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Anythink-MCP

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Search: audit

search_audit
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Compare an entity's configured public-searchable fields against what public search returns to detect and flag data leaks.

Instructions

Compare configured public-searchable fields vs what public search actually returns. Flags any data leaks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch query to use for the audit (default: '*' — wildcard across all records)
entityYesEntity to audit
sampleNoHow many records to inspect (default: 5)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.27

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description usefully clarifies that the operation is a config-vs-actual comparison that flags leaks, but it omits return format, sample behavior, and any side effects or rate characteristics. With annotations carrying the safety burden, a 3 is appropriate.

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 tightly written sentences with the core comparison front-loaded and the leak-flagging outcome second. There is no filler, though the extreme brevity leaves the other dimensions thin.

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?

For a 3-parameter tool with no output schema, the description should ideally hint at what the audit returns (the diff structure, how leaks are reported). It conveys the concept but not the result shape, so an agent knows what the tool does but not what to expect back.

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%, so the schema already documents query, entity, and sample (including defaults). The description adds no syntax or format detail beyond the schema, so the baseline 3 is correct when the schema does all the work.

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?

The description states a specific operation: comparing configured public-searchable fields against what public search actually returns, plus flagging leaks. This is clearly distinct from siblings like search_query, search_purge, or search_similar, though it never explicitly names them. The verb+resource is concrete enough for an agent to understand the intent.

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?

There is no explicit when-to-use guidance, no prerequisites, and no comparison against alternatives such as search_query or search_similar. The auditing use case is only weakly implied by 'Flags any data leaks.' Nothing tells the agent under what circumstances to prefer this over running a plain search.

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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