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duration_parse

Parse duration (ISO-8601 PnDTnHnMnS or human 1h30m / 90s) to seconds. When: Parse ISO-8601 / human durations to seconds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It informs users that the tool accepts two input formats and returns seconds. However, it does not disclose error handling (e.g., behavior on invalid input), output precision, or any constraints like maximum duration length. This is adequate for a simple parser but could be more 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?

The description is short (two sentences) and front-loaded with the purpose and examples. The second sentence ('When: ...') is somewhat redundant, but the overall structure is efficient and easy to scan.

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 the tool's simplicity (1 parameter, no output schema, no nested objects), the description provides sufficient context: input format, output unit, and usage scenario. It does not elaborate on the exact return value, but for a parsing tool that returns a number of seconds, this is likely sufficient for an AI agent.

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

Parameters5/5

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

The schema has 0% description coverage for the single parameter 'value', so the description is essential. It adds critical meaning by explaining that the string can be ISO-8601 ('PnDTnHnMnS') or human-readable formats ('1h30m', '90s'), which is not conveyed by the schema alone.

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 tool's purpose: parsing ISO-8601 and human-readable durations (with examples like '1h30m', '90s') to seconds. It distinguishes this tool from its siblings (none of which handle duration parsing), making it easy for an agent to select it for duration conversion tasks.

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 'When: Parse ISO-8601 / human durations to seconds.' line provides explicit context for when to use the tool. Although it does not mention when not to use it or suggest alternatives, the sibling tools are all different parsing/encoding utilities, so the usage scope is well-defined.

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

B3/5.0
Disambiguation5/5

Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.

Naming Consistency5/5

All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.

Tool Count1/5

193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.

Completeness4/5

Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.