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

The description richly discloses behavioral details beyond the annotations: a cost model (1 credit per completed http/mcp/assert check), an idempotency rule (save one request_key per operation and reuse on retry), a spending safeguard (max_coins is your explicit spending cap), charging logic (broken targets and failed assertions still charge; invalid requests and worker failures cost zero), and replay semantics (replays return a privacy-safe receipt without rechecking or recharging). This is exceptional behavioral disclosure for a paid operation.

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 text is dense but every clause delivers actionable information: pricing, idempotency, spending cap, charging rules, and replay behavior. It is front-loaded with the core cost model, though the multi-idea packing makes it slightly heavy.

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 paid, open-world diagnostic, the description covers cost model, idempotency, spending controls, failure-charge rules, and replay semantics, and an output schema exists to explain returns. The main missing piece is parameter-level detail for url, kind, and expect, given the 0% schema coverage.

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 0%, so the description must carry the parameter burden. It meaningfully explains request_key (save one per operation, reuse on retry), max_coins (spending cap), and api_key context, and implies the assert check relates to 'expect'. However, the url and kind parameters and the expect object structure are never explained, leaving gaps.

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 is an opt-in diagnostic using utility credits that performs http/mcp/assert checks. This is a specific verb+resource, and the credit/billing angle distinguishes it from the free diagnose_http or diagnose_mcp siblings. Without naming those alternatives directly, sibling differentiation remains implicit, keeping this a 4.

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?

Usage is implied by 'Opt-in diagnostic' and 'Read pricing first', but there are no explicit when-to-use or when-not-to-use instructions versus the many diagnostic siblings (diagnose_http, diagnose_mcp, assert_healthy, run_autonet_sandbox). The agent gets context but must infer which diagnostic tool fits which situation.

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