get_linkedin_publication_post_prompt

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

With no annotations, the description carries full burden. It discloses tone (professional but engaging), structure (includes CTA, hashtags), and target length (150-200 words). However, it does not specify output format (e.g., a string) or mention that it returns a prompt, not the post itself. The output schema exists but is not visible to the agent through the description alone.

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 concise (two short sentences) but sacrifices necessary information about parameters and output. It front-loads the purpose but lacks practical details for the agent. It could be restructured to include param hints without adding length.

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 5 required parameters with no schema descriptions, no annotations, and an output schema that is not described, the tool definition is incomplete. The agent lacks guidance on what to input and what the output looks like. The description only covers high-level purpose and tone.

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?

Schema description coverage is 0%, and the description does not mention or explain any of the 5 required parameters (paper_title, journal, key_message, clinical_significance, your_role). The agent must rely solely on parameter names, which may be ambiguous. This is a critical gap.

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 specifies a verb (generate) and resource (prompt to draft a LinkedIn post for a publication announcement). It distinguishes from sibling tools like get_author_invitation_email_prompt or get_slide_deck_outline_prompt by focusing on a LinkedIn post context.

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 implies the tool is for generating LinkedIn posts about publications but does not explicitly state when to use it versus alternatives like other prompt tools. No exclusion criteria or context are provided, leaving the agent to infer usage from the name and description.

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