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Medium: List responses

medium_list_responses
Read-only

Medium: Responses to a story, with author, text and whether you replied. Lists the responses under one story, with the author, text and whether you already replied. Hidden responses are not returned. Pass response_id to reply_to_response. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoNext page cursor from the previous call.
story_idYesStory ID from list_stories.
unanswered_onlyNoSkip responses you already replied to.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavioral context beyond them: hidden responses are filtered out, and the call requires a Cotlet API key with access to the app (an auth prerequisite). No return-format or rate-limit detail is given, but that is a minor gap against strong annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first two sentences are near-duplicates: 'Responses to a story, with author, text and whether you replied' and 'Lists the responses under one story, with the author, text and whether you already replied' convey the same content. The later sentences (hidden filtering, reply routing, auth) earn their place, but the redundancy costs this dimension.

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?

For a read-only list tool with a fully described schema and no output schema, the description covers the essentials: what it returns, filtering of hidden responses, pagination via cursor in the schema, the follow-up tool, and the auth requirement. Nothing critical is missing, though return format and pagination semantics are left to the schema.

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 all three parameters (story_id, cursor, unanswered_only) are already documented in the schema. The description adds only marginal meaning — it links response_id to reply_to_response and implies the 'whether you replied' flag relates to unanswered_only. Baseline 3 is appropriate when the schema does the heavy lifting.

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 states a specific verb and resource ('Lists the responses under one story') and immediately names the fields returned (author, text, whether you replied). It also names the sibling tool reply_to_response for the follow-up action, so an agent can place this among medium_list_stories and medium_reply_to_response without opening schemas.

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 gives clear context (responses under a single story, hidden responses excluded) and routes the agent to reply_to_response for the reply action. It does not, however, state explicit exclusions or when a different listing tool would be preferable, so it stops short of full when/when-not guidance.

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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