hub_usage_add

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

The description discloses important behavioral traits: reported values are tagged as SUPPLIED and never mixed with hub-measured data, and an empty entry records a $0 session. With no annotations provided, this detail is valuable.

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?

Two sentences, front-loaded with the action and resource, every sentence adds meaningful information. No fluff.

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 the core purpose and key semantics, but for a tool with 8 parameters and no output schema, it lacks details on return values and full parameter meanings. It's adequate but has clear gaps.

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 description names some parameters (seconds, tokens, cost, model) and adds a cross-field constraint, but it doesn't explain all eight parameters or the tokensIn/tokensOut distinction. Given 0% schema coverage, this is incomplete.

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 tool's function: recording usage metrics (seconds, tokens, cost, model) that only the user can observe. It distinguishes itself from sibling tools by emphasizing that data is supplied explicitly because the hub cannot measure it.

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?

It provides context for when to use the tool—whenever you have usage data the hub cannot observe—and includes a validation rule (at least one number required). However, it doesn't explicitly name alternatives or exclusions, so it earns a 4 rather than a 5.

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