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generate_persona_reply

Draft a reply, in the user's trained voice, to an inbound comment or message on one of their posts. The draft is saved as pending for review (list_persona_replies) — nothing is sent. Needs a plan with PersonaForge replies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformYesPlatform the conversation is on.
inbound_textYesThe comment or message to reply to (max 2000 characters).
source_post_idYesPlatform id of the user's post being replied under.
source_post_textYesText of that post (max 1000 characters).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark this as a non-readOnly, non-destructive, non-idempotent, open-world write. The description adds genuinely useful context beyond that: the output is only a pending draft and 'nothing is sent,' plus the plan prerequisite. It doesn't cover rate limits or auth scoping, keeping it below a 5.

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?

Three tight sentences, front-loaded with the action and immediately followed by the critical safety fact that nothing is sent. Zero filler.

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?

With no output schema, the description correctly explains the outcome (a draft saved as pending) and where to find it, and states the plan requirement. Minor gap: no indication of what the call returns (e.g., a draft id) for follow-up calls.

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 four parameters are already documented in the schema. The description implies voice/inbound-source semantics but adds no syntax, format, or length guidance beyond what the schema states, so the baseline 3 applies.

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 (draft), resource (a reply), and scope (in the user's trained voice, to an inbound comment/message on one of their posts). This clearly separates it from generate_persona_post and from reply_to_post, which presumably sends rather than drafts.

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 hard prerequisite ('Needs a plan with PersonaForge replies') and routes the review step to list_persona_replies. It does not explicitly say when to prefer this over the sibling reply_to_post, so it stops short of full when/when-not coverage.

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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