Free check before you pay: for every data tool, the content hash and validUntil of its current default result (all chains). If the hash matches what you already hold, nothing changed and there is nothing to buy. Optional name for one tool
| Name | Required | Description | Default |
|---|---|---|---|
| name | No |
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | ||
| tools | Yes | ||
| checkedAt | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries disclosure about it being free, returning a hash and expiry, and checking the current default result. This reasonably indicates a non-destructive query even though it does not discuss rate limits, errors, or indicators of mutation beyond '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 three sentences with no filler. It front-loads the core value, then gives the condition (hash match) and the optional parameter. Each sentence adds unique 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?
With an output schema present, the return value does not need description-level detail. The description sufficiently covers how the name parameter adjusts behavior (all vs. one tool), and it provides the check-before-pay use case. Nothing essential for calling it correctly 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 provides zero field descriptions, so the description must cover parameter meaning; it does by explaining the optional 'name' selects one tool, while omitting it covers every data tool. This gives the cardinality and optionality of the parameter, even if it does not enumerate accepted name values.
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 an action ('free check'), a target resource ('content hash and validUntil of ... default result'), and an all-chains scope. It is immediately differentiable from the buy/attest sibling tools because it positions itself as the pre-purchase freshness check.
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?
'Free check before you pay' tells the agent when to invoke this tool, and the hash-equality explanation shows when no purchase is needed. It stops short of explicitly naming alternatives, but the timing and decision context are clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but some overlap exists among report tools (situation_report, deep_report, market_state) and spec tools (attest_spec, proof_spec). These could confuse an agent selecting the most appropriate endpoint.
Tool names use consistent snake_case and are descriptive, but follow mixed patterns: verb_noun for actions (buy_key, list_attestations) and bare nouns or noun phrases for data endpoints (prices, congestion, wall_map). This is readable but not fully uniform.
With 26 tools, the set is heavy and covers multiple domains (attestation, market data, key management, webhooks). It sits just above the borderline for comfort, but the breadth is justifiable given the server's multi-purpose nature.
The tool surface provides full lifecycle coverage for attestation (create, read, verify), key management (buy, claim, status), and webhooks (register, status, unregister), plus a wide range of market data endpoints. There are no obvious gaps or dead ends.