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Find strings

find_strings
Read-only

Search defined string data in a binary to locate messages, then identify code references for deeper analysis.

Instructions

Search defined string data. Usually the fastest way into an unknown binary - find the message, then look at what references it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A3.9/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, covering the safety profile, and the description aligns with that by describing a search operation. The description adds a speed/strategy heuristic beyond the annotations, but it does not disclose behavioral details such as case sensitivity, substring vs. exact matching, or how the limit parameter affects results. This is acceptable given the read-only annotation but not richly transparent.

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 short sentences deliver a precise definition and a useful workflow heuristic. Every word earns its place, and the core action is front-loaded. No redundancy or 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 simple read-only search tool, the description provides enough to understand purpose and workflow. However, since there is no output schema and parameter descriptions are absent, an agent must infer query matching behavior, result shape, and the practical meaning of the limit parameter. Slightly more detail would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden of explaining parameters. It does not compensate: there is no mention of what query means (substring, regex, case sensitivity) or how limit behaves beyond the schema's min/max. The parameter names are somewhat self-explanatory, but the description adds no semantic value for them.

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

Purpose5/5

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

The description clearly states a specific action and resource: 'Search defined string data.' It also distinguishes itself from function-oriented siblings like decompile, list_functions, and call_graph by emphasizing string discovery. The added heuristic about finding a message and looking at references makes the purpose concrete and memorable.

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?

The description gives explicit context: it is 'usually the fastest way into an unknown binary' and suggests a follow-up step ('find the message, then look at what references it'). It does not explicitly name the sibling tool xrefs_to or state when not to use it, but the intended workflow is clear.

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

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