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Setlist Fm

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

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds behavioral context: internal use of ai_visibility_check, ranking, and treating first entity as subject. 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 three sentences with no wasted words. Purpose is front-loaded, followed by mechanism and use case/output format. Perfect conciseness.

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?

The tool has 4 parameters (1 required), no output schema. The description explains the output (ranked list with score, confidence, signal density) and mentions internal probe tool. Minor gaps: no mention of error handling or caching, but overall complete given annotations.

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 does not add significant meaning beyond the schema, except noting that the first entity is treated as 'subject' for narrative, which is not in 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 tool does a side-by-side comparison of AI visibility across multiple entities. It uses specific verbs: 'compare', 'probes', 'ranks', 'surfaces', and distinguishes from sibling like ai_visibility_check (single probe) by being a batch version.

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 provides clear usage context for competitive AI-marketing audits with an example question. However, it does not explicitly state when not to use it or mention 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

A3.6/5.0
Disambiguation2/5

The tool set mixes two completely different domains: setlist.fm (12 tools) and Pipeworx data services (30+ tools). An agent cannot easily distinguish which tools belong to the server's primary purpose, leading to confusion and misselection.

Naming Consistency2/5

Setlist.fm tools use consistent verb_noun patterns (artist, artist_search, artist_setlists), but the majority of tools follow no unified convention: some use snake_case (ai_visibility_check), others use mixed case (ask_pipeworx), creating an inconsistent naming landscape.

Tool Count2/5

43 tools is excessive for a setlist.fm API. Only about 12 are relevant; the remaining 31 are unrelated and bloat the tool surface, making it hard to navigate and maintain.

Completeness4/5

For the setlist.fm domain, the tools cover search, retrieval, and user data comprehensively (artists, setlists, venues, cities, countries, users). Minor gaps exist (e.g., no update/delete operations), but core workflows are supported.

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