twitter_usage

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

Annotations already declare readOnly, idempotent, and openWorld hints. The description adds meaningful context beyond that, including the required auth header (X_BEARER_TOKEN) and the exact return shape, and frames the tool as a pre-flight quota check.

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 compact and well-structured: a purpose/action line, a return shape line, and an auth line. Every sentence carries useful information with no filler or redundancy.

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?

With no output schema, the description's explicit return shape is essential and provided. Auth requirements and usage context are also included. Minor edge cases like behavior when the cap is exceeded are not discussed, but complexity is low and annotations cover safety aspects.

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% and both parameters (days, usage_fields) already have descriptions, so the description doesn't need to repeat them. The Returns line gives useful field-level context, but no additional parameter-specific semantics are needed beyond the schema.

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 it retrieves the project's post-read usage against its monthly cap, and the imperative 'check before burning quota' reinforces the tool's purpose. This is distinct from sibling Twitter data tools like twitter_tweets or twitter_search_recent, which fetch content rather than usage metrics.

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?

'Check before burning quota' provides direct guidance on when to use the tool: before consuming API quota. It does not explicitly name alternatives or exclusions, but the tool's purpose naturally separates it from data-fetching siblings.

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