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Ida Python Reference

ida_python_reference

Search official IDAPython API docs from the attached IDA runtime to retrieve function signatures and docstrings; query 'modules' to list available modules.

Instructions

Search the official IDAPython API documentation (from the attached IDA runtime). Returns signatures + docstrings; pass 'modules' as query to list modules.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of entries returned (default 20)
queryYesClass, function, or concept to look up in the official IDAPython docs of the attached IDA runtime, e.g. 'decompile', 'xrefs to', 'ida_funcs', 'rename local variable'. Use 'modules' to list modules.
moduleNoRestrict the search to one module, e.g. ida_funcs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.7

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the return content (signatures + docstrings) and the precondition that a runtime must be attached, but says nothing about search matching behavior, result ranking, truncation beyond the schema's limit, or failure when no runtime is attached.

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

Conciseness5/5

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

Two tight sentences, front-loaded with purpose and followed immediately by the return content and the special query value. No filler.

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?

For a read-only lookup tool with a fully documented schema and no output schema, the description covers purpose, return shape, and the module-listing entry point adequately. Only minor gaps remain around how matching works and what happens without an attached runtime.

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 query, module, and limit with examples. The description's only parameter-related content ('pass modules as query') merely restates what the schema already states, 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 (Search) and resource (official IDAPython API documentation from the attached IDA runtime), and notes the return payload (signatures + docstrings). It is clearly distinguishable from code-execution siblings like py_eval or py_exec_file, though it never names an alternative explicitly.

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 by 'Search the official IDAPython API documentation', and there is one concrete hint ('pass modules as query to list modules'). However there is no guidance on when to reach for this versus the sibling code tools or other search tools, and no exclusions.

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