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Search strings/immediates/refs

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Search strings, immediates, data refs, or code refs by target with offset/limit pagination to isolate specific matches in a binary during reverse engineering.

Instructions

Search strings/immediates/refs for targets with offset/limit pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSearch type: 'string', 'immediate', 'data_ref', or 'code_ref'
limitNoMax matches per target (default: 1000, max: 10000)
offsetNoSkip first N matches (default: 0)
targetsYesSearch targets (strings, integers, or addresses)
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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the offset/limit pagination behavior, which is useful, but says nothing about result shape beyond what the output schema carries and nothing about rate or scope caveats.

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 tight sentence with no filler and the pagination trait placed at the end. It is appropriately sized, though somewhat telegraphic for a 5-parameter search tool.

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?

With an output schema present, return values need not be explained, and the schema covers all parameters. What is missing is context that would let an agent choose this tool over its many search siblings, so completeness is only minimally adequate.

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 (type, targets, limit, offset, instance_id) is already documented in the schema. The description only restates offset/limit pagination and adds no syntax or semantics beyond that, 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 concrete verb+resource ('Search strings/immediates/refs for targets'), so an agent knows it retrieves occurrences of specific values inside a binary. However, it never distinguishes itself from close siblings like find_regex, find_bytes, search_text, or xref_query, which an agent could easily confuse with this tool.

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?

The description gives no when-to-use guidance, no prerequisites, and no comparison to alternatives. Given a large sibling set of similarly named search tools (find_regex, find_bytes, search_text, entity_query), the absence of routing guidance is a real gap.

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