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Barcelona Events

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 already indicate safe, read-only, idempotent behavior. Description adds how it probes each entity internally and returns ranked list with score, confidence, signal density. 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?

Three sentences, front-loaded with purpose. Each sentence adds value: what it does, how it works, use case/output. No waste.

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?

Despite no output schema, description fully specifies input (2-8 entities), process (probe and rank), and output (ranked list with score, confidence, signal density). Annotations cover safety. Complete for this tool.

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 covers 100% of parameters. Description adds key semantics: first entity is 'subject', rest are competitors; 'models' default to workers-ai; 'context' disambiguates common names. Adds meaning beyond 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?

Description clearly states verb 'compare', resource 'AI visibility', and action 'probes each entity with ai_visibility_check, ranks by score'. Distinguishes from sibling 'ai_visibility_check' (single entity) and 'compare_entities' by focusing on AI presence.

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?

Explicitly states usage context: 'useful for competitive AI-marketing audits' and provides a concrete question. But does not explicitly state when not to use or mention alternatives.

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

Many tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual queries with subtle differences, and the Polymarket suite (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) has fine-grained distinctions that are hard to separate. The single Barcelona events tool is isolated and unrelated to the rest, adding to agent confusion.

Naming Consistency3/5

Most tool names use snake_case and many follow a verb_noun pattern, but there are notable inconsistencies: noun-first names (entity_profile, polymarket_arbitrage, pipeworx_trending) and modifiers like beta/grounded on ask_pipeworx introduce non-uniformity. Overall the set is readable but not consistently predictable.

Tool Count2/5

With 32 tools, the set is beyond the well-scoped 3-15 range. The count is especially inappropriate for a server named 'Barcelona Events' because only one tool actually relates to Barcelona events; the other 31 are a broad data-research and utility collection with no clear connection to the server's apparent purpose.

Completeness1/5

For a server named 'Barcelona Events', the surface is severely incomplete: it offers a single events search tool with no create, update, delete, detail, venue, or organizer operations. Even interpreting the domain broadly, the mismatch between the server name and the tool set leaves a critical gap between user expectation and actual capability.

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