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chatgenius-mcp

chatgenius-mcp

Official
by SumCodeAI

approve_comment_reply

Destructive

Approves a pending comment reply by publishing it publicly under the comment, optionally posting edited text instead of the AI draft.

Instructions

Approve a reply. Posts the pending reply publicly under the comment, as the account. Send {"text": "..."} to post an edited reply instead of the AI draft; the draft is kept and edited becomes true. Only a pending comment can be approved (409 not_pending). A successful send counts against the plan's reply cap. Send Content-Type: application/json with an empty object when not editing; the server refuses a bodiless POST.

Input Schema

NameRequiredDescriptionDefault
idYesNumeric id.
textNoPost this instead of the AI draft.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses the public posting side effect, that the AI draft is retained and an 'edited' flag becomes true, the 409 not_pending failure mode, and that success consumes the plan's reply cap. It even documents the transport requirement (Content-Type: application/json, empty object instead of a bodiless POST), which is exactly the kind of operational detail annotations cannot express.

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?

Front-loads the action and effect, then layers edit semantics, failure mode, quota, and transport requirements in a tight block with no filler. It is dense but every sentence carries operational value; only the transport note could arguably be tightened.

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 destructive, non-idempotent mutation with annotations covering the safety profile, the description supplies preconditions, side effects, and quota impact. The one remaining gap is the response shape — no output schema exists, and 'edited becomes true' hints at a return field that is never described.

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?

Schema coverage is already 100%, so the baseline is 3, but the description adds real meaning: 'text' replaces the AI draft rather than appending to it, the draft survives, and an 'edited' flag flips — semantics not conveyed by the schema's one-line 'Post this instead of the AI draft.'

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?

States a specific verb and resource ("Approve a reply") and immediately describes the effect: it posts the pending reply publicly under the comment as the account. This is distinguishable at a glance from reject_comment_reply and the bulk variants in the sibling list.

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?

Gives a concrete precondition for use — only a pending comment can be approved, otherwise 409 not_pending — and explains the two invocation modes (approve the AI draft vs. post edited text). It does not explicitly route to reject_comment_reply or the bulk tools, so alternative selection is left implicit.

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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