render_single_view

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

With no annotations provided, the description carries the full burden. It explicitly discloses that the tool returns a dict rather than a string, details the Pydantic validation failure that motivated this behavior, mentions server-side return behavior and error fallback, and explains the environment-specific fork redirect and consent token mechanism. This is rich behavioral context beyond the schema.

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 front-loaded with an IMPORTANT block but is verbose and includes an exact Pydantic error message and a reference to _render_policy.py. Every sentence adds some technical detail, but the structure is dense and could be more concise by separating critical usage notes from implementation details.

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 covers output type, error behavior, and consent token requirements, and mentions that the result dict contains 'renderer / image_path / size_bytes / etc.' However, it lacks parameter semantics and clear usage boundaries relative to sibling render tools. For a 6-parameter tool with no annotations and no output schema, this is 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 schema has 0% description coverage, so the description must compensate, but it only indirectly explains karma_engine and consent_token. It does not describe rotation, render_path, orthographic, render_engine, or the meaning of their defaults. Though parameter names are somewhat self-explanatory, the lack of any schema descriptions or clarification leaves a significant 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 states "Render a single view inside Houdini and return a structured result dict." This gives a specific verb (render), resource (a single view inside Houdini), and output type. It distinguishes from siblings like render_quad_views by emphasizing "single view," though it does not explicitly name alternatives.

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 IMPORTANT block provides usage context for specific environments: on machines lacking OGL 3.3, the opengl renderer redirects to capture_pane_screenshot, and karma_cpu/karma_xpu renderers require a consent_token obtained from the first call's _interrupt field. However, it does not explicitly say when to prefer this tool over sibling render tools or when not to use it.

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