apply_business_profile_updateApply the exact business-profile patch returned by a recent preview.
| Name | Required | Description | Default |
|---|---|---|---|
| patch | Yes | ||
| reason | No | ||
| preview_token | Yes | ||
| expected_revision | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate safety: readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds some context by emphasizing 'exact' and 'recent preview,' but it does not disclose additional behavioral traits such as concurrency semantics, failure modes, or what the applied update affects.
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, front-loaded sentence with no filler or redundancy. Every word contributes to conveying the core action and precondition.
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 is minimally viable for a simple apply operation with good annotations and a detailed input schema, but it omits important invocation context such as how expected_revision relates to the patch, what happens on success or failure, and what the caller should expect in return. The absence of an output schema raises the need for more guidance.
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 0%, so the description must compensate for parameter semantics. It only indirectly relates 'patch' and 'preview_token' to the preview workflow; it does not explain 'expected_revision' or 'reason,' and the nested patch object's fields are left entirely to 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 uses a specific verb ('Apply') with a specific resource ('business-profile patch') and adds the crucial qualifier 'exact ... returned by a recent preview.' This clearly distinguishes the tool from the sibling preview_business_profile_update.
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 phrase 'returned by a recent preview' establishes a clear precondition and workflow context: this tool should be used after a preview, not instead of one. It does not explicitly name alternatives or exclusion cases, but the intended usage is reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear boundaries (e.g., get_award vs search_awards, get_business_profile vs get_vendor). Some overlap exists in pairs like find_recompetes/find_recompetes_for_business and search_opportunities/search_opportunities_for_business, though the latter are differentiated by profile context.
All tools follow a consistent verb_noun snake_case pattern (get_, search_, update_, watch_, save_, etc.) with no stylistic deviations. Naming is highly predictable across the entire set.
At 39 tools, the surface is excessively large. While the domain is broad, many tools could be combined or parameterized (e.g., get_business_awards and get_vendor_awards, multiple search variants). This creates overhead for agents and dilutes focus.
The tool set covers the core lifecycle: opportunity/award searching and retrieval, business profile updates, saved searches, watches, exclusions, and reference data. Minor gaps such as award amendments or more granular exclusion handling exist, but the surface is fundamentally complete.