GovGazette

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.

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

Beyond the annotations (readOnly, non-destructive, idempotent), the description adds that the tool compares facts and explicitly avoids claiming eligibility or win odds. However, it does not describe the output format or any other behavioral aspects, so transparency is moderate.

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, concise sentence with no redundant information. It conveys the core purpose and constraints efficiently, making it well-structured and 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?

While the purpose is clear, the description lacks details about the expected output or what the assessment includes. Given there is no output schema, the description should provide more context on the return value or the nature of the assessment. It also does not elaborate on how the 'connected business profile' is determined, leaving some gaps.

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 only parameter, notice_id, is mentioned in the schema but not described in the tool description. The description references opportunity facts but does not explicitly explain what notice_id refers to (e.g., an opportunity identifier). Schema coverage is minimal, so the description should have compensated, but it does not.

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 purpose: to assess an opportunity for a business by comparing source-backed facts with the business profile. It also specifies what it does not do (claim eligibility or win odds), making it distinct from related tools like get_opportunity or search_opportunities_for_business.

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 explicitly mention when to use this tool versus alternatives. It only hints at a limitation (no eligibility/win odds claims), but lacks guidance on conditions or scenarios that would warrant its use over sibling tools.

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 disclose readOnlyHint, idempotentHint, and destructiveHint. The description adds the critical caveat 'This is not a compliance certification' and specifies the exactness of the lookup, which are meaningful behavioral details beyond the annotations. 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?

Two concise sentences. The first sentence leads with the action and scope, and the second adds an important qualification. No redundant words, and the structure is front-loaded with the core purpose.

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 tool is simple, with no parameters and no output schema. The description explains the purpose, scope, and an important caveat. While it does not explicitly describe the return format, the nature of the tool makes the output predictable enough. Given the low complexity, this is adequate.

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 trivially covers 100% of parameters. Per the baseline for 0 parameters, a score of 4 is appropriate. The description does not need to explain parameters since there are none.

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 action ('Run an exact UEI exclusion lookup') with a clear resource ('exclusion lookup') and scope ('for the connected business'). It also distinguishes itself from a general search tool by emphasizing 'exact UEI' and adds a disclaimer that it is not a compliance certification, which further clarifies its role relative to potential 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 this is for the connected business and uses an exact UEI lookup, but it does not explicitly state when to use this tool versus siblings like search_exclusions or get_business_profile. There is no mention of scenarios where this tool should be preferred or when to use alternatives, leaving the agent to infer usage.

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 readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds meaningful behavioral context beyond these annotations by stating that results are 'inferences' drawn from period-of-performance dates, not confirmed solicitations. This clarifies the heuristic nature and incomplete consistency of results, which is valuable for the agent.

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 (two sentences) and front-loaded, immediately stating the core purpose and the key caveat about inference. Every sentence earns its place with no redundancy or filler.

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 gives the essential purpose and result type, but lacks information about result format, pagination, or parameter usage. Given the tool has 9 optional parameters and no output schema, it could benefit from explaining the return structure or common filters. It is adequate for a simple search tool but leaves gaps for a complex parameter set.

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 input schema provides no property descriptions. The description does not compensate by explaining any of the 9 parameters (e.g., from/to as date range, naics, set_aside). While parameter names are somewhat self-explanatory, the description omits all parameter semantics, leaving the agent to infer meaning solely from names and types.

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: 'Find awards whose period-of-performance dates suggest a possible recompete.' It uses a specific verb ('Find') and resource ('awards') with a distinct filter (dates suggesting recompete). It also clarifies what the results are not ('not confirmed solicitations'), which differentiates it from sibling search tools.

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 identifying potential recompete candidates based on dates, and the phrase 'not confirmed solicitations' warns against treating results as confirmed opportunities. However, it does not explicitly state when to use this tool versus alternatives like search_awards or get_opportunities, nor does it mention exclusions or prerequisites.

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, destructiveHint, so the safety profile is known. The description adds valuable context beyond this: 'Results are not confirmed solicitations' warns that the output is inferred and potentially unverified. This is useful for the agent to set expectations and avoid over-trusting results, going beyond what annotations provide.

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 sentences long, with the primary purpose front-loaded. Every word adds value: 'inferred' and 'not confirmed' are essential caveats, and 'across profile markets' scopes the tool. There is no filler or redundant information.

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 tool with one optional parameter and rich annotations, the description covers the core purpose and an important caveat about data confidence. It doesn't detail return structure, but with no output schema and a simple list-returning operation, that's acceptable. The description is complete enough for a low-complexity 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?

The input schema has one parameter, 'limit', with default/min/max constraints, but the description does not mention this parameter at all. With schema description coverage at 0%, the description fails to compensate by explaining what 'limit' controls. While the parameter name is self-explanatory, the description still adds no semantics beyond the schema, and the rubric requires compensation for low 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's function: 'Find inferred recompete candidates across profile markets.' It uses a specific verb ('Find') and identifies the resource ('recompete candidates') and scope ('across profile markets'). The qualifier 'inferred' and the note 'not confirmed solicitations' further illuminate the nature of the results, distinguishing this from a confirmed/recompete tool.

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 context via 'across profile markets,' suggesting this tool is for a connected business's own market areas. However, it does not explicitly mention when to use this over the sibling tool 'find_recompetes' or any other alternatives. It provides no exclusions or when-not-to-use guidance, but the scope is reasonably implied.

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 the tool as read-only, idempotent, and non-destructive, so the bar is lower. The description adds minimal context by referencing a 'selected hot award dataset', but does not detail expected behavior for missing IDs or open-world aspects.

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, concise sentence that front-loads the core action. Every word is purposeful 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 simple one-parameter tool with rich annotations, the description is mostly adequate but leaves ambiguity around the 'hot award dataset' term. It does not clarify what selecting this dataset means or what to expect when the award_id is not found.

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%, and the description does not explicitly explain the award_id parameter. The agent must infer its meaning from the tool name, and the description adds no value beyond the schema's type and minLength constraints.

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 ('Get') and the resource ('one award'), distinguishing it from sibling tools like search_awards and get_vendor_awards. However, the phrase 'selected hot award dataset' is vague and not fully explained, which slightly reduces clarity.

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 this tool is for retrieving a single award by ID, but it does not explicitly state when to use it versus alternatives such as search_awards or get_vendor_awards. No exclusions or alternative 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?

Annotations already mark the tool as read-only, idempotent, open-world, and non-destructive. The description adds a useful nuance with 'without claiming an incumbent,' but does not disclose output shape, pagination, or authorization expectations.

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 compact sentence with no filler words. It loses one point because the phrasing is awkward and sacrifices clarity for brevity.

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?

This is a simple one-parameter read-only tool with strong annotations, so the baseline context is present. Still, because there is no output schema, the description should have explicitly indicated what the tool returns or how the 'separation' is represented.

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%, and the description never mentions notice_id or explains how it should be used. The parameter name is self-explanatory, but with no description-level compensation the semantics remain minimally covered.

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 title identifies the tool as getting opportunity award evidence, and the description names concrete entities: official notice awardee, linked prior award recipients, and market participants. However, the verb 'Separate' is ambiguous about whether the tool returns categorized data or performs some internal distinction, making the purpose less clear than it could be.

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 offers no guidance about when to use this tool instead of related siblings such as get_award, get_opportunity, or get_vendor. There are no stated alternatives, prerequisites, or exclusion conditions.

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 some context about the 'confirmed profile UEI' and 'explicit coverage limits,' but the meaning of 'selected-hot' is unclear and no additional behavioral details such as return format or pagination are disclosed.

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 sentence and reasonably short, but it is not optimally clear due to jargon like 'selected-hot' and 'confirmed profile UEI.' It is concise in length but sacrifices clarity, and the awkward phrasing prevents it from being a model of efficient communication.

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?

With no output schema, the description should clarify what the returned award history contains, but it does not. It also leaves 'selected-hot' and the selection criteria unexplained, so the tool's behavior is incomplete for an agent trying to invoke it 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?

The input schema documents the single 'limit' parameter with default, minimum, and maximum, but the description's vague 'explicit coverage limits' adds no meaningful parameter semantics. With 0% schema description coverage, the description should compensate, but it does not clearly explain the parameter or its effect.

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 ('Get') and resource ('award history') scoped to the connected business/confirmed profile UEI, which makes the core purpose understandable. However, the phrase 'selected-hot' is ambiguous and the description does not explicitly differentiate this from sibling award-related tools like get_vendor_awards or search_awards.

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 guidance is provided about when to use this tool versus alternatives such as get_vendor_awards, get_award, or search_awards. The description gives context ('confirmed profile UEI') but no exclusions, prerequisites, or alternative 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?

The annotations already indicate read-only and idempotent behavior. The description adds the trait 'deterministic' and clarifies the data source ('connected business profile'), which goes beyond the annotations. However, it does not discuss potential errors or side effects, but those are minimal for a getter.

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, consisting of two short sentences that fully convey the tool's purpose without unnecessary detail. It is well-structured and easy to read.

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?

There is no output schema, so the description should clarify what the tool returns. It mentions 'defaults' for several categories, but does not specify the structure or format of the returned data. It also does not mention any prerequisites (e.g., that a business profile must exist). This is adequate but not fully complete.

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 no parameters, and the schema covers this perfectly. The description does not need to explain parameter meanings further. According to the rubric, a high schema coverage sets a baseline of 3, which is appropriate here.

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: retrieving defaults for specific entities (opportunity, award, etc.) from the business profile. The verb 'Get' and the resource 'business profile' make the purpose explicit and distinguishable from sibling tools that handle other data.

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 mention when to use this tool over alternatives or provide context for its usage. It only states what it does, leaving the user to infer when it would be appropriate. No comparisons or exclusions are given.

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, destructiveHint=false, and idempotentHint=true, establishing a safe, read-only profile. The description aligns with this (no contradiction) and adds the useful scope of 'public' data and the specific dimensions being summarized. It adds some value by clarifying what class of market data is exposed, though it stops short of describing output format or data freshness.

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, efficiently worded sentence that front-loads the verb and primary resource. Minor redundancy exists between the title ('market evidence for the connected business') and the description ('public market summaries'), and the word 'selected' is vague, but nothing is wasted.

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, no-output-schema tool with strong annotations, the burden on the description is lighter. However, the single most valuable piece of context—how get_business_market differs from the near-identically-named get_market_summary and what 'evidence' the summaries contain—is absent. Adequate for the tool's simple shape, but a missed opportunity to disambiguate the sibling set.

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, and the rubric establishes a baseline of 4 for no-parameter tools. The description's framing of 'classifications, agencies, and target states' gives helpful conceptual context for what the filtered summaries are about, though there is no actual parameter documentation burden to carry here.

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+resource ('Get... public market summaries') and adds scoping dimensions ('profile classifications, agencies, and target states') that give the user a concrete sense of what is retrieved. It's clear, though it doesn't explicitly differentiate from the similarly-named sibling get_market_summary.

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 offers no guidance on when to use this tool versus alternatives like get_market_summary, get_business_profile, or get_business_awards. With 38 siblings and a near-twin in get_market_summary, the absence of any disambiguation is a significant gap. No exclusions, alternatives, or context are given.

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 read-only, idempotent, and non-destructive hints. The description adds useful context by naming the exact data areas and the required 'profile-read permission', which goes beyond what annotations alone convey.

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 sentences, front-loaded with the verb 'Read' and immediately listing specific data categories, followed by a permission note. Every word 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?

Given this is a zero-parameter, read-only tool with no output schema, the description sufficiently conveys what data is returned by listing the four categories. Combined with strong annotations, the agent has enough information to decide when to invoke it.

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 does not need to add parameter-level detail. Per the baseline for 0 params, a score of 4 is appropriate, and no gaps exist.

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 reads the business profile, listing four specific content areas (confirmed business identity, capability preferences, public SAM evidence, selected-award coverage). This specificity distinguishes it from sibling getter tools like get_business_market or get_business_awards.

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 use when you need the connected business profile's identity, capabilities, SAM evidence, or award coverage, and it notes a permission prerequisite. However, it does not explicitly contrast with alternatives or say when not to use it, which is less helpful given the many sibling tools.

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 clear. However, the description does not disclose what 'signals' means, whether the summary is an aggregate or a list, how the optional parameters interact, or what happens if no filters are provided. It adds minimal 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 a single sentence and not bloated, but it is under-specified. It doesn't front-load any critical usage constraints or parameter details, and while concise, the brevity sacrifices essential information, making it no more informative than a high-level summary.

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?

With five optional parameters, no output schema, and no parameter descriptions, the description is insufficient for an agent to effectively use the tool. It does not explain what the returned summary contains, how to interpret a 'market slice,' or any constraints on parameter combinations, leaving significant gaps in 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?

The schema has 0% description coverage for its five properties (psc, naics, state, agency, set_aside), and the description does not mention or explain any of them. Since the description fails to compensate for this gap, an agent cannot understand the meaning or purpose of these parameters or how to construct a valid query.

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 uses the verb 'Summarize' and identifies the resource as 'public award and opportunity signals' for a 'market slice,' which distinguishes it from sibling tools that list, search, or retrieve specific records. However, the term 'market slice' is vague and could benefit from explicit mention of the filter dimensions (psc, naics, state, agency, set_aside).

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 no guidance on when to use this tool versus alternatives such as search_awards, get_award, or search_opportunities. There is no mention of exclusions, prerequisites, or specific use cases, leaving the agent to infer the appropriate context solely from the tool's name.

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 the tool as read-only, idempotent, and non-destructive. The description adds that the response includes GovGazette and official source links, and notes it returns a single opportunity, but does not disclose further behavioral details like error cases or data freshness, which is acceptable given the strong 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, front-loaded sentence with no redundant phrasing. Every word contributes meaning, and it avoids restating the tool name or title.

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 get-by-ID tool with rich annotations, the description is complete: it identifies the resource, the required input, and what links are included in the result. No output schema exists, but the description sufficiently conveys the return nature. Given the low complexity, nothing essential 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 schema has zero description coverage, so the description must compensate. It mentions 'by notice ID' and 'SAM.gov' which adds domain context to the otherwise generic notice_id parameter, but it does not provide format, example, or source for obtaining the ID. This is marginal but adequate for a single, self-explanatory parameter.

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 single SAM.gov opportunity by notice ID and includes GovGazette and official source links. It distinguishes itself from siblings like get_opportunity_changes or get_opportunity_documents by focusing on the base opportunity 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 phrase 'by notice ID' clearly indicates this tool is for retrieving a specific opportunity when the ID is known. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to choose this over search tools.

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, so the agent knows this is a safe read operation. The description adds 'bounded' and 'source-backed' which hints at scope and evidence, but doesn't detail pagination, data freshness, or what happens if the notice_id is invalid. With annotations covering safety, a 3 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 a single sentence that front-loads the key qualifiers ('bounded, source-backed') and lists the brief's contents. It's efficient with no wasted words, though the list of content areas is somewhat long.

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 tool's complexity (a comprehensive brief with multiple content areas) and the lack of an output schema, the description gives a good overview but doesn't specify the structure or format of the response. The single parameter is simple, and annotations cover safety, so the description is adequate but not exhaustive.

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%, but there is only one parameter (notice_id) with a minLength of 1. The description doesn't explain what notice_id refers to (e.g., a government opportunity ID), but the tool name and context make it inferable. Since the schema is minimal and the description doesn't add parameter-specific meaning, a baseline 3 is fair.

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 'bounded, source-backed response decision brief' with specific content areas (deadline status, fit signals, requirements, etc.). It uses a specific verb ('Get') and resource ('opportunity decision brief'), and the content list distinguishes it from siblings like get_opportunity or get_opportunity_changes, though it doesn't 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 this is for decision-making on an opportunity, but it doesn't explicitly state when to use this versus get_opportunity, get_opportunity_extracted, or search_opportunities. The content list suggests a comprehensive brief, but no exclusions or alternative tool names 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: changes are sanitized (redacted/cleaned), immutable (append-only), and carry separate source and detection times. This helps the agent understand the nature of returned data beyond basic read-only semantics.

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 that efficiently states the core purpose and distinctive features. There is no fluff or repetition; every term 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?

With five parameters, no schema descriptions, and no output schema, the description is insufficient for confident tool invocation. Annotations provide safety context, but the missing parameter semantics and result structure leave significant gaps that the sparse description does not fill.

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%, and the description does not explain any of the five parameters. It only implies that notice_id identifies the target opportunity. The meanings of type, limit, since, and materiality are left undocumented, forcing the agent to guess at filter 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 uses a specific verb ('Get') and resource ('opportunity changes'), and further specifies unique characteristics ('sanitized immutable changes', 'separate source and detection times'). This clearly distinguishes the tool from siblings like get_opportunity, which likely returns current opportunity details, and get_opportunity_documents for files.

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 offers no explicit guidance on when to use this tool versus alternatives or scenarios where it should not be used. While 'change history' implies an audit or history use case, no comparison or exclusions are provided, leaving the agent without clear decision support.

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, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds valuable context by warning that results should not be treated as independent cost estimates or win odds, which goes beyond what annotations provide.

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 concise sentences: the first states the primary purpose, the second adds an important caveat. No wasted words, information is front-loaded.

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?

Although the tool is simple (1 parameter, no nested objects), there is no output schema and the description does not explain return value structure, what 'comps' entails, or how the notice_id is used. The caveat about cost estimates/win odds provides some context but leaves significant gaps.

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 only notice_id with zero schema description coverage. The description does not explain how notice_id is used or clarify the relationship between the tool name (opportunity comps) and the notice_id parameter. The parameter name is self-evident, but the description adds no semantic value 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?

The description uses the specific verb 'Get' with the resource 'historical comparable public awards', clearly distinguishing this from sibling tools like get_award or get_opportunity. The scope is unambiguous: it returns comparable awards, not a single award.

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?

There is no explicit guidance on when to use this tool versus alternatives. The second sentence ('Results are not an independent cost estimate or win odds') is a caveat about output interpretation, not a usage guideline. No alternatives or exclusions are mentioned.

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 convey read-only, idempotent, non-destructive behavior. The description adds useful behavioral context: it notes that raw binaries are not proxied and that the plain-text chunks are 'untrusted', which informs the agent about link reliability. It also scopes to 'current public' attachments, giving a temporal constraint. This adds value beyond the annotation profile.

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 concise sentences with no fluff. The primary purpose is front-loaded, and the caveat about raw binaries is an efficient second sentence. Every word 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 read-only tool with one parameter and no output schema, the description covers the essential behavior and outcomes (types of links returned, non-proxying). It does not explain the parameter or potential error conditions, but these are minor given the low complexity. It is mostly complete for an agent to call it 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?

The schema description coverage is 0%, so the description must compensate by explaining the `notice_id` parameter. It does not mention the parameter at all. While the name is somewhat self-explanatory (likely an opportunity notice ID), the description does not explicitly state that `notice_id` identifies the opportunity whose documents should be listed. This is a significant gap given 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 states the verb 'List' and the resource 'public SAM attachments', and adds details on what it returns (external download links and plain-text chunks) and a caveat (raw binaries not proxied). This clearly distinguishes it from sibling tools like get_opportunity or get_opportunity_extracted by focusing on attachments and download links.

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 the tool is for retrieving attachment/download links for a given opportunity, but does not explicitly contrast it with alternatives or state when not to use it. The context is clear enough given the focus on documents, but no explicit exclusions or alternative routing 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context by stating the output is 'exact' and 'without an LLM', indicating a deterministic and reproducible extraction process. This goes beyond annotations and does not contradict 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 a single, front-loaded sentence: 'Get exact citations, requirements, costs, dates, forms, and submission text extracted without an LLM.' It contains no filler, immediately states the action, and lists the returned content types concisely. Every word 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 read-only tool with one parameter and strong annotations, the description is mostly complete. It lists the kinds of extracted data (citations, requirements, costs, dates, forms, submission text), which gives a good sense of the output. However, there is no output schema, and the description does not mention behavior when data is not found or how the data is structured, leaving minor gaps. Given the simplicity, 4 is appropriate.

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 one parameter, notice_id, with no description, resulting in 0% schema coverage. The tool description does not mention the parameter, but the name 'notice_id' is self-explanatory and the tool name 'get_opportunity_extracted' clarifies it refers to an opportunity notice. Since the parameter is trivial, a score of 3 is defensible, though better compensation in the description would be ideal.

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 'exact citations, requirements, costs, dates, forms, and submission text extracted without an LLM.' This identifies a specific verb+resource and distinguishes it from sibling tools like get_opportunity by emphasizing deterministic (non-LLM) extraction, making the purpose unmistakable.

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 'without an LLM' implies this tool is for deterministic facts rather than AI-generated summaries, but it does not explicitly name alternatives or provide when-not-to-use guidance. Sibling tools like get_opportunity and search_extracted_facts exist, yet no direct comparison or exclusion is given, leaving usage implied rather than explicit.

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, covering the safety profile. The description adds the context that the record is 'public', implying no special access required, which is a useful behavioral note. However, it does not disclose other behaviors like error handling or response format, so with annotations present 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 a single sentence that is front-loaded with the action and resource, followed by the identifier requirement. Every word earns its place with 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?

The tool is a simple lookup with one parameter and no output schema. The description specifies the resource type, the record scope (public), and the exact identifier format. Combined with annotations, this provides enough context to invoke the tool correctly. It does not describe the return value, but for a getter named 'get_vendor' this is implied and not a critical gap.

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 must compensate. It clarifies that the single parameter is a '12-character UEI' used to fetch the record, adding meaning beyond the schema's bare length constraints. While it doesn't expand the acronym UEI, it clearly identifies the parameter's role and format, which is sufficient for this simple tool.

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 the specific verb 'Get' and identifies the resource as 'public vendor or awardee record' with the exact identifier '12-character UEI'. It clearly distinguishes from sibling tools like search_vendors (search) and get_vendor_awards (awards for a vendor), making the purpose 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 when you have a 12-character UEI, but it does not explicitly state when not to use it or mention alternatives such as search_vendors for lookups without a known UEI. The context is clear but the guidance is not explicit, so it falls at 'implied usage'.

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 destructiveHint=false. The description adds that the data is 'public' and concerns 'award history', giving useful context beyond the structured annotations without contradiction.

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?

A single front-loaded sentence that conveys all essential meaning with no redundant words. It is the ideal length for a tool of this simplicity.

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 tool is simple, with strong annotations and only 2 parameters. The description adequately covers purpose and scope. It does not detail return format, but no output schema exists and the use case is straightforward, so this is not a critical gap.

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 has 0% parameter descriptions. The description clarifies that 'uei' refers to a vendor's UEI, but does not explain the 'limit' parameter. The schema's min/max/default constraints for limit partially compensate, making this an average score.

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 the specific verb 'Get' with a clear resource ('public award history') and scope ('one vendor UEI'). This distinguishes it from siblings like get_award (single award) and search_awards (search), making its purpose 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?

It clearly scopes usage to a single vendor UEI, implying it is for retrieving one vendor's award history rather than searching across vendors. However, it doesn't explicitly mention alternatives or when-not to use it, so it falls 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the OAuth requirement and explicitly states 'never changes a watch,' reinforcing the read-only behavior beyond what annotations provide. This adds useful context without contradicting 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 one concise, front-loaded sentence that covers purpose and a key requirement. No filler or redundancy; every word serves to inform the agent.

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 tool with no parameters and no output schema, the description fully specifies what it reads and its prerequisites. It is complete for an agent to decide when to invoke it, given the annotations and the absence of complex inputs or outputs.

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 are no parameters, so the description does not need to explain them. The schema coverage is 100% (vacuously) and the description adds no param-specific details, but since none exist, this is appropriate and meets the baseline for zero-parameter tools.

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 purpose: reading watches and related items. It uses the verb 'Read' and specifies the resources (searches, pursuits, award/vendor watches, recompete radars), distinguishing it from sibling tools that update or save watches.

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: it reads all watch types but does not mention when to use it over specific get_* tools. It implies it is the general read tool but lacks explicit exclusions or alternative suggestions, though the listed resource types give a strong hint.

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, openWorldHint, idempotentHint, and destructiveHint=false, so the tool's safety profile is covered. The description adds only the 'Search or retrieve' behavior and reference type scope, which is consistent but minimal 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 a single, front-loaded sentence with no wasted words, listing the scope efficiently.

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 tool is simple and read-only with strong annotations, and the type enumeration helps. However, the description does not clarify how to use q and id together or separately, nor does it mention any constraints like requiring one of them, which leaves a moderate gap for autonomous invocation.

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 descriptions are absent (0% coverage), so the description carries the burden. It adds human-readable labels for the type enum (e.g., 'SBA size-standard' for 'sba_size_standard'), but does not explain the q vs id distinction or limit semantics beyond what property names imply.

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 specific verbs 'Search or retrieve' and enumerates reference types (NAICS, PSC, FAR, etc.), clearly distinguishing from sibling search tools that focus on awards, opportunities, or vendors.

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 listing reference categories but provides no explicit when-to-use guidance, exclusions, or alternative tool references. The agent must infer that this tool is for reference lookups rather than award/opportunity searches.

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?

The description says 'preview ... before applying them,' implying no state modification, yet the annotations set readOnlyHint to false, suggesting the tool may modify state. This directly contradicts the description's implied read-only behavior. No other behavioral details are provided, so this is a critical gap.

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, direct sentence that is easy to parse and front-loads the core purpose. While it is concise, it sacrifices necessary detail, but from a structural perspective it is appropriately sized for a simple statement.

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 tool's complexity (nested patch object, multiple optional fields, no output schema), the description is far too minimal. It provides no information about return values, expected_revision semantics, or how the preview is presented. The lack of output schema and low parameter coverage make this incomplete for an agent to use effectively.

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 by explaining the parameters, but it only mentions 'capabilities and target markets' without mapping to specific fields. The patch object has many properties, but none are described, and expected_revision and reason are entirely undocumented. This is insufficient for a complex nested parameter structure.

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 previews changes to capabilities and target markets before applying them, distinguishing it from the sibling tool apply_business_profile_update. The verb 'preview' and resource 'business-profile update' are specific and actionable.

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 'before applying them' explicitly situates this tool in a workflow, implying it should be used to inspect changes prior to application. It does not explicitly name the alternative, but the context makes the usage clear enough.

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 readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds one behavioral nuance ('exact matches first') but does not disclose result format, pagination, or type-specific handling, which would be valuable for a resolver. With strong annotations, 3 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 a single, dense sentence that is front-loaded with the action and resource, and the enumerated identifier types are all necessary context. There is no filler or redundancy, making it highly concise while preserving key information.

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?

Although the purpose is clear, the description lacks parameter details and return behavior. With no output schema, an agent cannot determine what a successful resolution returns or how to interpret multiple matches. The `types` parameter, in particular, is left completely undocumented, so the tool is not fully invocable from the description alone.

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%, and the description does not explain the `q`, `limit`, or `types` parameters. It indirectly implies `q` accepts the enumerated identifier types, but it does not clarify input format, the `types` filtering behavior, or `limit` constraints. This is a clear gap in parameter understanding.

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 ('resolve') and explicitly names the resource scope ('federal contract identifier'), plus enumerates the identifier types (notice, solicitation, award, PIID, UEI, CAGE, NAICS, PSC, FAR). This clearly distinguishes it from sibling search/get tools and clarifies its exact-match behavior.

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 list of identifier types and the phrase 'exact matches first' strongly imply the tool is intended for resolving known identifiers, contrasting with broader search tools in the sibling list. However, it does not explicitly state when not to use it or name alternative tools, so it falls just short of full usage 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?

The description adds little beyond the annotations, which already indicate a non-read-only, non-idempotent operation. It fails to disclose potential side effects, such as whether saving creates a duplicate or overwrites an existing search, and what happens to delivery channels when enabled is false. Given the idempotentHint is false, an agent would benefit from knowing the implications of repeated calls.

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 concise sentence, front-loading the core action and the optional cadence choice. Every word adds value, with no redundancy or excess structure.

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 tool has five parameters but the description only covers saving and cadence, omitting important configuration options like delivery channels and enabled status. With no output schema, the description also fails to specify what the tool returns or how success is indicated, making the tool incomplete from an agent's perspective.

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?

With schema description coverage at 0%, the description must compensate for parameter meanings. It addresses 'name', 'search_spec' implicitly, and 'cadence' explicitly, but remains silent on 'enabled' and 'delivery_channels'. It also does not explain the structure of 'search_spec', leaving several parameters unclear.

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 creates a saved opportunity search with an optional alert cadence, using the specific verb 'save' and resource 'federal opportunity search'. It distinguishes itself from siblings like 'update_saved_search' by implying a new creation, and from 'search_opportunities' by focusing on saving rather than executing a search.

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 saving a new search and setting cadence, but it does not explicitly contrast with alternatives like 'update_saved_search' or state when not to use this tool. There is no mention of exclusions or alternative tool names, so guidance is only implied.

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 are all false (readOnlyHint=false, openWorldHint=false, idempotentHint=false, destructiveHint=false), providing no safety or behavioral cues. The description only says 'Save', which implies a mutation, but it does not disclose whether the radar is persisted, whether it triggers notifications, whether saving with an existing name overwrites, or how 'inferred recompete window' is calculated. Since annotations are uninformative, the description carries the burden but fails to add meaningful behavioral transparency.

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 sentence, concise and front-loaded, with no unnecessary words. It efficiently conveys the core action and subject. However, it may be overly terse for the tool's complexity, but that is a completeness issue rather than a conciseness flaw. For what it attempts to say, it is well-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?

The tool has 6 parameters including a nested object, no output schema, and all-false annotations. The description is severely under-specified: it does not define 'rolling radar', explain what 'inferred recompete window' means, clarify the role of filters, or describe the result of the save operation. An agent cannot correctly invoke this tool without additional knowledge, especially given the presence of sibling tools like 'update_recompete_radar' that are not distinguished.

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%, and the description does not explain any parameter semantics. While property names like 'name', 'filters', 'cadence', etc., are self-explanatory at a basic level, domain-specific parameters such as 'filters' (with fields like psc, naics, set_aside, recipient_uei) and 'delivery_channels' are not elaborated. The description does not compensate for the lack of schema descriptions, leaving the agent to infer how these parameters configure the radar.

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 and resource: 'Save a rolling radar for awards entering an inferred recompete window.' This clearly indicates the action (save/create) and the target (a rolling radar for recompete awards), distinguishing it from 'find' tools. However, the term 'rolling radar' is somewhat vague without further explanation, and it doesn't explicitly differentiate from the sibling 'update_recompete_radar' or 'save_opportunity_search' beyond the obvious save vs. update distinction.

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 no guidance on when to use this tool versus alternatives. It does not mention that this is for creating a new radar while 'update_recompete_radar' is for modifying an existing one, nor does it explain prerequisites like requiring a valid set of filters. The context is implied only by the verb 'save' and the sibling tool names, but no explicit when-to-use or when-not-to-use guidance is given.

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 readOnly, idempotent, and non-destructive behavior, so the description does not need to restate those. It adds context about the dataset being 'public' and 'selected', but does not mention pagination via cursor, default limit, or result format. 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?

The description is a single sentence, front-loaded with the verb and resource, and contains no unnecessary words. However, the phrase 'selected hot award dataset' is vague and could be more precise without adding length.

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?

With 15 parameters, no output schema, and no parameter descriptions, the description is too thin. It does not explain how results are returned, how pagination works (cursor, limit), or how the listed facets map to parameters. A tool of this complexity requires more behavioral detail.

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 has 15 parameters with zero descriptions, and the description only gives a high-level list of facets without mapping them to specific parameter names like piid, psc, or naics. It also mentions 'value' but no corresponding parameter exists in the schema, which could mislead. It does not sufficiently compensate for the schema's lack of parameter 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 the action ('Search') and the resource ('selected hot award dataset'), and lists the search dimensions (award, recipient, agency, classification, place, dates, and value). It distinguishes from sibling tools by focusing on awards, though the term 'hot' is vague and could be clearer.

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 like search_opportunities or search_vendors. The description implies it is for award data, but it does not provide exclusions or alternative tool references.

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 read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context with 'cautious name search' and the warning that this is not a compliance certification, which goes beyond the annotations and clarifies the reliability of the snapshot.

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 redundant wording, and front-loaded with the core purpose. Every part of the description 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?

The core workflow is clear, but the description omits details about parameter interactions (e.g., combining UEI and CAGE), return value structure, and snapshot update frequency. Since there is no output schema, these gaps are not covered elsewhere, leaving the description adequate but not fully complete.

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?

With 0% schema description coverage, the description compensates partially by explaining UEI, CAGE, and name search semantics. However, it does not address q, limit, or sam_number, leaving these parameters underspecified. The added insight on exact vs. cautious searching is useful but incomplete.

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 checks the current public exclusion snapshot using exact UEI/CAGE or cautious name search, which distinguishes it from sibling tools like search_awards or search_vendors. The added caveat that it is not a compliance certification further clarifies the intent.

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 verifying exclusion status but does not explicitly state when to use this tool over alternatives. The 'not a compliance certification' warning gives partial context, but there is no direct mention of when to avoid this tool or which sibling to choose instead.

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 readOnly, openWorld, idempotent, and non-destructive, covering the safety profile. The description adds behavioral context beyond annotations: 'exact source-backed' indicates deterministic matching without approximation, and 'official opportunity descriptions' scopes the data source. It doesn't mention result ordering or pagination, but the core behavior is adequately disclosed.

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 zero wasted words. It includes the key qualifiers 'exact source-backed' and 'official opportunity descriptions' without 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?

The tool is simple with 2 parameters, and annotations provide safety/reliability information. The description conveys the core purpose but does not explain what constitutes a 'fact', how results are ordered, or whether a return structure is expected. Since there is no output schema, some additional detail on return format would be helpful, though the description is minimally adequate.

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%, and the description provides no information about the parameters 'q' or 'limit'. While the names are somewhat self-explanatory, the description does not clarify query semantics (e.g., case sensitivity, field targeting) or the effect of the limit parameter. The description fails to compensate for the lack of schema documentation.

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 'Search' and the resource 'exact source-backed facts extracted from official opportunity descriptions.' It distinguishes itself from sibling search tools by emphasizing 'exact source-backed' and 'deterministic' (from title), which implies a precise, non-fuzzy search over extracted facts rather than full-text or non-deterministic matching.

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 no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. It implies use when needing exact source-backed facts, but it doesn't contrast with sibling tools like search_opportunities or get_opportunity_extracted, leaving the agent to infer the right 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the context that data is 'public', which may imply no authentication, but it does not disclose pagination, result limits, or return format. This is acceptable given the annotations but adds only modest value.

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, efficient sentence that immediately conveys the tool's core purpose and scope. Every word earns its place, and there is no redundant information.

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?

This is a complex search tool with 16 parameters and no output schema, yet the description provides only a one-sentence overview. It omits critical details such as how filters combine, pagination behavior, result structure, or sorting options, leaving the agent under-informed for correct invocation.

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 provides high-level categories (text, classification, buyer, location, status, dates) that loosely map to some parameters, but with 16 parameters and 0% schema description coverage, it is insufficient. There is no explanation of specific parameters like q, sort, cursor, set_aside, or awardee_uei, leaving significant 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 public opportunity data with specific filter dimensions (text, classification, buyer, location, status, dates). This distinguishes it from sibling search tools like search_awards and search_vendors, which target different entity types.

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 when to use the tool (searching opportunity data) but provides no explicit guidance on alternatives or when not to use it. Given the sibling tools, there is no direct comparison or exclusion, so usage context is only implicitly conveyed.

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 readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavior context: the tool produces a ranking with transparent reasons and is not a win probability. These are behavioral traits not captured in the annotations, though it does not disclose return format or pagination.

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 short, front-loaded sentences with no fluff. Every word adds value: the verb, the target, the profile, the transparent reasons, and the explicit negation. It is exceptionally concise and well-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?

Despite good annotations and a clear purpose, the description is incomplete for a tool with 7 optional parameters and no output schema. It fails to explain parameter usage, filter meanings, or the shape of the ranked results. The agent would struggle to invoke the tool correctly without additional context, especially since several sibling search tools exist.

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 carries full responsibility for explaining parameters. However, it does not describe any of the 7 parameters (e.g., q, psc, limit, naics, state, agency, set_aside). The general notion of 'connected business profile' gives some context, but the agent cannot infer the meaning of each filter without additional information.

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 ranks open opportunities against the connected business profile, using a specific verb ('Rank') and resource ('open opportunities'). It also adds a distinctive feature ('with transparent reasons') and differentiates from related tools by noting it is not a win probability.

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 context by specifying the ranking against the connected business profile, but it does not explicitly state when to use this tool over alternatives like search_opportunities or assess_opportunity_for_business. The negation 'This is not a win probability' hints at an exclusion, but no alternative tools or when-not-to-use conditions 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds 'current' and 'public' context but does not disclose pagination behavior, result ordering, or matching semantics. 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?

A single, well-structured sentence that front-loads the primary action and resource. Every word contributes, with no redundancy or filler.

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 rich annotations, the description is adequate but not complete. It does not explain the cursor-based pagination, the exact meaning of 'location' (state vs. country), or what the response structure contains, which are relevant given the 9 parameters and absent 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?

The description lists most searchable fields (name, UEI, CAGE, status, location, primary NAICS), adding meaning beyond bare property names. However, it omits the limit and cursor parameters and does not explain how fields interact (e.g., AND/OR), leaving gaps given the 0% schema description 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 identifies the resource as 'current public SAM entities' and lists specific search fields (name, UEI, CAGE, status, location, primary NAICS). This distinguishes it from sibling search tools like search_awards and search_exclusions.

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 focusing on SAM entities, but it does not explicitly state when to use this tool versus alternatives like search_exclusions or search_awards. No exclusions or alternative tool names are mentioned.

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 idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description adds context that the tool operates on the 'connected account' and includes 'next action' semantics. It does not contradict annotations and builds on the idempotent nature with 'add or replace'.

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 concise sentence that quickly conveys the primary action. No redundancy or filler.

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 tool's complexity (9 parameters, 0% schema coverage, no output schema), the description is too sparse. It omits crucial context such as what happens when the opportunity already exists, and does not clarify the relationship with update_tracked_opportunity.

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%, yet the description only hints at two parameters ('tracked opportunity' and 'next action'). With 9 parameters including enums and defaults, the description does not compensate for the lack of schema descriptions, leaving many parameters unexplained.

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 'Add or replace' with a clear resource ('one tracked opportunity and its next action') and context ('in the connected account'). It clearly distinguishes from the sibling update_tracked_opportunity by implying an upsert operation.

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 when-to-use or alternatives are mentioned. The presence of update_tracked_opportunity as a sibling suggests a distinction between adding/replacing and updating, but the description does not articulate when to choose this tool over that one. Usage is only implied by the name and action.

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 non-read-only and idempotent behavior; the description adds the 'pause/resume' state-change semantics. However, it doesn't disclose what identifying information is needed, whether an existing watch is required, or what state transitions are possible beyond the verbs.

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?

A single, clear sentence fully front-loads the action and resource. There is no filler, redundancy, or unnecessary detail.

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 adequate for a simple mutation with no parameters, but it lacks context about prerequisites (e.g., existing watch), how the award/vendor watch is identified, and what the result of pausing/resuming looks like. Given the sibling watch-management tools, a bit more workflow context would help.

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 zero parameters, so there is no parameter detail to explain; the schema coverage is 100% and an empty schema is self-documenting. The description reasonably relies on context for the target watch, though it doesn't mention how that target is resolved.

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 specific verbs ('Change, pause, or resume') and clearly identifies the resource ('an award or vendor watch'). It distinguishes the tool from creation tools like watch_award/watch_vendor and read tools like get_watch_status, though it doesn't explicitly differentiate update variants.

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 guidance is provided for when to use this tool versus alternatives such as get_watch_status, watch_award, or watch_vendor. The intended use is only implied by the verb 'update' and title, with no exclusions or workflow 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?

Annotations already indicate the operation is not read-only, is idempotent, and is not destructive. The description adds the action range ('change, pause, or resume') but does not explain side effects, persistence, or what state transitions occur, leaving meaningful behavioral details undisclosed.

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 concise sentence with no wasted words and is easy to parse. It is appropriately brief for a simple tool, though it could have used the available space to add a bit more operational context without harming conciseness.

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 empty input schema, the description does not clarify how the tool identifies which recompete radar to update, pause, or resume. It also does not explain what 'pause' or 'resume' means operationally, leaving a critical gap for an agent to invoke the tool correctly in a real workflow.

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 zero parameters and 100% schema description coverage, so there are no parameter semantics to clarify. Per the baseline for tools with no parameters, the description does not need to compensate, and the score reflects that no parameter-related gap exists.

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 changes, pauses, or resumes a recompete radar, using a specific verb and resource. It is distinguishable from sibling tools like save_recompete_radar, though it does not explicitly define what a 'recompete radar' is.

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 guidance is provided on when to use this tool versus alternatives such as save_recompete_radar or update_saved_search. The usage is only implied by the verb 'update' and the listed actions, with no explicit context, prerequisites, or exclusions.

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 disclose idempotent and non-destructive behavior. The description adds minimal context like 'connected GovGazette account' but does not mention side effects, partial update semantics, or response format. Since annotations cover the safety profile, a score of 3 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?

A single, direct sentence with no filler. It front-loads the key action and resource, earning every word's 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?

With 6 parameters and no output schema, the description should explain mutation behavior (e.g., partial updates, not-found handling, return values) but does not. It covers only the high-level action, leaving significant gaps for an agent to invoke 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?

The schema description coverage is 0%, and the description adds no parameter-level meaning. It does not explain name, cadence, search_spec, delivery_channels, or how enabled disables the search. The word 'disable' is the only hint, leaving 6 parameters effectively undocumented.

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 ('Change or disable') and the resource ('a saved search in the connected GovGazette account'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like save_opportunity_search, so it stops short of a 5.

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 no guidance on when to use this tool versus alternatives such as save_opportunity_search or update_tracked_opportunity. It lacks any when-to-use or when-not-to-use 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?

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the description doesn't need to repeat those. However, it adds only the word 'disable' without explaining what that entails (e.g., whether it stops alerts entirely). No detail on partial-update behavior or side effects.

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 sentence that is direct and free of filler. It earns its place by stating the core action and scope in minimal 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?

Despite having 9 parameters, enums, and no output schema, the description is far too sparse to be complete. It doesn't explain how to identify the tracked opportunity, what fields are updateable, or what 'disable' means operationally. The bare-bones wording leaves critical gaps for a mutation tool of this 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 0%, and the tool description provides no parameter information whatsoever. The agent gets no hints about what notice_id, pursuit_state, alert_cadence, or the other fields mean, forcing reliance on raw schema names alone.

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 ('Change or disable') and identifies the resource ('tracked opportunity') and scope ('in the connected account'). It clearly distinguishes from sibling tools like track_opportunity (create) and update_saved_search (different resource).

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 guidance is provided on when to use this tool versus alternatives, such as track_opportunity for creating or update_saved_search for updating saved searches. No exclusions or prerequisites are mentioned.

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 indicate idempotent and non-destructive, which the description does not contradict. The description adds the detail that the watch is for 'material changes and activity', giving some context. However, it does not describe the mechanics of watching (e.g., setting up alerts, permissions required, or lifecycle of a watch).

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, focused sentence that directly states the tool's purpose with no filler. It is front-loaded and efficient, earning its place despite its brevity.

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?

With 5 parameters and no output schema, the description is too sparse. It fails to explain what the tool returns, how the parameters control behavior, or when it should be used versus alternatives. Given the tool's complexity, it is incomplete for reliable selection and invocation.

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 includes 5 parameters (name, enabled, award_id, alert_cadence, delivery_channels) with 0% description coverage. The description does not explain any of these parameters, leaving the agent to infer from names alone. Since schema coverage is zero, the description should compensate but does not.

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 'Watch' applied to 'a selected public award for material changes and activity'. This distinguishes it from sibling tools like get_award (read) and track_opportunity (broader). It is specific about the resource and scope.

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 the tool is used to monitor an award, but it does not provide explicit when-to-use guidance or differentiate from similar monitoring tools like track_opportunity or watch_vendor. No exclusions or alternatives are mentioned. The context 'selected public award' hints at a prerequisite but is not elaborated.

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 indicate this is idempotent and not destructive or read-only, so the description doesn't need to restate those. The description adds context about 'public award activity' and 'one exact vendor UEI', but it doesn't explain what happens if the vendor is already watched, whether an immediate alert triggers on creation, or any side effects beyond creating a watch. Since idempotentHint true and destructiveHint false are given, the additional context is minimal, and the score reflects the limited extra value.

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 one short sentence, efficient and front-loaded with the core action and object. However, given the complexity (5 params, 0% coverage), the brevity may be too sparse, but it doesn't have waste. It earns a 4 because it's appropriately concise for its limited content.

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 tool has 5 parameters, no output schema, and minimal annotations description coverage. The description only addresses the core purpose and requirement for an exact UEI but lacks essential details such as how to configure alert cadence and delivery channels, prerequisites like whether the vendor must exist, or behavior regarding duplicates. This is incomplete for an agent to use it correctly without additional inference.

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 has 5 parameters and the description provides no details about them, with schema description coverage at 0%. The description mentions 'UEI' as the identifier and implies the vendor name, but it does not explain the meaning or purpose of 'enabled', 'alert_cadence', or 'delivery_channels'. Since the schema itself provides little semantic context (just types and defaults), the description fails to compensate, leaving the agent without guidance on how to set these parameters appropriately.

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 (watch) and the resource (public award activity) for a specific vendor UEI. It distinguishes from the sibling 'watch_award' by specifying 'vendor' and 'public award activity', though it could be more explicit about the difference.

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 when to use it (when you want to watch a vendor's award activity) and the exact UEI requirement, but it does not provide explicit guidance on when not to use it or mention alternatives like 'update_award_watch' for existing watches. The sibling list includes 'update_award_watch' and 'get_watch_status', which could be relevant but aren't referenced.

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