delimit_social_post

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

With no annotations, the description fully bears the burden of behavioral disclosure. It discloses auto-trigger behavior, auto-generation of text, platform-specific tone rules, a daily limit of 2 posts, and the draft parameter. It is transparent about the tool's actions and constraints, though it does not detail error handling or response format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long and includes some repetition (e.g., 'IMPORTANT' sections). While the content is valuable, the structure could be more concise. However, the information is well-organized with clear sections for auto-trigger, categories, and platform rules.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, 3 platforms, auto-generation, drafts), the description covers most necessary context: why to post, how to craft content, platform rules, and limitations. With an output schema present (not seen), it need not explain return values. It is complete enough for an AI agent to use correctly.

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

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

The input schema has 100% description coverage, but the description adds substantial meaning beyond the schema. It explains categories (tip, changelog, etc.), provides detailed platform tone rules for Twitter, Reddit, and LinkedIn, and clarifies the 'context' parameter's purpose. This enhances the agent's understanding of how to use each parameter effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Post to social media' and distinguishes it from sibling tools like delimit_social_generate and delimit_social_approve by specifying the exact action (posting) and the auto-trigger rule for AI drafts. It provides detailed platform-specific tone rules, making the purpose unambiguous.

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

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

The description includes explicit usage guidelines: 'When the AI drafts a social post, it MUST call this tool immediately.' It also explains the approval flow and that the AI should not ask for confirmation. While it doesn't directly contrast with alternatives like delimit_social_generate, it provides clear context for when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.