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by dev.agentbits

mime_lookup

Map a file extension such as webp or png, or a MIME type string, to curated Content-Type metadata when setting headers, validating uploads, or choosing a media type.

Use when:

  • What MIME type should I use for a .webp file?

  • Look up metadata for Content-Type application/json

  • Resolve a file extension to the correct MIME type for an upload or response header

Do not use when:

  • Sniff or detect MIME type from raw file bytes

  • Encode or decode Base64 file payloads (use base64_encode / base64_decode)

  • Look up DNS top-level domain metadata (use tld_lookup)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses a key boundary: 'Do not use when: Sniff or detect MIME type from raw file bytes', which clarifies that this tool does not perform byte-level detection. Phrases like 'Map ... to curated Content-Type metadata' imply a read-only operation, but it does not explicitly state 'read-only' or mention side effects, rate limits, or output format. Given the tool's simplicity, this is a minor shortfall.

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?

The description starts with a concise definition, followed by well-organized 'Use when' and 'Do not use when' bullet lists. Every sentence contributes value, and the structure makes it instantly scannable. It is appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single parameter, no output schema, and no annotations, the description is remarkably complete. It covers the purpose, provides lookup examples, lists exclusions, and names sibling tools for redirection. The agent gets enough context to invoke the tool correctly without missing critical details.

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

Parameters4/5

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

The schema only says 'query' is a string with minLength 1, and schema coverage is 0%. The description compensates by clarifying acceptable input forms: 'a file extension such as webp or png, or a MIME type string' and gives a real-world example ('Content-Type application/json'). It adds useful context beyond the schema, though it doesn't cover every edge (e.g., dot handling, case sensitivity).

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 opens with a specific and clear statement: 'Map a file extension such as webp or png, or a MIME type string, to curated Content-Type metadata.' This clearly indicates the verb (map), resource (file extension/MIME type to metadata), and purpose, and it is distinct from sibling lookup tools like tld_lookup or base64_encode.

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?

The description explicitly provides 'Use when' and 'Do not use when' sections with concrete examples like 'What MIME type should I use for a .webp file?' and alternatives such as 'use base64_encode / base64_decode' and 'use tld_lookup'. This gives the agent clear guidance on when to select this tool vs others.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct data format and operation, with explicit 'Do not use when' cross-references to prevent confusion. For example, base64_encode/decode, url_encode/decode, and timestamp_convert/timezone_convert are clearly separated, and the various validators (ISBN, Luhn, UUID, JSON) apply to different identifiers.

Naming Consistency4/5

Most tool names follow an object_operation pattern (e.g., base64_decode, country_lookup, timestamp_convert), using lowercase with underscores. The main deviation is countries_bulk, which uses a noun+adjective form without an explicit operation, making it inconsistent with the verb-like operations used elsewhere.

Tool Count3/5

With 18 tools, the server falls into the 16-25 range which feels heavy for a utility collection. While each tool is individually useful and the scope is broad, the count is higher than typical for a well-focused server and may overwhelm agents scanning the available options.

Completeness4/5

The set provides solid coverage of encoding/decoding, validation, lookups, and conversions, with paired encode/decode and convert functions. However, some common utilities such as hashing, HTML entity encoding, UUID generation, or email validation are absent, leaving minor gaps for agents that need those operations.

Resources