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Loudcode

draft_post

Write a build in public post for X about work the user just did, in their own voice (Loudcode knows their product, tone and past posts). Pass a concrete summary of what was built or changed in this session: features, fixes, decisions, numbers, and why it matters to users. Returns the draft (and alternatives). It is saved in Loudcode for the user to review; it is NOT posted.

Input Schema

NameRequiredDescriptionDefault
formatNosingle (default): one X post. thread: 3 to 5 posts. long: LinkedIn style.
summaryYesWhat was built or changed, and why it matters. Plain language, specific.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the output (draft plus alternatives), the persistence side effect ('saved in Loudcode for the user to review'), and the critical negative ('NOT posted'). It does not cover auth requirements or limits, but the safety-relevant behavior is explicit.

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 sentences, front-loaded with the action and scoped to the triggering situation, then the input guidance, then the return/no-publish contract. No 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?

For a 2-parameter draft tool with no output schema and no annotations, the description covers action, input expectations, return shape, and persistence. Minor gap: nothing about whether the draft is tied to the current session/user context or how the voice personalization is scoped.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3; the description earns more by unpacking what 'summary' should contain — features, fixes, decisions, numbers, and user impact — which is richer than the schema's 'Plain language, specific.' The 'format' parameter is left to the schema, which documents its enum fully.

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+resource+channel: 'Write a build in public post for X about work the user just did'. Clearly separable from siblings like list_drafts, queue_post, and post_metrics — it produces a draft, it doesn't post or 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 clear context for use ('about work the user just did' in this session) and implicitly rules out posting via 'it is NOT posted', which routes the agent toward queue_post for publishing. It stops short of naming an explicit alternative or exclusion.

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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