List C4D Entities

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the return format, kind-specific fields (is_active for take/material/render_data), the inline data-reading behavior of include_tags/include_params, and the shader-chain vs node-graph behavioral caveat. It stops short of explicitly stating read-only semantics and any result limits, but the return-shape and per-kind behavior disclosure goes well beyond the bare minimum.

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?

Four sentences, roughly 85 words, with zero filler. The core purpose and return shape are front-loaded, followed by the object-kind capabilities, then the usage ordering guidance, then the shader caveat. The example and the list_graph_nodes pointer each earn their place by preventing a likely mis-selection.

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?

This is an 11-parameter, kind-dependent tool with no output schema and no annotations, so the description has a heavy burden. It covers the return format, the most confusing behavioral trap (shader vs node-material), and the tool's role in the discovery workflow. The main gap is that the return-value disclosure is partial — fields are enumerated for only some kinds — but 100% schema coverage on parameters and the explicit shader caveat keep this complete enough for correct invocation.

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 coverage is 100%, so per-parameter documentation already exists, establishing a baseline of 3. The description adds genuine value beyond that by showing how parameters compose in a real query: 'all cubes with a Ttexture tag and their position in one call' demonstrates the combined use of type_ids, tag_types, and include_params. This composition insight is absent from the schema's individual parameter descriptions.

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 states a specific verb and resource ('Enumerate scene entities of a given kind') and immediately describes the return shape ('compact summaries (name, type_id, type_name, plus kind-specific fields...)'). It differentiates from siblings by name-dropping the closest alternative (list_graph_nodes) and clarifying that shader enumeration covers classical chains only, so an agent can distinguish this from list_graph_nodes and list_xpresso_nodes without opening any schema.

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 gives explicit sequencing guidance: 'Use this first to find what exists before describe/set_params.' It also names concrete alternatives with selection conditions — 'without falling back to exec_python' and 'for node-material graphs use list_graph_nodes.' This is exactly the when/alternative routing the dimension asks for, with nothing left to inference.

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