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asadhuddleduck

thread-storm

threads_publish_text

Send text posts to Threads and create threaded replies using an optional reply-to ID for sequential discussions.

Instructions

Publish a text post to Threads, optionally as a reply to another post.

Use reply_to_id to chain posts into a thread (each post replies to the previous one). Limit: 250 API-published posts per 24-hour window. Max 500 characters per post.

Args: text: The text content to publish. reply_to_id: Optional post ID to reply to (for building threads).

Returns: JSON string with the published post ID and permalink.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
reply_to_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses important behavioral traits: the 250-post daily limit, the 500-character maximum, and the reply-chaining semantics. It also notes the return value (post ID and permalink). While it does not mention authentication or error handling, the disclosed limits and reply behavior provide meaningful transparency.

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 well-structured and concise. It opens with a clear purpose, then provides usage guidance and limits, followed by parameter explanations and return value. Every sentence earns its place, with no redundant or vague wording.

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?

Given the tool's simplicity (2 parameters, one required, with an output schema), the description covers all necessary aspects: purpose, usage, limits, parameter semantics, and return value. The presence of an output schema means return details are optional, but including them adds completeness. It is sufficient for an agent to select and invoke the tool correctly.

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 description coverage is 0%, so the description must fully compensate. The Args section adds clear semantics: 'text: The text content to publish' and 'reply_to_id: Optional post ID to reply to (for building threads).' This goes beyond the bare property names and gives the agent the necessary context to set these parameters correctly.

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 first sentence clearly states the tool's function: 'Publish a text post to Threads, optionally as a reply to another post.' This is specific about the action, resource, and scope, and implicitly distinguishes it from sibling tools like threads_publish_thread by focusing on a single text post and reply functionality.

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 provides explicit guidance for using reply_to_id to chain posts into a thread, and mentions the 24-hour limit and 500-character cap, which helps set expectations. It does not explicitly contrast with threads_publish_thread, but the purpose statement and the reply chaining instruction give clear context for when to use this tool.

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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