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

No annotations are provided, so the description carries the full burden, and it does: free and read-only, payment detection reads Base USDC transfer logs, detection can lag the chain by minutes, and unpaid orders expire. These are exactly the behavioral facts an agent needs to avoid misinterpreting a pending order as a failure.

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?

Front-loaded with the most important qualifiers ('FREE, read-only') followed by status semantics and then caveats. It is dense but nearly every sentence carries operational value; the status-value enumeration is slightly list-like but not wasteful.

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 one-parameter polling tool with no output schema, the description supplies the return-state vocabulary (pending_payment, paid: true, delivered), the delivery channel (emailed report), and timing caveats. Nothing an agent needs in order to call it and interpret the result is missing.

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 the single order_id parameter already documents its origin and format with a pattern and example. The description reinforces that the id comes from order_endpoint_audit but adds no syntax or validation meaning beyond the schema, so the baseline of 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 specific verb and resource: poll the status of an audit order. It also anchors the resource to its origin ('created with order_endpoint_audit'), which cleanly separates it from the sibling that creates orders and from get_network_decomposition.

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?

Gives explicit operational guidance: poll after paying, wait 2-5 minutes before assuming a problem, and expect unpaid orders to expire within 24h. It also names the creating tool, so an agent knows the sequence of calls without inference.

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

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

With no annotations supplied, the description carries the full burden and does so: it declares read-only and free access, explains the integrity mechanism (SHA-256 seal recomputed locally with the recipe in the response), and discloses two real limitations — roughly daily refresh and ~1h ingest lag. This is exactly the behavioral context an agent needs before quoting numbers.

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?

Front-loaded with access mode and subject, then the decomposition, then the return fields, then caveats — a logical order with no filler sentences. Some phrasing ("Integrity-sealed," "independent ledger") leans promotional, but each clause still conveys usable information.

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 zero-parameter tool with no output schema and no annotations, the description covers access mode, data provenance, what is returned, how to verify integrity, and the freshness caveats. Nothing an agent needs in order to call it or to interpret the result is missing.

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 tool takes zero parameters, so there is no parameter meaning to add and the baseline applies. The description instead spends its space on return-value semantics (seal_verified, data_age_hours), which is a sensible use of the budget for a no-arg tool.

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 names a specific resource and a specific analytical output: a decomposition of x402 payment growth on Base split into wash/self-dealing/clone-fleet vs bundler plumbing vs organic core. That is far more precise than the title alone, and it is clearly distinguishable from the sibling audit/order-status tools.

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 gives an explicit trigger: "Use this BEFORE trusting any headline x402 volume figure," which tells the agent exactly when to reach for it. It stops short of naming alternatives or stating when NOT to use it, but the caveats section supplies the boundary conditions (stale data, recent-hour under-representation).

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

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

With no annotations supplied, the description carries the full behavioral burden and does so: calling the tool is free and moves no funds, it returns an HTTP 402 exact-scheme challenge with a per-order unique USDC amount on Base, the purchase only completes on payment of the exact unrounded amount, and orders expire within 24h. The double-payment hazard and the timeout-recovery procedure are both disclosed, which is exactly the context annotations would otherwise have to supply.

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 information is front-loaded: cost and non-charge guarantee come before the mechanics, and the operational warnings close it out. It is dense but nearly every sentence carries a distinct fact (price, no-charge, return shape, unique amount, expiration, polling, no double-pay), with only mild repetition between the COST label and the later 'real $399 purchase' sentence.

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?

There is no output schema and no annotations, so the description must explain both the response and the safety profile, and it does: it names the returned 402 challenge, the unique amount, the plain-language instructions, and the order id. Combined with the payment and polling lifecycle, an agent has everything needed to invoke this correctly and safely.

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 100%, so both parameters (target and email) are already documented in the schema, including that target may be a URL or a wallet address. The description adds only marginal meaning beyond that, mainly the 48-business-hour delivery window tied to the email parameter. Baseline 3 applies since the schema does the heavy lifting.

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 opens with a concrete verb and artifact: "Creates a PAYABLE ORDER for a $399 signed, human-reviewed audit of an x402 endpoint or receiving wallet." It names the deliverable, the audited dimensions, the price, and the delivery channel, which lets an agent separate it instantly from the sibling get_audit_order_status (status polling) and get_network_decomposition.

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 states explicitly when to call (to buy the audit), when not to worry (unpaid orders are harmless and expire in 24h), and the exact follow-up sequence: pay the quoted amount, then poll get_audit_order_status with the order id, and poll before re-paying if a submission times out. It also flags the operator-confirmation condition for spend policies, which is the one real prerequisite for this tool.

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