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Podcastindex

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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint. The description adds that it probes each entity with ai_visibility_check, ranks by score, and returns metrics (score, confidence, signal density), which is useful beyond annotations. No 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?

The description is concise (5 sentences), front-loaded with the core purpose, and every sentence contributes value without 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?

Given no output schema and 4 parameters, the description adequately explains input, process, and output format. It does not cover error handling but is sufficient for typical use.

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 description coverage is 100%. The description adds extra meaning by explaining the first entity is treated as the subject and the context parameter for disambiguation, going beyond 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?

The description clearly specifies a verb ('scan', 'compare') and resource ('competitor AI presence'), and distinguishes from sibling tools like ai_visibility_check by emphasizing multi-entity comparison and ranking.

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 includes a concrete use case (competitive AI-marketing audits) and implies when to use it, but does not explicitly state when not to use it or name alternatives like compare_entities.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx and ask_pipeworx_grounded overlap (one is grounded), and bet_research/validate_claim/compare_entities/entity_profile all query Pipeworx data with different intents, which could cause confusion.

Naming Consistency4/5

Names are consistently lower_snake_case and mostly follow a verb_noun pattern (e.g., search_podcasts, get_podcast, list_subscriptions). A few compound names like pipeworx_feedback and polymarket_arbitrage deviate slightly but remain readable.

Tool Count2/5

30 tools is excessive for a server named 'Podcastindex'. It aggregates unrelated domains (podcasts, Pipeworx queries, Polymarket, memory, etc.), making it feel like a kitchen sink rather than a focused tool set.

Completeness3/5

For podcasts, the tool set covers search, metadata, episodes, and trending but lacks subscription management. For the broader Pipeworx domain, ask_pipeworx and discover_tools provide wide access, but specific gaps exist (e.g., no direct SEC filing query). Overall, the surface is broad but uneven.

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