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Jisho

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
Behavior5/5

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

Describes process: probes with ai_visibility_check, ranks, surfaces most/least recognized. Returns score, confidence, signal density per entity. Annotations already indicate read-only; description adds rich behavioral detail.

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, front-loaded with purpose and output. Every sentence adds value; no redundancy or 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 4 parameters fully described in schema, no output schema, and annotations covering safety, the description adequately explains the tool's purpose, process, and return structure.

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 3. Description adds no further parameter meaning beyond summarizing the probe process. No contradiction or omission noted.

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 states specific verb 'compare AI visibility' and resource 'multiple entities', with clear output of ranked list. Distinguishes from sibling 'ai_visibility_check' (single entity) and 'compare_entities' by targeting 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 useful for competitive AI-marketing audits with example. Implicitly for multiple entities, but no explicit when-not-to-use or direct contrast with siblings like ai_visibility_check.

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
Disambiguation3/5

Most tools have distinct purposes, but there are overlapping tools like the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and ai_visibility_check/scan_competitor_ai_presence. A few pairs could cause confusion, but overall differentiation is moderate.

Naming Consistency2/5

Tool names follow no consistent pattern: some are imperative verbs (remember, forget), some are compound nouns (entity_profile, polymarket_arbitrage), some are descriptive phrases (recent_alerts, scan_dependency). The verb_noun pattern is absent, leading to inconsistency.

Tool Count1/5

33 tools is far too many for a server named 'Jisho' (a Japanese dictionary), especially since only 2 tools (lookup, search_words) are dictionary-related. The majority of tools belong to an unrelated data platform, making the count wildly inappropriate for the server's apparent purpose.

Completeness3/5

For the dictionary domain, the server lacks common features like example sentences or kanji details. However, the extended tool set covers many data retrieval and analysis tasks, though it is read-heavy with no update/delete capabilities for most resources.

Resources