prospect_research_render_prospect_html

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

No annotations provided, so description must carry the burden. It discloses deterministic rendering and no LLM use, but does not cover error handling, input validation, or side effects like whether it modifies state. This is adequate but not exhaustive.

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?

A single sentence that is front-loaded with the main action and key attributes (email-compatible HTML, Jinja2, no LLM). Every word adds value; no 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?

For a simple tool with two parameters and no output schema, the description adequately covers the render function, output format, and efficiency. Could mention expected input format (JSON from Research Prospect) but is otherwise 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?

Schema description coverage is 100%, so the schema already documents both parameters (prospect_research and output_variable_name). The description adds minimal extra meaning beyond what the schema provides, meeting the baseline.

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 uses a specific verb ('Renders') and resource ('Prospect Intelligence Brief as professional email-compatible HTML'), clearly distinguishing it from other render tools by specifying the output format and technology (Jinja2 templates).

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?

Provides context ('No LLM required — fast deterministic rendering') but lacks explicit guidance on when to use this tool versus similar rendering tools among siblings, such as competitive_brief_render_brief_html or company_research_v2_render_html.

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