Skip to main content
Glama

Generic IDB entity query

entity_query
Read-only

Query IDB entities such as functions, globals, imports, strings, and names using typed filters, field projection, sorting, and pagination to retrieve focused reverse-engineering data.

Instructions

Query IDB entities with typed filters, projection, and pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesGeneric entity query with filtering, projection, and pagination
instance_idNoOptional database instance id. If omitted, use the current target.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv20261008.0.1

TDQS

C2.7/5.0
Behavior2/5

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

readOnlyHint=true already tells the agent this is a safe read. The description adds essentially nothing behavioral beyond that: it does not mention multi-query batching semantics, that count=0 means all, instance_id fallback to the current target, or any rate/size limits. With annotations covering safety, the description contributes only restated structure.

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?

A single front-loaded sentence with no padding, which is appropriately sized for a thin wrapper tool. It is efficient, though minimal to the point of under-specification for a tool of this breadth.

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 return values need not be described, and annotations carry the safety profile. What is missing is the routing context: with ~60 sibling tools, a generic query tool needs at least a pointer to when it is the right choice. Minimum viable but with a clear gap.

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 the schema already documents every flag (kind, filter, regex, sort_by, offset, count, etc.). The description's mention of "typed filters, projection, and pagination" loosely maps to those params but adds no syntax or interaction detail. Baseline 3 when the schema does the heavy lifting.

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

Purpose3/5

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

States a generic verb+resource ("query IDB entities") and hints at capability areas (typed filters, projection, pagination). However, "IDB entities" is vague and never names the concrete kinds (functions/globals/imports/strings/names) that the schema exposes, and it does nothing to distinguish this from the many specialized siblings like func_query, xref_query, insn_query, and type_query.

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 at all. Given the sibling list contains numerous purpose-built query tools, the agent has no signal for when the generic entity_query is preferred over func_query/list_funcs/imports_query. It states what it can do but not when to reach for it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.