Signal Sprint

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

With no annotations, the description carries the full burden. It discloses that the endpoint is paid, costs $0.005 USDC through x402, and does not return transaction bodies. This goes beyond a simple read-only hint, though it does not detail the exact response contents or rate limits.

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 two sentences with no fluff. It front-loads the main action, then efficiently adds cost and limitation details. Every sentence earns its place.

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?

Given the simplicity (one parameter, no output schema), the description is compact but leaves a gap: it says 'compact public metadata' without specifying what fields are included. Since there is no output schema, the agent cannot know if the response contains e.g. timestamp, block number, or transaction count, making it incomplete.

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 input schema already provides 100% coverage for blockHash with a clear description. The tool description adds no new parameter semantics beyond restating 'one Base block hash' and does not elaborate on format, validity, or examples, so it meets the baseline for schema coverage.

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 the action ('Return compact public metadata') and the target resource ('one Base block hash'), distinguishing it from siblings like gas price or USDC balance tools. It also explicitly notes what it does not return (transaction bodies), further clarifying its scope.

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 gives clear context: it is for a single block hash and is a paid endpoint, which informs when to use it. It provides a when-not by stating it does not return transaction bodies, but it does not explicitly name alternatives or state a preferred use case, so it falls short of a 5.

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, the description carries the full burden. It discloses the cost ($0.005 USDC via x402), the exact REST endpoint, and the inclusion of the block number—valuable behavioral traits that go beyond the schema. It does not mention rate limits or auth, but the cost and response detail are substantial.

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 two sentences that are front-loaded with the purpose and followed by relevant cost/endpoint details. Every clause adds value without redundancy.

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 simple zero-parameter getter with no output schema, the description sufficiently covers the action, response contents (wei, gwei, block number), and cost. It is complete for the tool's complexity and context.

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?

There are zero parameters, so the schema already covers all inputs. The description correctly avoids adding parameter details, adhering to the baseline of 4 for no parameter tools.

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 the verb 'Return' and the resource 'Base gas-price observation' with output units (wei and decimal gwei). It is distinct from siblings like 'block' or 'balance', so it differentiates well.

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 no explicit guidance on when to use this tool versus alternatives. It mentions it is a paid endpoint but does not name or compare with sibling tools, leaving usage context implicit.

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, the description carries the full burden of behavioral disclosure. It transparently reveals that the call is paid and specifies the cost, which is critical for an agent's decision-making. It also discloses that the endpoint returns the observed block number, giving insight into the response. It does not explicitly claim read-only, but the nature of a balance query implies it. It lacks mention of rate limits or error behaviors, but for a simple read operation, the disclosure is adequate.

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 extremely concise, consisting of exactly two sentences. The first sentence states the core function, and the second adds critical cost and response details. There is no extraneous text, redundancy, or padding. Every word earns its place, making it a model of efficient writing.

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?

Given the tool's simplicity (single parameter, no output schema), the description covers the essential context: purpose, cost, and a hint about the response (observed block number). It does not explicitly describe the balance amount format, but the absence of an output schema means the description should at least mention what is returned, which it does. The cost disclosure is a notable addition that makes the tool's usage expectations clearer. A small gap is that the relationship between the balance and block number is not fully elaborated, but overall it is sufficient for a straightforward balance checker.

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 input schema has 100% description coverage with a pattern and a clear description for the only parameter 'address'. The description does not add additional parameter semantics beyond what the schema provides; it reiterates that the address is on Base. The baseline of 3 applies because the schema already documents the parameter fully, and the description does not enrich it further.

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 the tool's function: 'Return the current USDC balance for an EVM address on Base.' This is a specific verb (return) + resource (USDC balance) + scope (Base network), and it differentiates from siblings like signal_sprint_base_block and signal_sprint_base_gas_price which target different data types on the same network.

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 practical usage context by noting the paid nature of the endpoint ($0.005 via x402) and the REST endpoint path, which helps an agent decide whether to incur cost. However, it does not explicitly state when to prefer this tool over alternatives or list exclusions. The sibling tools cover other Base data, so the purpose alone largely implies when to use it, but explicit guidance is missing.

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?

The description discloses that the call costs $1.00 USDC on Base through x402 and that it returns HTTP 402 before settlement. This transparently communicates the payment requirement and potential error response. There are no annotations to rely on, but the description itself covers key behavioral aspects such as cost and failure mode.

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 two sentences. The first sentence states the core purpose, and the second provides essential operational details (endpoint, cost, and 402 behavior). No unnecessary words or redundant information is included, making it efficient and well-structured.

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 description sufficiently covers the tool's purpose, input parameters, and operational constraints (cost, payment, and 402 response). While there is no output schema, the action of 'generating a bio' implies the return value. The absence of error handling details beyond 402 is a minor gap, but overall the description gives enough context for effective use.

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?

All parameters are described in the schema with meaningful descriptions: agentName ('Name of the AI agent.'), capabilities ('Two to six concise capabilities.'), tone ('Optional writing tone.'), and audience ('Optional intended audience.'). The descriptions clarify the purpose and constraints of each field, achieving full coverage of the schema.

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 the tool's purpose: 'Generate a concise professional profile bio for an AI agent.' It uses a specific verb ('generate') and identifies the target resource (an AI agent's bio). It is distinct from sibling tools which focus on blockchain data (block, gas price, USDC balance), so there is no ambiguity about what this tool does.

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 implicitly indicates usage—whenever a professional bio for an AI agent is needed—and provides implementation details (REST endpoint, payment method). However, it does not explicitly state alternative scenarios or contrast with sibling tools, though the sibling tools are clearly unrelated. The cost and payment requirement are mentioned, which helps set expectations for usage.

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