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Ai search history

ai_search_history
Read-onlyIdempotent

Read the plan, the saved searches, the last runs and the position trend of each search. Reads never call the search engine. The trend compares each search of the newest run with the previous run that had it: up, down, same, new or lost.

Input Schema

NameRequiredDescriptionDefault
idYesSite owned by this account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real value: it clarifies that reads never invoke the search engine (no external calls or quota impact) and spells out the trend semantics (up/down/same/new/lost) that the annotations cannot express.

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?

Front-loaded with the read scope, followed by a key behavioral caveat and a compact definition of the trend values. Every sentence carries information; the trend clause is dense but earns its place by defining return semantics not available elsewhere.

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?

There is no output schema, so the description must characterize the return, and it does: plan, saved searches, last runs, and per-search trend values. Combined with annotations covering safety and a fully documented parameter, an agent has enough to call it correctly, though pagination or result shape is not addressed.

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 coverage is 100% with a single documented 'id' parameter, so the schema does the heavy lifting. The description adds no syntax, format, or constraint detail about the id beyond what the schema already provides. Baseline 3 is appropriate.

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 clear verb (Read) and enumerates the resource contents: plan, saved searches, last runs, and position trend. An agent knows exactly what data this returns. It doesn't explicitly differentiate itself from siblings like ai_search_visibility or save_ai_search_queries, but the scope is unambiguous.

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

Usage Guidelines2/5

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

No when-to-use guidance and no named alternatives. The description explains what is returned but never states the condition that selects this tool over ai_search_visibility or save_ai_search_queries. The 'reads never call the search engine' note is behavioral, not a usage selector.

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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