Skip to main content
Glama

format_bytes

Convert byte values into human-readable formats using binary (1024-based) or decimal (1000-based) systems with customizable precision.

Instructions

Format bytes to human-readable format (binary or decimal)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bytesYesNumber of bytes to format
formatNoFormat type: binary (1024-based) or decimal (1000-based) (default: binary)
precisionNoNumber of decimal places (0-10, default: 2)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the two format types (binary/decimal) but doesn't describe what 'human-readable format' means in practice (e.g., returns strings like '1.5 MB'), doesn't mention default behaviors beyond what's in the schema, and doesn't address edge cases like negative bytes or performance characteristics. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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 is extremely concise - a single sentence that efficiently communicates the core functionality. Every word earns its place: 'Format bytes' (action), 'to human-readable format' (outcome), '(binary or decimal)' (key options). No wasted words or unnecessary elaboration for this straightforward utility 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?

Given this is a simple data formatting utility with 3 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. However, without annotations and with no output schema, the description should ideally clarify what 'human-readable format' returns (e.g., string with units) and mention any default behaviors. It's complete enough for basic understanding but lacks output details that would help the agent use it effectively.

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 schema already fully documents all three parameters (bytes, format, precision). The description adds minimal value beyond the schema - it mentions 'binary or decimal' which is already in the format parameter's enum description. No additional parameter semantics, examples, or constraints are provided beyond what's in the structured schema.

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?

The description clearly states the tool's purpose: 'Format bytes to human-readable format' with the specific verb 'format' and resource 'bytes'. It distinguishes between 'binary or decimal' formats, though it doesn't explicitly differentiate from sibling tools like format_number or format_json. The purpose is specific but lacks sibling comparison context.

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 provides no guidance on when to use this tool versus alternatives. There's no mention of when this specific byte formatting is appropriate compared to other formatting tools (format_number, format_json) or conversion tools. The agent must infer usage from the tool name alone without contextual direction.

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/Angry-Robot-Deals/mcp-sys8'

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