Point-in-time historical price: what did a token cost at a past date/timestamp? Send { coin, when }. Essential for backtesting, accounting, and audits. [x402 paid tool — price $0.005; POST /api/analytics/price-at]
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes | Symbol (ETH), coingecko:id, or chain:0xaddress | |
| when | No | Unix timestamp or ISO date; default now |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral transparency. It discloses that the tool is paid (x402) and the endpoint. However, it does not mention data freshness, error behavior for invalid inputs, rate limits, or other behavioral traits. Given the lack of annotations, the description is insufficient.
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 concise, consisting of a single clear sentence and a note with cost and endpoint. It conveys the core purpose efficiently. While there is minor redundancy, it is well-structured and easy to parse. The presence of extra details (cost/endpoint) slightly reduces conciseness but remains appropriate.
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?
The tool is simple with two parameters and no output schema. The description explains the purpose and basic input. However, it omits details about output format, error cases, and data availability. Given the low complexity, the description is adequate but could be more complete with expected behavior and return structure.
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 for parameters is 100%, with detailed descriptions for each parameter. The description repeats the parameter names ('Send { coin, when }') but adds little beyond what the schema provides. It does not clarify formats or constraints further. Therefore, the description adds minimal semantic value, earning a baseline score of 3.
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 states the tool's purpose clearly: retrieving a historical price at a specific point in time. The verb 'get' is implied, and the resource is specified as token price at a past date/timestamp. The mention of use cases (backtesting, accounting, audits) reinforces the purpose. However, it does not explicitly differentiate from siblings like crypto_price or analytics_ohlcv, though the context implies it's for historical point data.
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?
The description provides usage context by listing use cases (backtesting, accounting, audits) and includes a cost note. However, it offers no explicit guidance on when not to use this tool or alternatives. The context is sufficient to infer appropriate usage but lacks exclusionary guidance.
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.
Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.
All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.
With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.
The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.