data-access

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

With no annotations, the description effectively discloses behavioral aspects: it is a read-only retrieval of metadata, explains the meaning of tiers ('golden' vs 'abstract'), and lists output fields. No side effects or destructive actions are mentioned, which is appropriate.

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, using two sentences to convey the purpose, output fields, and tier definitions. It is front-loaded with the key function, but the tier explanation could be slightly more 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?

Given the simple single-parameter tool with no output schema, the description adequately explains the return values (fields and tiers). It does not address error handling, but complexity is low, and the description provides sufficient context for an agent to use the tool correctly.

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% and already states 'a ref from search_programs'. The description adds 'state or program ref' but does not provide additional meaning beyond the schema's example. Baseline 3 is appropriate.

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 returns 'primary-document shelf metadata' for a state or program ref, listing specific fields (title, kind, publication date, source URL, sealed hash) and explaining the tier system. This distinguishes it from siblings like 'get_state_profile' (state info) and 'search_programs' (refs).

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 when document metadata for a known ref is needed, but does not explicitly state when to use this tool versus alternatives or exclude cases. No when-not or alternative tool references are provided.

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 explains behavioral traits: response_format controls output details and tier indicates data verification level. However, it does not disclose error behavior, permissions, or whether the operation is read-only (though implied).

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 concise sentences with no redundant information. Key details are front-loaded in the first sentence, making it easy to parse.

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 no output schema, the description covers the main output components and variations, but lacks details on error handling, default response_format, and a structured output format overview.

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 description adds meaning beyond the input schema for response_format by specifying that 'detailed' adds officials and primary-document shelf, and explains the significance of tier values. For the state parameter, schema already provides description.

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 retrieves a state's RHTP profile listing award, lead agency, and initiative summaries. It distinguishes from sibling tools like get_document and get_subinitiative_ledger by focusing on the state-level profile.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention contexts where another sibling tool would be more appropriate, nor does it specify when not to use it.

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 provided, the description must disclose behavioral traits. It mentions the data semantics (golden vs abstract tiers) but does not state whether the operation is read-only, requires authentication, or handles pagination (despite a cursor parameter). This is minimal behavioral disclosure.

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 at two sentences, with the first stating the core purpose and the second explaining tier terminology. While efficient, it could benefit from slightly more structure (e.g., listing key parameters), but earns a 4 for being well above minimal verbosity.

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 tool with 3 parameters, no annotations, and no output schema, the description provides adequate high-level understanding of what data is returned. However, it lacks information on pagination, parameter details, and behavioral aspects, leaving gaps for effective usage.

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 3 parameters with only 33% description coverage (only tag has a description). The tool description adds no details about parameters, such as the meaning of 'state' or how 'cursor' works. It fails to compensate for the low 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 tool returns a funded sub-initiative ledger for a state, detailing what it contains (who is funded, with dollars and RFA timing) and explains the two tiers (golden and abstract). This is a specific verb-resource combination that implicitly distinguishes from sibling tools like get_document or get_state_profile.

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 does not provide any when-to-use or when-not-to-use guidance relative to sibling tools such as search_programs or list_live_deadlines. It only describes what the tool returns, leaving the agent to infer appropriate usage context.

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?

No annotations are provided, so the description carries full burden. It does disclose tier meanings (golden vs abstract) and their verification implications. However, it does not mention operational traits like data freshness, pagination, or whether the operation is read-only.

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?

Two sentences with no filler. The first sentence states the core purpose immediately, and the second adds valuable detail about tiers. 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?

The description explains the purpose and tier system adequately for a simple list tool with two parameters and no output schema. However, it could mention expected return format or ordering, especially given the lack of an output 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 description coverage is 50% (only 'before' has a description). The tool description adds context that states filter by 'entitled states and programs', which supplements the schema. However, it does not elaborate on the 'before' parameter beyond what the schema already provides.

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 it lists 'open/closing solicitations and key dates' across entitled states and programs, with a specific verb 'list' implied and a defined scope. It distinguishes from sibling tools like get_document or get_state_profile by focusing on deadlines and solicitations.

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?

No explicit guidance on when to use this tool versus siblings like search_programs or verify_seal. The description implies usage for deadlines but lacks when-not-to-use or alternative tool recommendations.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the return format ('ranked stubs with refs') and tier meaning, but does not mention pagination behavior (cursor parameter), rate limits, or authentication needs. For a search tool, this is adequate but not rich.

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 with three sentences: first defines purpose and scope, second describes output, third explains result tiers. No redundant words or fluff. Every sentence adds value.

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 absence of an output schema, the description does not detail the structure of a 'stub', result count limits, or error handling. It mentions cursor pagination implicitly but does not explain it. For a search tool with three parameters, it is moderately complete but missing some 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?

Schema description coverage is only 33% (only 'query' has a description). The tool description adds general meaning for 'query' (keywords), but does not explain 'kind' (enum of types, partially listed) or 'cursor' (pagination). With low coverage, the description should compensate, but it fails to clarify these parameters, leaving ambiguity.

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 searches a verified federal-funding corpus across multiple document types (states, initiatives, sub-initiatives, programs) by keywords, and returns ranked stubs. This is specific and distinguishes it from sibling tools like get_document which retrieve a single document, or get_state_profile which focuses on a specific state.

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 context on result tiers and their reliability (golden vs abstract), guiding the agent on how to interpret results. It does not explicitly state when to avoid this tool or contrast with alternatives, but the sibling list implies search is for discovery while get_document is for retrieval. The added tier guidance is valuable but not exhaustive.

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?

No annotations provided, so description carries full burden. It describes the verification steps (recompute hash, check manifest/signature) and notes that verification is free. This gives a good sense of behavior, though it doesn't mention failure modes 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?

Two sentences, no redundancy. First sentence describes the core function, second explains the optional parameter. Every word contributes meaning.

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?

While the description covers what the tool does, it lacks information about the return value or output format, which would be helpful for a verification tool. Since no output schema exists, the description could have addressed this.

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?

Input schema has 100% coverage with descriptions for both parameters. Description adds value by explaining the optional parameter's role ('Pass sha3_256 to attest a copy you hold'), which enhances understanding beyond 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?

Description clearly states 'Cryptographically verify an artifact' and details the steps: recompute SHA3-256, check manifest and Ed25519 signature. The verb 'verify' and resource 'artifact' are specific, and the tool is distinct from siblings like get_document or search_programs.

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?

Description indicates usage for verifying an artifact's cryptographic integrity. It mentions passing sha3_256 to attest a copy you hold, providing context. However, it does not explicitly state when not to use this tool or suggest alternatives, but the purpose is clear enough.

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