overlapping edge/arbitrage scanners. The four Recreation.gov tools are distinct but are buried among unrelated Pipeworx tools, making selection ambiguous.

Naming Consistency3/5

Names are all snake_case and readable, with recognizable prefix families like ask_pipeworx*, polymarket_*, and pipeworx_* plus verb_noun names like search_facilities and list_campsites. However, the conventions are mixed: bare verbs, brand prefixes, and composite names coexist, and nothing in the naming signals that this is a Recreation.gov server.

Tool Count1/5

This server is named Recreation Gov but only 4 of 35 tools relate to recreation facilities; the other 31 are a general-purpose data, research, and prediction-market platform. That is an extreme scope mismatch for the server's stated purpose.

Completeness2/5

For the Recreation.gov surface, basic search and detail retrieval exist, but key operations like campsite availability, reservations, and permits are missing. The dominant Pipeworx functionality is unrelated to Recreation.gov, so the tool set as a whole has no coherent domain coverage.