compute-ledger__describe_agent

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only states 'self-description', implying a read operation but does not confirm safety, side effects, permissions, or output nature. This is insufficient for an agent to understand operational traits.

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 extremely concise (one short phrase), but conciseness should not sacrifice informativeness. It is not verbose, yet it could be restructured to better front-load key details; currently, it lacks substance.

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?

Given no output schema and low complexity, the description fails to clarify what information the self-description returns. An agent needs to know the response format or content to use the tool effectively, which is missing.

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 tool has zero parameters and 100% schema coverage. Per guidelines, 0 params sets a baseline of 4. The description adds no parameter info, which is acceptable since none exist, and the schema already communicates this.

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 'Fleet-standard self-description' is vague and jargon-heavy, not clearly stating what the tool does beyond the name 'describe_agent'. The bracket prefix provides module context but lacks specific verb-resource semantics, making it hard for an agent to understand the exact purpose.

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?

No guidance on when to use this tool versus the many other describe_agent siblings from different modules. The agent is left to infer based solely on the module name, with no exclusionary or contextual cues.

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