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by io.github.pipeworx-io

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

A4.5/5.0
Behavior4/5

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

Annotations declare the tool read-only, idempotent, and open-world. Description adds internal behavior ('probes each entity with ai_visibility_check') and output structure ('ranked list with score, confidence, signal density per entity'). No contradictions. Sufficiently discloses behavioral traits beyond annotations.

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?

Two sentences: first states core action, second provides purpose and output. No wasted words, front-loaded, every sentence earns its place.

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

Completeness5/5

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

Given no output schema, description sufficiently explains return values (ranked list with score, confidence, signal density). All 4 parameters are implicitly covered. Complexities like optional _apiKey and context are addressed. No critical gaps.

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%, providing baseline 3. Description adds meaning: 'first entry treated as subject' for entities, 'omit for just workers-ai' clarifies default. This adds value beyond the schema alone.

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 the tool's purpose: comparing AI visibility across multiple entities, probing each with ai_visibility_check, ranking by score, and surfacing most/least recognized. The specific verb 'compare' and resource 'competitor AI presence' differentiate it from siblings like ai_visibility_check (single entity) and general compare_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?

Description provides a concrete use case ('competitive AI-marketing audits') and an example question. It does not explicitly state when not to use or contrast with sibling tools, but the context is clear enough for an agent to infer appropriate usage.

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

A3.8/5.0
Disambiguation2/5

Multiple tools have overlapping purposes (e.g., three variants of ask_pipeworx, several polymarket tools, and multiple discovery/entity tools). Despite detailed descriptions, the similiar functionalities create confusion for an agent selecting among them.

Naming Consistency3/5

Tool names are consistently in snake_case but the verb/noun pattern is mixed: some start with verbs (ask_, list_, remember_), others with nouns (entity_profile, polymarket_edges). This inconsistency reduces predictability.

Tool Count2/5

35 tools is high for a single server, especially when the scope spans two disparate domains (HDX humanitarian data and Pipeworx data platform). Many tools could be logically split into separate, more focused servers.

Completeness3/5

The tool set covers a wide range of functionality (data retrieval, comparison, monitoring, memory) but has notable gaps: no direct data download tool for HDX resources, no account management, and no exploration of Pipeworx packs beyond discover_tools.

Resources