Infers and applies likely data types at target addresses within IDA Pro databases, enabling better reverse engineering and binary analysis.
Infer and apply likely types at target addresses.
| Name | Required | Description | Default |
|---|---|---|---|
| addrs | Yes | Addresses to infer types for | |
| instance_id | Yes | 必须提供的 instance_id（或 client_id），用于将请求精确路由到特定的 IDA 实例。请先调用 instance_list 查看并选择合适的客户端 ID。 |
Changes observed during successful MCP inspections.
v2.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral burden. 'Apply' implies a mutation of the IDB, but the description never states whether changes are reversible, what 'likely types' are based on, what gets modified, or any permission/scope constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short, front-loaded sentence with no filler. It is efficient, though its brevity contributes to the behavioral gaps noted elsewhere.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Parameters are fully covered by the schema, but for a mutation tool with no annotations and no output schema, the description leaves key behavioral questions (reversibility, inference basis, scope of modification) unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both addrs and instance_id documented in the schema, including a detailed routing note for instance_id. The description adds nothing beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb pair (infer and apply) plus resource (types) and location (target addresses), which is more informative than a bare name restatement. However, it does not differentiate itself from close siblings like set_type, declare_type, or type_apply_batch, so an agent must infer the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this versus the many type-related siblings (declare_type, set_type, type_apply_batch). The agent gets no signal about automatic-inference vs manual-setting workflows, leaving selection to guesswork.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.