get_object

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

Since annotations are absent, the description carries the full burden of behavioral disclosure. It does add value by explicitly noting that base64 payloads are omitted, which is a concrete behavioral trait. However, it does not mention whether the operation is read-only, any side effects, error conditions, or permission requirements, which are important for a tool without annotation support. This is a moderate disclosure but leaves significant gaps.

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 a single, front-loaded sentence that immediately states the core action and scope, then adds the key omission detail. There is zero fluff; every word earns its place, making it easy for an agent to parse and act on efficiently.

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 relatively simple get-by-id tool with full schema coverage and no output schema, the description adequately covers what is returned and what is omitted. It could be more complete by mentioning error handling or behavior when the object is not found, but given the low complexity, the current description is sufficient 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 description coverage is 100% – both objectId and captureId have descriptions in the input schema. The tool description does not add any additional parameter semantics beyond what the schema already provides, so it stays at the baseline score of 3 for high schema coverage.

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 verb ('Return'), the resource ('one GPU object record from a capture'), and specific context (descriptor, label, stacktrace), with base64 payloads omitted. It is specific and actionable, but does not explicitly differentiate itself from sibling tools like get_shader or get_draw_state, so it loses a point for missing cross-tool distinction.

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 when to use the tool: when you need a GPU object record from a capture, particularly its descriptor, label, and stacktrace. However, it does not explicitly state when to prefer this tool over alternatives (e.g., get_shader for shader-specific info), nor does it mention exclusions or prerequisites. The usage context is implied but not elaborated.

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