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Delimit Social Generate

delimit_social_generate
Read-onlyIdempotent

Generate a social media post draft for review before manual or automated publishing. Choose from tip, changelog, insight, or engagement categories to create a read-only draft without posting.

Instructions

Generate a social media post draft (no posting) (Pro).

When to use: to draft a tweet for review before manual or automated posting. When NOT to use: to actually publish (use delimit_social_post or delimit_content_publish) or to manage targets (delimit_social_target_config).

Sibling contrast: delimit_social_post publishes a draft; this only generates one.

Side effects: read-only / draft. Calls ai.social.generate_post.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoPost category — "tip" (default), "changelog", "insight", or "engagement".tip

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv4.7.9
    • addedInput schema / properties / category / description
      Added value: +"Post category — \"tip\" (default), \"changelog\", \"insight\", or \"engagement\"."
  2. Addedv4.5.5

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context beyond that: it only creates a draft, never publishes, and calls ai.social.generate_post. This meaningfully supplements the annotations without contradicting them.

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, well-structured, and front-loaded with the core purpose before diving into usage guidance. Every sentence provides useful information with no redundancy.

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?

The tool is simple, has only one optional parameter, and has an output schema. Annotations cover safety semantics, and the description covers purpose, usage boundaries, sibling contrast, and side effects. Nothing critical is missing for an agent to invoke it 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 description coverage is 100%, and the single optional category parameter is already fully documented in the schema. The description does not add parameter-level detail, but it does not need to because the schema carries the weight.

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 generates a social media post draft without posting, which is a specific verb and resource. It also distinguishes itself from delimit_social_post and delimit_content_publish, so an agent can tell them apart immediately.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use it (drafting a tweet for review) and when NOT to use it (publishing, managing targets), and names the alternative tools. This leaves no ambiguity about tool selection.

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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