agiscorecard-web3-disclosures

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds significant behavioral detail: it does not verify reserves, issuer solvency, or redemption rights, and states that parameters are processed remotely without application persistence. This goes far beyond the structured metadata and clearly sets expectations about limitations.

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 reasonably structured, starting with the core purpose and moving to limitations and usage, but it contains redundancy: 'It does not verify reserves, issuer solvency or redemption rights' is largely repeated by 'No live asset feed, reserve audit, redemption verification, credit rating or investment recommendation'. This repetition could be trimmed for tighter prose.

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 complexity of 4 required parameters with arrays of objects, the description covers key aspects: how to obtain exact inputs via fetch/example, what the tool does and does not do, and remote processing without persistence. The presence of an output schema reduces the need to describe return values. It is complete enough for an agent to use correctly, with minor gaps around expected output shape being covered by the schema.

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 the schema already documents all parameters with descriptions. The tool description adds context about the before/after arrays being disclosure fields and mentions retaining units/dates/source references, but does not elaborate on individual parameters beyond that. This is adequate but does not significantly enhance the schema-level semantics.

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 a specific verb and resource: 'compares two sets of supplied asset disclosure fields while retaining units, dates and source references'. This distinguishes it from siblings like compare_compute_costs or reconcile_stablecoin_records, which target different domains. The scope is unambiguous.

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 implies usage by stating the tool compares asset disclosure fields and flags issues, but it does not explicitly state when to use this tool versus alternatives. It does advise 'Retrieve disclosures with fetch or read its example resource to obtain exact inputs', which is a practical prerequisite, but it lacks explicit exclusions or alternative routing compared to siblings.

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?

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds valuable behavioral context: bilingual (English and Chinese) name support, public scope, and the empty-query listing behavior. These details go beyond what annotations or schema provide without contradicting them.

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 clean sentences with no filler. The primary action is front-loaded, and the supporting usage details are kept minimal and relevant.

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 single-parameter search tool with annotations and an output schema, the description is complete: it defines the search scope, supported query forms, and the empty-query behavior. No essential information for invoking the tool 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 coverage is 0%, so the description carries the burden of explaining the query parameter. It clarifies that queries are names, that English and Chinese are accepted, and that an empty query has special meaning. It does not fully specify matching behavior (e.g., exact vs partial), but it compensates well for the schema gap.

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 a specific verb ('Search') and resource ('this server’s public AI/Web3 tools and citation pages'), making the tool’s function immediately clear. It is distinct from all sibling tools, which focus on checking permissions, comparing costs, or reading profiles rather than searching a corpus. The title and description align 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 clearly indicates when to use the tool: when searching for AI/Web3 tools or citation pages on this server. The note about empty query listing available worksheets provides a concrete usage scenario. It does not explicitly name alternatives or exclusion conditions, so it misses the top score.

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