Verify a Company

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful context beyond annotations: the operation must be completed, and the call is free with no key required.

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 tight sentence plus a bracket note. Every element earns its place, and the core purpose is front-loaded before the access note.

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 retrieval tool with strong annotations, the description is mostly complete: it identifies what to pass, when it is valid, and the access requirements. It does not describe the return shape, but no output schema exists and the resource name 'OutcomeReceipt' is reasonably self-descriptive.

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% and the schema only says operation_id is a required string. The description adds context by tying operation_id to the completed operation whose OutcomeReceipt is requested, but it does not specify where the ID comes from or its format.

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?

States a specific verb ('Retrieve') and a specific resource ('final OutcomeReceipt') for a 'completed operation'. This clearly distinguishes it from siblings like get_status, which would naturally map to intermediate status rather than the final receipt.

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: this is for retrieving the outcome only after an operation has completed. It does not explicitly name alternatives or exclusions, but the completed-operation condition is a meaningful usage signal.

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, idempotentHint, and non-destructive behavior, so the description only needs to add context. It adds that the operation is free, requires no API key, and applies to in-flight async operations, which provides useful behavioral context beyond 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?

The description is compact and front-loaded. The primary purpose is stated in one clear sentence, and the cost/auth note is appended succinctly. Every element 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?

For a simple, one-parameter, read-only status tool, the description provides enough to call it correctly: the target resource, the identifier, and the cost/auth constraints. It does not detail the output shape or possible statuses, and it does not explain what happens if the operation is not in-flight, but these are not critical for a basic status query given the annotations.

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 only specifies 'operation_id' as a string with no description, so the description carries the semantic burden. It clarifies that operation_id references an in-flight async operation and that the tool queries its state, which gives the parameter meaningful context. It could be stronger by explaining how to obtain the operation_id, but it is adequate.

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 specifies a verb ('Query'), a resource ('the current state of any in-flight async operation'), and the key identifier ('operation_id'). It also implicitly differentiates from the sibling 'get_outcome' by focusing on in-flight operations rather than completed outcomes.

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: use this when you need the current state of an in-flight operation identified by operation_id. It also notes the operation is free and requires no key. It does not explicitly mention exclusions or alternatives, but the usage context 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description adds value by mentioning 'Zero upstream cost, no key required' and the data coverage range (2020-2026). It also specifies the sorting behavior (by dollar amount), which is useful beyond 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?

The description is compact, front-loaded with the core action, and each sentence adds relevant information (API source, output fields, cost, key requirement, data range). No wasted words.

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 2-parameter read-only tool with no output schema, the description covers the essentials: what it returns, the data source, and constraints. It does not cover error handling or pagination, but these are minor for this use case and annotations already cover the safety profile.

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 parameters are already documented. The description adds minimal extra meaning, only reiterating the sorting by award amount for max_results and the search intent for company_name. This is within the baseline for full 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 states a clear verb ('Search') and resource ('US federal contract awards by company name') and lists the specific output fields. It is distinct from the sibling tools (which appear unrelated to contract lookup) and leaves no ambiguity about what the 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 clearly conveys when to use the tool (for US federal contract awards by company) and implicitly that it is for read-only lookups. However, it does not explicitly name alternatives or state when not to use it, but given the sibling tools are unrelated, the context is sufficient.

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 readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral context beyond that: it returns exact prices when fixed, min/max ranges when variable, does not promise accuracy, and requires no API key ('[free, no key]'). No contradiction with 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 focused sentences with no filler. The first sentence front-loads the core purpose, the second explains the exact-vs-range behavior, and the third adds a crucial caveat plus auth note. 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 covers what the tool returns, how pricing varies, and the free/no-key requirement. With no output schema, the return-value description is useful and mostly sufficient. Minor gaps remain around expected operation naming and the exact output shape, but the tool is simple enough that this is not a major deficiency.

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 schema documents params as 'the same request body you would pass to the operation,' and the description reinforces the 'proposed call' idea. However, the operation parameter is only a bare string with no allowed values or format, and the description does not elaborate on how operations are specified. Schema coverage is exactly 50%, so the description only partially compensates.

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 specific verb ('Return') and a precise resource: cost, latency, and success-probability estimates for a proposed call before execution. This clearly distinguishes it from siblings like get_outcome, get_status, or verify_company_record, which address different concerns.

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 signals this tool is for pre-execution estimation ('before execution') and cautions that accuracy is not promised, directing the user to cost_range. It does not explicitly name alternatives or state when not to use it, but the context is clear enough given the sibling set.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it explains that each list is fetched from the issuing authority, that alternate spellings come from ALT.CSV, and that the UN list is deliberately omitted due to licensing. It also discloses the quota/pricing model ('free in quota, then $0.02/call'), which is useful cost-awareness context not present in 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?

The description is a single dense paragraph that front-loads the core purpose and then adds the key exclusions and pricing. Every sentence earns its place: the list enumeration, the UN exclusion with rationale, and the cost note. It is slightly long but not bloated, and the most decision-relevant information (what is screened and what is not) appears early.

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 screening tool with no output schema, the description covers the main things an agent needs: what lists are searched, what is excluded and why, and the cost model. It does not describe the output format or match scoring, but since there is no output schema and the tool is a simple screening lookup, a brief note on return shape would have made it complete. Still, the coverage is strong for the tool's complexity.

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 three parameters. The description adds a little context by mentioning alternate spellings (ALT.CSV), which implies why the 'name' parameter may match variants, but it does not add meaningfully beyond the schema for 'type' or 'country'. Baseline 3 is appropriate because the schema carries the parameter documentation burden.

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 opens with a specific verb ('Free screening') and a precise resource ('a name or entity against official sanctions lists'), then enumerates the exact lists covered (OFAC SDN, EU consolidated, UK FCDO). It also explicitly names what is NOT covered (UN Consolidated List) and why, which sharply distinguishes it from any sibling that might look similar.

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 states the tool's scope and the data sources, and it explicitly excludes the UN list with a licensing rationale, which helps an agent decide when not to rely on it. It does not name sibling tools or provide explicit 'use this instead when...' guidance, but the context signals show siblings are unrelated (get_outcome, get_status, etc.), so the exclusion of the UN list is the main routing guidance and it is clear.

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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by disclosing the internal check count (6), the aggregate pass/fail nature, and the free/no-key requirement, which are not in 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?

The description is compact and front-loaded: it states the core function first, then the limitation, then the use case, then the free/no-key note. Every sentence earns its place with no 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 zero-parameter, read-only health probe with no output schema, the description covers the essential information: what it checks, what it reports, what it does not do, and when to use it. The only minor gap is not describing the exact output format, but that is not critical for a simple health probe.

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 schema is trivially complete. The description adds no parameter details because none are needed; the baseline of 4 for zero-parameter tools 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 clearly states the tool's function: it runs 6 internal checks and reports how many passed, confirming the server is up. It explicitly distinguishes itself from per-tool probing, which differentiates it from sibling tools like get_status or verify_company_record.

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 says to use it to verify connectivity before production use, which gives a clear context. It does not explicitly name alternative tools or state when not to use it, but the 'does NOT probe each tool individually' exclusion provides useful 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 declare readOnlyHint=true and idempotentHint=true, and the description adds substantial behavioral detail beyond that: it names the two registries queried, highlights that it returns an honest not_found with sources when absent, and mentions the free quota and pricing. This goes well beyond the annotation hints and gives the agent a clear model of how the tool behaves under all outcomes.

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 long but every sentence earns its place: purpose, registry sources, full return field list, non-fabrication guarantee, and cost model. It is front-loaded with the core action and immediately informs the agent of the most critical behavioral trait (honesty). No filler or 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?

Given that there is no output schema, the description compensates by listing every return field. It also covers failure behavior (not_found), sources queried, and cost. For a read-only lookup with simple parameters and clear behavior, nothing critical is missing – an agent has everything needed to correctly invoke and interpret the tool.

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 three parameters. The description does not add any parameter-specific semantics beyond what the schema provides; it only implicitly references name and LEI in the context of the registry output. With full coverage, a baseline score of 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 states a specific verb ('lookup'), a precise resource (official company registry records via GLEIF and SEC EDGAR), and enumerates the returned fields (legal name, LEI, status, jurisdiction, etc.). It also explicitly declares what it will never do ('never fabricates'), which distinguishes it from other tools by setting clear expectations.

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 does not explicitly name alternative tools or conditions for choosing this one, but the sibling list contains no similar lookup tools, so the absence of explicit exclusion is acceptable. The description does provide strong contextual cues about when it is appropriate: it is a free/live lookup with honest not_found behavior, which helps the agent decide to use it for authoritative registry queries. However, it stops short of stating 'use X instead' or 'do not use when Y'.

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