Skip to main content
Glama

clarify

Resolve a clarification request by submitting the replay token and the zero-based index of the user's chosen option.

Instructions

Replay dispatcher for clarification-needed responses. When a tool returns { kind: 'clarification-needed' }, present the question and options to the user, then call this tool with the replayToken from that response and the zero-based index of the option the user selected. The server resumes the original tool call with the disambiguation applied and returns the final result envelope. Tokens are single-use and expire after 5 minutes — call this tool promptly after the user responds. Passing an expired or unknown token returns a NotFound error. Passing a choice index outside the valid range returns an InvalidInput error. Example: clarify({ replayToken: "tok_abc", choice: 0 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
choiceYesZero-based index of the option the user selected (matches ClarificationOption.index).
replayTokenYesOpaque token from the clarification-needed envelope's replayToken field.
Behavior5/5

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

Without annotations, the description fully discloses behavioral traits: token single-use, 5-minute expiry, error conditions (NotFound for expired/unknown tokens, InvalidInput for out-of-range choice), and the overall behavior of resuming the original tool call.

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 a single dense paragraph but covers all necessary information efficiently. It could be slightly more structured (e.g., bullet points), but the content is precise and front-loaded with the purpose.

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 no output schema, the description explains the return (final result envelope) and covers workflow, errors, and an example. For a 2-parameter tool, this is fully complete.

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?

Schema coverage is 100% with descriptions, but the tool description adds crucial context: replayToken comes from the clarification-needed envelope, choice is a zero-based index matching ClarificationOption.index, and provides an example. This adds value beyond the schema.

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 role as a replay dispatcher for clarification-needed responses, explaining the interaction flow and distinguishing it from sibling tools by its specific function in disambiguation.

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?

It explicitly states when to use the tool (after receiving a clarification-needed response) and provides context on token expiry and the need for promptness. However, it does not explicitly mention when not to use it, though the scenario is well-defined.

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/torsday/omnifocus-mcp'

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