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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

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, non-destructive. The description adds that the tool probes each entity using ai_visibility_check and ranks results, providing behavioral context 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?

The description is concise (5 sentences), front-loaded with purpose, and each sentence adds value. No wasted words.

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, the description explains the return value (ranked list with score, confidence, signal density). Parameter count is moderate, all are covered. Annotations are rich. The description is complete for the tool's function.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description paraphrases some parameters ('Optional shared context', 'Optional Anthropic API key') but adds no new meaning beyond the schema.

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?

The description clearly states the verb 'Compare AI visibility' and the resource 'multiple entities'. It distinguishes from the sibling tool 'ai_visibility_check' which handles single entities, and from 'compare_entities' which may have a different focus.

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?

The description explicitly mentions the use case 'competitive AI-marketing audits' and gives an example question. It implies when not to use (single entity check), but lacks an explicit exclusion statement.

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

A3.6/5.0
Disambiguation3/5

Tools are mostly distinct but there is some overlap among lookup tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) and among Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage). Agents might occasionally struggle to choose the right one.

Naming Consistency2/5

Naming is inconsistent: some use verb_noun snake_case (ask_pipeworx, compare_entities), some are single words (forget, recall, remember), and others are noun-based (compliance_catalog, entity_profile). No consistent pattern.

Tool Count1/5

With 34 tools, the count is too high for a server named 'ISO Standards'. The majority of tools are unrelated to ISO standards (e.g., Polymarket, memory, web scraping), making the scope highly inappropriate.

Completeness1/5

As an ISO standards server, the tool set is severely incomplete. Only 4-5 tools (search_standards, get_standard, compliance_catalog, open_data_files) actually deal with ISO standards. Essential operations like comparing standards or browsing revisions are missing.

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