Skip to main content
Glama

extract_strings

Extract printable ASCII and UTF-16LE strings from binary files with offset and section details. Returns structured data with totals and truncation status.

Instructions

Extract printable ASCII and UTF-16LE strings from path.

Returns {"ascii": [...], "utf16le": [...], "totals": {...}, "truncated": bool}. Each string has string, offset, and section fields.

.. note:: This is the v2.4 shape, kept stable for backward compatibility. New code should call categorize_strings (below), which returns the same ascii / utf16le arrays plus a keyword-bucketed by_category block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
min_lengthNo
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses return structure (fields, totals, truncated flag) and notes stability for backward compatibility. Lacks mention of side effects or performance, but overall transparent.

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?

Concise overall, with a clear front-loaded purpose. The note adds value without excessive verbosity. A slight improvement would be integrating parameter info, but structure is good.

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?

Given 2 parameters, no output schema, and no annotations, the description covers return structure and sibling context well. The only missing element is the min_length parameter explanation, but otherwise 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%. The description only mentions path implicitly. The min_length parameter is not described, its default or effect is missing, leaving the agent with incomplete information for parameter usage.

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 the verb 'Extract', the resource 'strings', and specifies the types 'printable ASCII and UTF-16LE'. It also distinguishes from sibling 'categorize_strings' by noting the return shape and backward compatibility.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises new code to use 'categorize_strings' instead, providing clear when-to-use guidance and alternatives, making it straightforward for an AI agent to choose correctly.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Heretek-RE/re-lief'

If you have feedback or need assistance with the MCP directory API, please join our Discord server