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Strings Extractor

extract_strings
Read-onlyIdempotent

List the readable text inside any file, given as base64, at most 2,000,000 bytes: runs of ASCII and UTF-16LE characters (UTF-8 on request) at least min_length long, with byte offsets. Labels each string by shape as a URL, email, IP address, file path, key or token, or other, and counts every kind across the whole file; the list can be narrowed by kind or text and holds up to 2,000 strings in file order. Pure standard library, no network or model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesRequired. Any file, as base64 or a base64 data URL; at most 2,000,000 bytes once decoded.
kindsNoOnly list strings of these kinds (url, email, ip, path, key, other). Counts always cover all.
limitNoMost strings to list, in file order. Default and maximum 2,000.
containsNoOnly list strings containing this text (any case).
filenameNoOptional file name, used only in the result text.
encodingsNoWhich text to look for: ascii, utf-16le and utf-8. Default ascii and utf-16le; utf-8 also reads accented and other non-English letters, and finds more false text in random bytes.
min_lengthNoShortest run of characters to keep, 3 to 32. Default 4.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so credit goes to the added context: 'Pure standard library, no network or model', the labeling/counting behavior, file-order output, and the 2,000-string cap. Input validation and failure modes (bad base64, oversized file) are not stated.

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?

Front-loaded with purpose in the first clause, and every clause carries information (extraction rule, labeling, filtering, limits, no-network stance). It is one very dense run-on sentence, which slightly hurts scanability, but there is no padding.

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 no output schema, the description carries the return burden and does cover labels, counts, ordering, byte offsets and the list cap, which is good. However it omits error/failure behavior for malformed base64 or truncated input and does not explain the interaction between encodings and false positives beyond a schema-level remark.

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 baseline is 3, and the description largely paraphrases it (kinds filtering, counts covering all, default/max limit, case-insensitive contains, encodings). The one genuine addition beyond the schema is that results carry byte offsets, which is return-shape information rather than parameter semantics.

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?

Names a specific verb and resource ('List the readable text inside any file') and immediately scopes it with the input format (base64) and extraction rule (runs of ASCII/UTF-16LE characters). This clearly separates it from adjacent siblings like inspect_binary, inspect_apk, find_data and get_transcript.

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?

The description implies the use case (pulling readable strings out of a binary/blob) and states the 2,000,000-byte ceiling, but never explicitly says when to choose this over inspect_binary, inspect_apk, or find_data, nor what happens with a non-base64 or oversized input. Usage is inferable but not routed.

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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