Skip to main content
Glama

Query imports with filters

imports_query
Read-only

Find and filter imported functions and modules in IDA with name/module patterns and pagination for targeted reverse engineering.

Instructions

Query imports with richer filtering than imports(offset,count).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesImport query with import/module filters 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

B3.4/5.0
Behavior2/5

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

The readOnlyHint annotation already establishes this is a safe read, so the description must add its own behavioral value. It adds none: nothing about batch/multi-query semantics, glob-vs-regex interpretation, or that count=0 returns everything. Effectively it paraphrases the schema.

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 zero filler and the key differentiator (richer filtering) placed early. It is arguably too terse for a nested batch-query schema, but on conciseness alone it is efficient.

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. However, the notable structural feature — queries being an array/object of multiple import queries — is left entirely to the schema, leaving the description thin for this complexity level.

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 every parameter (filter, module, offset, count, instance_id) is documented in structured data. The description's phrase "richer filtering" gestures at filter/module but adds no meaning beyond the schema, so baseline 3 applies.

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 ("Query imports") and explicitly compares its scope to the sibling tool imports(offset,count). The differentiator "richer filtering" is vague about which filters are richer, but an agent can still tell it apart from the plain imports listing.

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?

Names the alternative (imports(offset,count)) and the condition that selects this one over it, so routing is clear. It stops short of saying when neither tool is appropriate or noting prerequisites such as an open database.

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