neurogenesis__compute_efficiency_report

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

No annotations are provided, so the description carries the full burden. It calls itself a 'Free read', implying it is read-only, but does not elaborate on side effects, authorization needs, or performance implications. The abstract physics framing adds little practical behavioral context.

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 verbose and cluttered with jargon and brackets. It is not concise or front-loaded; key information is buried in a dense, metaphorical phrase.

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 the simple schema (one optional parameter) and no output schema, the description should clearly specify the output structure and scope. It mentions some elements (counts, costs, reasons) but lacks concrete details, leaving the agent guessing about the actual return format and semantics.

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 only parameter 'limit' is not mentioned or explained in the description. With 0% schema coverage, the description should compensate by describing what 'limit' controls, but it fails to do so.

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 it returns a 'routing decision log' with counts, costs, and reasons, which gives a general sense of purpose. However, the heavy use of jargon ('Landauer-floor physics context', 'Intelligence Bound frame') obscures the exact functionality and output, making it less clear than it could be.

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 alternatives like 'compute-ledger__list_inventories' or other neurogenesis tools. There is no explicit context for when it is appropriate 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.