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

Annotations declare readOnlyHint=false and idempotentHint=false, which would otherwise look wrong for a pure compute tool; the description explains exactly why, citing the per-call $0.001 x402/USDC charge, the prepaid-credit/API-key path, and that failed calls are never charged. That is high-value context beyond the structured fields.

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 core purpose is front-loaded in the first sentence, with usage and then payment mechanics following. The payment passage is long but earns its place by justifying the surprising annotation combination; only minor tightening is possible.

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 two-parameter, no-output-schema tool, the description covers purpose, the plus flag, usage context, cost model, and charge semantics. It does not state the return shape, though that is largely implied by "decode ... text."

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%, so both parameters are already documented, including "true to read + as space" for plus. The description adds only the form-encoding framing, which is marginal beyond the schema, so the baseline 3 applies.

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?

States a precise verb+resource (decode percent-encoded text) and immediately names the sibling it opposes in spirit, url_encode, by implication. The plus/form-encoding qualifier scopes it further so an agent can distinguish it from url_parse and other URL siblings.

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?

"Use to read encoded links and form data" gives an implied usage context but names no alternative and states no exclusions. An agent can infer decode-vs-encode, but the description never explicitly routes to url_encode for the inverse operation.

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