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Get Post Auto Reply

get_post_auto_reply
Read-onlyIdempotent

[read] The comment auto reply settings of one post (<platform>_post_id or <platform>_post_uuid; yt: yt_video_id / yt_video_uuid). platform = ig|fb|tw|tt|yt|li|th. Returns {enabled: false} when none is set. Shape: {enabled, mode: MATCH|AI|MATCH_AI, once_per_user, rules: [{type: contains|exact|regex..., pattern, action: dm|reply|both, dm, reply}], fallback: {action, dm, reply}|null, ai: {provider, account, model, prompt, action, reply}}.

Input Schema

NameRequiredDescriptionDefault
post_idNo
platformYes
post_uuidNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds meaningful context beyond that by specifying the empty return shape and the full response structure for configured auto-replies.

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?

The description is compact and front-loaded: read marker, resource, scope, platform values, empty behavior, then response shape. Dense but every element serves selection or invocation.

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?

With no output schema, the description supplies the return shape and the important fallback when no auto-reply exists. Combined with annotations and the platform/ID guidance, it is complete enough for an agent to call the tool correctly.

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 coverage is 0%, so the description must carry parameter meaning. It does provide the platform enum and ID-style guidance, but it introduces `<platform>_post_id` and `yt_video_id`-style names that do not exactly match the schema's `post_id` / `post_uuid` fields and does not clarify post_id as integer versus post_uuid as string, leaving some ambiguity.

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 read operation on one post's comment auto-reply settings, with platform-specific ID variants and an explicit empty-state return. It is clearly distinguishable from account-level auto-reply siblings and from set/test auto-reply operations.

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 description clearly frames this as the read operation for a single post's auto-reply settings and notes the {enabled: false} behavior when no configuration exists. It does not explicitly name alternatives such as get_account_auto_reply, but the post-level scope makes the intended use clear.

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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