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RankCanon

RankCanon

by codepharm99
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

search_docs

Search official Google Search Central SEO documentation by query, then get cited results with URL, title, snippet, and last-changed date for accurate SEO answers.

Instructions

Full-text search over official SEO documentation (Google Search Central).

Returns url, title, snippet, and changed_at (last time content changed) for citation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_docs"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
sourceNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the returned shape and clarifies changed_at ('last time content changed'), which is useful, but says nothing about read-only safety, ranking/freshness behavior, or retrieval limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the core action and then the return contract. No filler, though the parenthetical branding adds little.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so explaining return values is a bonus rather than a requirement. The gap is the input side: with 0% schema coverage and no annotation hints, an agent has no guidance on limit semantics or valid source values.

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

Parameters2/5

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

Schema description coverage is 0% for 3 parameters, so the description must compensate and does not. 'query', 'limit', and especially 'source' (what sources are valid?) are never explained anywhere, leaving the agent guessing on how to scope the search.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('full-text search over official SEO documentation') and even narrows the corpus to Google Search Central. It does not differentiate from siblings like get_doc, but an agent can tell what it does without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: this is the discovery step whose results ('for citation') feed later retrieval. However, no explicit when-to-use vs get_doc or algorithm_updates is given, so the agent must infer the search-then-fetch workflow.

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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