generate_lead_magnet

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

The description discloses valuable behavioral traits beyond the schema: it streams NDJSON events in a specific sequence (validation → post → visual_spec → done) and returns a list of parsed events. With no annotations provided, this information is crucial for the agent to handle the output correctly.

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 two concise sentences, front-loaded with the primary purpose and followed by the streaming output behavior. Every sentence adds essential information without redundancy.

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?

The description provides a solid overview of the tool's purpose and output flow, which is adequate for a basic understanding. However, given the complexity of 14 parameters, nested objects, no output schema, and no annotations, it leaves gaps around required parameters, potential event types, and error conditions, making it only partially complete.

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 description mentions key input categories (outils, chiffre+source, type de preuve) that map to several parameters, providing some semantic context. However, schema coverage is only 36%, and the description does not compensate for all undocumented parameters, leaving many fields (e.g., audience, workshop_date, auto_dm_enabled) without contextual guidance.

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 generates a complete LinkedIn lead magnet (text post + visual_spec) from structured input, which is a specific action and resource. It distinguishes itself from siblings like render_visual and publish_lead_magnet by focusing on generation of content, not rendering or publishing.

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 this tool is for generating lead magnets, but provides no explicit guidance on when to use it versus alternatives like render_visual or publish_lead_magnet. The usage context is inferable but not directly stated.

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