Bizmoon

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

Beyond the readOnly/idempotent/openWorld annotations, it adds a 90-day coverage window, a 25-result-per-call cap, and newest-first ordering. The 25-result cap is a useful rate-limit disclosure even though it sits oddly with the schema's `limit` maximum of 50; it does not contradict the annotations.

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?

Three sentences, front-loaded with the core behavior, followed by the intended usage pattern and hard limits. No filler or repeated schema text.

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 read-only paged list endpoint, it covers the key operational details: time window, result cap, ordering, jurisdiction option, and the recurring-agent cursor flow. It relies on the schema for offset/limit mechanics, which is acceptable, and the only notable gap is the unresolved 25-vs-50 limit discrepancy.

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?

Since the input schema already documents all four parameters at 100% coverage, the baseline is 3. The description earns a 4 by giving `since` cursor semantics (store newest publishedDate and pass it back) and warning of the effective 25-result cap beyond the schema's limit bounds.

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 names a concrete resource (regulatory changes), a specific operation (everything published since a given date), an optional jurisdiction filter, and an ordering (newest first). The `since`-cursor framing makes it easy to tell apart from the sibling `search_regulatory_changes` without opening schemas.

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?

It explicitly says this is for scheduled or recurring agents and prescribes the exact cursor pattern: store the newest publishedDate and pass it back as `since`. It doesn't name the alternative search tool or state when not to use it, so it stops 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?

Annotations already cover read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds value by specifying the exact content returned (AI summary, full description, canonical URL) and the citation purpose, going beyond annotation coverage.

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 a single, well-structured sentence. It front-loads the action and then lists all returned fields without unnecessary detail, making it efficient and easy to scan.

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 fetch-by-id tool, the description is complete: it lists all returned fields, includes a specific use case (citation), and the schema covers parameter semantics. The absence of an output schema is mitigated by the field enumeration in the description.

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 is only one parameter, id, and the schema provides full coverage, including its provenance from search tools. The description adds no additional meaning beyond what the schema already offers, so 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 action (fetch one document by id) and lists the specific fields returned. It distinguishes from siblings implicitly by focusing on retrieval of a single item using an id, but does not explicitly name alternatives.

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 for retrieving a specific document when the id is known, and the schema adds that the id comes from search_regulatory_changes or changes_since. It does not explicitly state when not to use other tools, but the context is clear enough for an agent.

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 declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, which are comprehensive for a read-only list operation. The description adds the meaning of the returned data (publication date, last checked), but since there is no output schema, this is valuable. No contradictions.

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?

One sentence, concise, and front-loaded with the action ('List every jurisdiction') and the output details. The usage hint is at the end, but the sentence is short and focused. No fluff.

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 zero-parameter tool with rich annotations (read-only, open world, idempotent), the description fully covers what the tool does and when to use it. The output schema is absent, but the description lists the key fields, so an agent knows what to expect. The complexity is low, so nothing 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?

The tool has zero parameters, so the description doesn't need to explain any. The description adds contextual meaning about what the list contains and its purpose, which is beyond the empty schema. This 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 verb 'list' and the resource 'jurisdictions and official registers', and specifies the key output fields (publication date, last checked time). It also explicitly says 'Call this first to learn coverage and freshness', which distinguishes it from the sibling tools that deal with changes and funding 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?

The description explicitly instructs the agent to call this tool first to learn coverage and freshness, which is a clear usage directive. It doesn't explicitly mention alternatives, but the siblings (changes_since, get_regulatory_change, search_funding_programs, search_regulatory_changes) are implicitly different, so the purpose is unambiguous.

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 cover read-only, idempotent, and non-destructive behavior. The description adds a useful 90-day coverage window, but it claims 'up to 25 results per call' while the input schema allows a maximum of 50 and a default of 20. This inconsistency misleads the agent about the actual limit and undermines the 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 three sentences and front-loads the purpose and sources. It is concise overall, but the incorrect limit claim is a minor structural flaw that forces the agent to reconcile conflicting information with the schema.

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 search tool with 7 optional parameters and no output schema, the description provides key context: sources, date window, and result contents. The limit inconsistency is a gap, but pagination and defaults are covered by the schema, so the description is otherwise sufficient.

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%, so the schema already documents all seven parameters. The description mentions keyword, jurisdiction, agency, and date, which maps to existing parameters, but it adds no new semantic detail beyond what the schema provides. The baseline of 3 applies.

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'), a clear resource ('federal and state grant and incentive programs'), and explicitly names the data sources (grants.gov plus state economic development agencies) and the filtering dimensions (keyword, jurisdiction, agency, date). This fully distinguishes it from the sibling tools, which are about regulatory changes, making the tool's scope 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 provides clear context that this tool is for grants/funding programs while siblings are for regulatory changes, so an agent can infer when to use it. However, it does not explicitly name alternatives or state when not to use it, stopping short of full when/when-not guidance.

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 provide readOnly/openWorld/idempotent/non-destructive hints. The description adds useful behavior beyond those: funding exclusion, sort order, citation URLs, 90-day window, and result cap. However, the 'up to 25 results per call' claim conflicts with the schema's limit maximum of 50, which is a notable inconsistency.

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?

Four sentences, front-loaded with purpose, then usage routing, then behavioral details. No fluff, but the 'up to 25 results' statement is concise yet contradicts the schema, so it loses a point for misleading precision.

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 8 parameters, no required fields, and no output schema, the description covers scope, exclusion behavior, result contents (AI summaries, agencies, effective dates, citation URL), sort order, time window, and result cap. Pagination is not described, but the schema covers offset and limit, so completeness is solid.

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%, so the baseline is 3. The description adds some global behavioral context (category exclusion, time window) but does not add parameter-specific semantics beyond what the schema already documents. It matches the baseline expectation.

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 states a specific verb ('Search') and resource ('US federal and state regulatory documents') with clear scope, and explicitly contrasts with search_funding_programs by excluding funding unless category is specified. An agent can distinguish this tool from siblings immediately.

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?

Explicitly states when not to use this tool ('Funding opportunities are excluded unless you pass category "funding"') and routes to the alternative ('use search_funding_programs'). Also adds practical constraints like the 90-day coverage and result limit, helping selection decisions.

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