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

No annotations are provided, so the description carries the full burden. 'Upsert' hints at idempotency, but the description does not disclose details such as what happens when the profile already exists (update all fields?), side effects, authentication requirements, or error conditions. For a creation tool, more behavioral context is needed.

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 consists of two concise sentences, each contributing meaning. The first sentence states the action and resource, and the second provides workflow context. No redundant or filler 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 two parameters (one required, a complex nested object) and no output schema. The description provides workflow context but does not mention return values, response structure, or error handling. Given the complexity, the description is adequate but lacks completeness; it could, for example, state what the tool returns (e.g., profile ID) or how to interpret success.

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 100% (both parameters have descriptions). The description adds no parameter-level information beyond what the schema provides (e.g., it does not clarify how to use the 'fields' object or the optionality of customerOrgId). With high schema coverage, the baseline is 3, and the description does not exceed it.

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 explicitly states 'Create or upsert a structured business profile for an existing organization,' which clearly identifies the action and distinguishes it from sibling tools like get_business_profile (read) and update_business_profile (update). The verb 'create/upsert' combined with the resource 'structured business profile' makes 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 provides clear workflow context: 'Use this first in the headless workflow: existing PAT + existing org -> create_business_profile -> generate_use_cases or trigger_full_pipeline.' This tells the agent when to use the tool, though it does not explicitly state when not to use it or give alternatives. However, the workflow guidance is strong 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?

No annotations are provided, so the description carries the burden. It implies a read operation ('Download... Returns'), but does not explicitly state it is read-only or mention any authorization requirements. For a download tool, this is adequate but could be clearer.

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, front-loading the primary action and immediately providing the return format and usage guidance. Every sentence adds value 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 the lack of output schema, the description appropriately explains the return value (JSON manifest with files). It clarifies the tool's role relative to siblings. Minor omissions include prerequisites or input constraints, but overall 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?

All three parameters have descriptions in the input schema (100% coverage), so the baseline is 3. The overall description does not add extra parameter-specific meaning beyond what is already in 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 ('Download') and resource ('blueprint as an Agent Skills directory'), clearly distinguishing it from sibling tools like get_blueprint by stating 'Use this instead of reading full blueprint/business-case/plan data via individual 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 explicitly advises when to use this tool ('instead of reading full blueprint/business-case/plan data via individual tools'), but does not explicitly list conditions when not to use it, such as when only a specific field is needed.

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

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns an auditId immediately and implies asynchronous behavior via polling. However, it does not detail side effects, authentication needs, rate limits, or error conditions, which would be beneficial.

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, front-loaded with the key action, and contains no filler. 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?

Given the tool's complexity (async with 6 parameters, no output schema), the description covers the initiation and follow-up steps but does not explain the return value format beyond 'auditId'. It lacks details on required permissions or what to expect after polling completes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description does not add additional meaning beyond the schema's parameter descriptions; it only mentions 'chosen use case' in passing. No extra context is provided for parameters.

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 'Start blueprint generation' and the resource 'blueprint for a chosen use case'. It distinguishes this tool from its siblings like 'get_generation_status' and 'download_blueprint' by indicating it is the initiation step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs when to use the tool and provides a clear workflow: start generation, poll with get_generation_status, then call download_blueprint. It does not explicitly state when not to use it, but the guidance is sufficient for an agent.

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

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

No annotations provided, so the description must fully disclose behavior. It only states it 'generates' and returns data, but does not mention side effects, synchronous/asynchronous nature, or permissions required. This is minimal for a tool that likely creates data.

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, front-loaded with key information. Efficiently states action, inputs, and output utility. No unnecessary 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?

Given no output schema, the description explains the return type as normalized data with IDs, which is helpful. However, it does not mention whether the operation is synchronous or if errors are returned, and there is a sibling get_generation_status that suggests possible async behavior not addressed.

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 100%, so baseline is 3. The description adds value by explaining the return data includes IDs that feed into generate_blueprint, linking the output to a downstream tool. However, it does not add specific parameter-level context 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 clearly states it generates AI use cases from the business profile and readiness assessment, and specifies the output can be passed to generate_blueprint. This distinguishes it from sibling tools like get_use_case or generate_blueprint.

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?

Implies usage requires an existing business profile and readiness assessment, but lacks explicit when-to-use or alternatives. Does not mention when not to use this tool, e.g., if use cases already exist.

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

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

No annotations are provided, so the description carries the full burden. It states it returns a summary but omits behavioral traits like idempotency or error handling. Adequate for a simple read operation but could be more explicit.

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, front-loaded with the action and resource. Every sentence adds value 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?

No output schema exists, but the description lists the fields returned. For a simple get operation with a sibling reference, it is sufficiently complete, though a brief note on response format could enhance 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?

Input schema covers 100% of parameters with descriptions. The description adds no extra meaning beyond the schema (only 'by ID'). Baseline 3 applies due to high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get a blueprint summary by ID' and lists specific return fields, distinguishing it from the sibling 'download_blueprint' which provides full details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises when to use an alternative: 'For full details, use download_blueprint', providing clear context on when to invoke this tool vs. its sibling.

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

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

No annotations provided, so the description must carry the behavioral disclosure burden. It states what is returned but does not mention permissions, latency, or side effects. The 'Get' verb implies a read operation, but no explicit readOnlyHint. Basic transparency is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no redundant information. The first sentence defines the tool's purpose and output, the second provides an alternative. Each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 parameters, no output schema), the description covers the return values and provides an alternative tool. It is missing details on error conditions or prerequisites, but it is sufficiently complete for a straightforward read operation.

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 100% documentation coverage for both parameters (blueprintId and customerOrgId) with descriptions. The tool description does not add any additional meaning or usage context beyond the schema, so it meets the baseline.

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 ('business case summary for a blueprint'), and lists the returned data (executive summary, ROI numbers, etc.). It distinguishes itself from the sibling tool 'download_blueprint' by noting that tool is for full financial analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides a when-not-to-use condition: 'For full financial analysis, use download_blueprint.' This helps the agent decide between siblings. It also implies when to use: when a summary is needed.

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

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

With no annotations, the description must carry the full burden of behavioral transparency. It implies a read operation but does not explicitly state safety (e.g., no side effects, no destructive actions), nor does it mention permission requirements, caching, or potential delays.

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 conveys the tool's purpose and its return contents. Every word adds value, with no redundancy or wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of this tool (one optional parameter, no output schema), the description adequately lists the key return fields. It lacks details on response structure or error handling, but for a basic get operation, it is nearly 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 input schema has one parameter (customerOrgId) with a description, achieving 100% schema coverage. The tool description does not add any additional meaning beyond identifying the returned fields, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'business profile for the organization', listing specific returned fields. However, it does not explicitly differentiate from sibling tools like get_blueprint or get_business_case, though the resource name is distinct.

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. There is no mention of prerequisites, when to choose this over other get_* tools, or any context-specific advice.

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?

Describes polling behavior implying idempotent reads, but lacks detail on error handling, rate limits, or effects of providing both IDs. No annotations present, so description bears full burden; moderate disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences with no redundancy. First sentence states purpose, second provides usage constraint, third gives follow-up action. Efficient 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?

Covers both poll use cases and next step. Missing details on output structure (e.g., status, blueprintId) but implied by download instruction. Adequate for a straightforward polling tool without output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover all parameters (100% coverage), but the description adds the critical mutual-exclusivity constraint (exactly one of auditId/jobId) not captured in schema. customerOrgId is not re-explained but schema suffices.

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?

Clearly states the tool polls blueprint or full-pipeline generation status, distinguishing between two distinct workflows. Instructs to call download_blueprint upon completion, providing actionable next-step context that differentiates it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly requires exactly one of auditId or jobId, and specifies the condition to call download_blueprint. However, does not compare to get_progress or other polling tools, nor mention when not to use this tool.

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

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

No annotations are present, so the description must carry the full burden. It indicates a read operation ('Get') and describes output, but does not disclose behavioral traits like authentication requirements, rate limits, or side effects. The description is adequate but limited.

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 that efficiently convey purpose and usage distinction. No extraneous 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?

With no output schema, the description appropriately lists return components (project overview, epic names, phases, story counts, timeline). It is mostly complete, though lacks mention of pagination or limits. For a summary tool, this is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers both parameters (blueprintId, customerOrgId) with descriptions, achieving 100% coverage. The description adds no additional parameter semantics, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get an implementation plan summary for a blueprint', specifying the verb and resource. It lists returned elements (project overview, epic names, phases, story counts, timeline) and differentiates from sibling 'download_blueprint' which provides full stories and dependencies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool (to get a summary) and when to use an alternative ('For full stories and dependencies, use download_blueprint'). This provides clear 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?

As a read operation with no annotations, the description adequately conveys that it returns metadata (agent count, platform, artifacts) and implies idempotent, non-destructive behavior, though it could explicitly mention its safe, read-only nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no waste: the first states the purpose, the second details the return content. Everything 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 tool with well-described schema, the description covers purpose and return fields adequately. It could mention error handling or that the tool is safe to call repeatedly, but is otherwise 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?

Schema coverage is 100% and both parameters are described clearly. The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and resource ('implementation spec for a blueprint'), clearly distinguishing it from sibling tools like 'get_blueprint' and 'get_implementation_plan'.

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 states what the tool does and what it returns, but does not provide explicit guidance on when to use it versus alternatives, or when not to use it.

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

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

With no annotations, the description carries the full burden. It discloses that the tool returns predicted targets, latest actuals, deviation analysis, and implementation state conditionally (dependent on sync_implementation_state). This is transparent about the data and dependency, though it could explicitly state it's read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences (40 words), front-loaded with the purpose, and contains no redundant information. Every word contributes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately covers return values (predicted targets, actuals, deviation, implementation state). It also mentions the dependency on sync_implementation_state. Minor gaps: no details on error cases or the exact format of deviation analysis, but it's sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description does not add additional meaning to the parameters beyond what the schema already provides (blueprintId and customerOrgId).

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: retrieving implementation progress and performance metrics for a blueprint, including predicted targets, actual measurements, deviation analysis, and implementation state. It distinguishes from siblings by mentioning the dependency on sync_implementation_state for the state portion, though it doesn't explicitly differentiate from other getters like get_implementation_plan.

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 includes a usage statement: 'Use this to check how an implementation is tracking against the plan.' It provides context but does not specify when not to use this tool or mention alternatives among the siblings.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions regeneration capability via ?force=true (though undocumented) and implies a read operation. It does not discuss side effects, rate limits, or error states. The dependency on prior sync is disclosed, but the behavior around performance metrics and AI landscape changes is not detailed.

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 consists of three concise sentences, front-loaded with the core purpose. Each sentence adds essential information: what it does, what it returns, and prerequisites. There is no fluff or repetition.

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 complexity (2 parameters, no output schema), the description covers key aspects: inputs, outputs, prerequisite, and regeneration capability. It provides sufficient context for an AI agent to decide when to invoke this tool versus siblings like sync_implementation_state. The lack of output schema is partially compensated by the mention of 'prioritized, actionable recommendations.'

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 100% (both parameters have descriptions), so baseline is 3. The description adds no value for the defined parameters (blueprintId, customerOrgId) and instead introduces a non-existent parameter 'force' via ?force=true, which could mislead an AI agent. This inconsistency reduces the score below baseline.

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 gets strategic recommendations for a blueprint, specifying the inputs (implementation state, performance metrics, AI landscape changes) and output (prioritized actionable recommendations). It distinguishes from siblings by mentioning the prerequisite sync_implementation_state, but does not explicitly compare to other get tools. The verb 'get' combined with 'recommendations' is specific and 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 explicitly states a prerequisite: 'Requires implementation state to be synced first via sync_implementation_state.' This guides when to use the tool. However, it also mentions '?force=true to regenerate' which implies a parameter not present in the input schema, creating confusion. There is no guidance on when not to use or alternatives to other 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?

With no annotations, the description carries full burden. It discloses the return content but omits behavioral traits like idempotency, authentication requirements, or performance characteristics. The 'get' prefix implies read-only, but this is not explicit.

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 efficiently states purpose and return items. No redundancy or filler. Front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description covers the tool's purpose and return items, it lacks output schema and omits details on return structure, pagination, or error scenarios. For a read tool in a context with many siblings, more completeness would benefit the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with both parameters documented. The description adds no further semantics beyond the schema. Baseline 3 is appropriate since the schema already provides adequate parameter context.

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 use case analysis linked to a blueprint and lists returned items (business challenge, success metrics, ROI estimate, strategic alignment). This distinguishes it from sibling 'get' tools like get_blueprint or get_business_case.

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. While the description implies it's for use case retrieval, it does not provide decision criteria or exclusions, leaving the agent to infer usage context.

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

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

No annotations provided, so description carries burden. It states it returns summaries but does not disclose pagination, rate limits, authorization needs, or whether it lists all blueprints for the organization or only accessible ones.

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, front-loaded with the action, 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?

For a simple list tool with no output schema, description adequately explains return fields. However, missing details on pagination, ordering, and scope (all vs filtered) reduce completeness mildly.

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 100% with one parameter well-described. Description does not add meaning beyond schema; it merely lists return fields. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and resource 'blueprints', specifying it returns summaries with explicit fields. It distinguishes from sibling tools like get_blueprint (singular) and download_blueprint.

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 vs alternatives like get_blueprint or search. The purpose is implied but not compared to other listing or retrieval 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?

With no annotations, the description carries the full burden. It reveals that the tool 'Clears staleness on the business case', indicating a state change. However, it does not disclose other behavioral traits like auth requirements, potential side effects beyond staleness clearing, or whether it modifies data persistently. 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 two sentences long, both essential. The first sentence defines the core function, and the second provides usage context and a side effect. No unnecessary words 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?

Given no output schema, the description could briefly mention what the tool returns (e.g., updated financials or status). However, for a recalculation tool in a business context, the description covers the main inputs and purpose. It is fairly complete for its simplicity, but a hint about the output would improve completeness.

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 100%, so the schema already documents both parameters. The description adds minimal extra meaning: it implies that blueprintId is used to identify the current blueprint and that customerOrgId might be needed for partner access. This is consistent with the schema but does not provide new semantics beyond what is already stated.

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 'Recalculate business case financials', the resource 'business case financials', and the source data 'from current blueprint and profile data'. It also specifies the outcomes: 'refresh ROI projections, labor savings, and payback period', which differentiates it from siblings like get_business_case or update_business_case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this after updating the blueprint' and lists the refreshed fields, providing clear when-to-use guidance. It does not explicitly mention when not to use it, but the positive context is strong enough for an AI agent to infer appropriate 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?

Discloses behavioral traits like auto-resolving targets and returning deviation analysis, and supports multiple metrics. However, without annotations, it omits details on side effects (e.g., whether it persists data) and authentication requirements, making it 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?

Three sentences efficiently convey purpose, mechanism, and usage context with no redundancy. Front-loaded with the core action.

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?

Provides enough context for an AI agent to understand when to use this tool and what it returns (deviation analysis). Lacks details on idempotency or side effects, but given no output schema, the description is reasonably 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?

Schema coverage is 100%, so baseline is 3. Description adds no extra meaning beyond parameter descriptions in the schema (e.g., it does not elaborate on how metrics are structured or expected formats).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action ('report actual performance metrics') and resource ('blueprint'), distinguishes from sibling tools by focusing on post-implementation tracking, and explains the auto-resolution and deviation analysis.

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?

Directly advises to use 'after implementing agents to track whether they hit their success criteria', providing clear context. Does not explicitly name alternatives but implicitly distinguishes from other 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?

No annotations provided, so description must convey behavioral traits. It states it syncs and creates a versioned snapshot, but does not disclose auth needs, rate limits, whether it overwrites or appends, or how conflicts are handled. Significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences: first states action, second explains what it reports, third highlights versioning. No wasted words, front-loaded with essential info.

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 complex nested schema and no output schema, the description covers high-level purpose and outcome (versioned snapshot) but omits return value details, error conditions, and idempotency. Adequate but not 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?

Schema coverage is 100%, so baseline is 3. The description says it reports agent status, artifacts, deviations, which aligns with stateData, but adds no meaning beyond the schema for blueprintId or customerOrgId. Minimal added value.

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 syncs implementation state back to Agent Blueprint, reports agent status, artifacts, deviations, and creates versioned snapshots. This distinguishes it from sibling tools like update_implementation_plan or report_metric.

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 on when to use this tool versus alternatives (e.g., update_implementation_plan, report_metric). It does not mention prerequisites or scenarios where it should be avoided.

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

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

With no annotations, the description reveals that the tool is asynchronous and returns a jobId. However, it does not disclose potential side effects, required permissions, or what happens to existing data. More behavioral context is needed.

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 core purpose and includes essential async/polling guidance. No unnecessary 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?

The description covers the return value (jobId) and the async workflow, but lacks details on the pipeline's steps, output artifacts, or how to interpret results. Given the lack of output schema, slightly more context would be beneficial.

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 100%, so the description adds limited value beyond what is already in the schema. It does not elaborate on optional parameters like specialInstructions or platform beyond their names.

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 starts the full pipeline for an existing business profile, runs use cases through implementation plan generation, and returns a jobId for polling. This verb+resource combination is specific and distinguishes from siblings like generate_use_cases or get_generation_status.

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 explains the asynchronous nature and suggests polling for status, but does not provide explicit when-not-to-use guidance or alternatives for similar tasks. It is clear but lacks exclusion criteria.

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?

Without annotations, description discloses key behaviors: shallow merge, version snapshot creation, and staleness propagation. However, lacks details on permissions, error conditions, or return 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?

Three sentences, front-loaded with primary action, includes key details without redundancy. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, merge behavior, side effects, and usage context. Lacks output specification (no output schema) and error handling, but acceptable given 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 coverage is 100% (baseline 3). Description adds meaning by explaining sections are 'full top-level sections' and 'shallow-merged', providing operational context beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it updates blueprint sections with implementation data and distinguishes from siblings like update_business_case by specifying 'blueprint sections'. The phrase 'Use this when the implementation diverges from the original recommendation' adds specific context.

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?

Provides explicit guidance on when to use ('when the implementation diverges from the original recommendation') and implies side effects (propagates staleness to business case and implementation plan), but does not explicitly exclude alternatives or state when not to use.

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 discloses key behavioral traits: shallow merge, propagation of staleness, and suggestion to recalculate financials. Since no annotations are provided, the description carries full burden. It lacks return value details but is otherwise transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences with no wasted words: first sentence states purpose, second explains behavior and side effect, third suggests follow-up. Well-structured and 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?

For a tool with 3 parameters and no output schema, the description covers the merge behavior, side effect on implementation plan, and follow-up action. It could mention return value or error conditions but is sufficiently 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?

Schema description coverage is 100%, giving a baseline of 3. The description adds value by explaining the sections merging behavior and listing common keys, which goes beyond the schema's propertyNames description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates business case sections with a specific verb and resource, and explains the shallow-merge behavior. It distinguishes itself from sibling tools like recalculate_financials.

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 usage context by explaining the merge and side effect (propagates staleness), and suggests calling recalculate_financials after updating. However, it does not explicitly contrast with other update tools like update_blueprint or when to avoid using this tool.

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

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

No annotations are provided, so the description bears full responsibility. It discloses side effects: propagates staleness to use cases and syncs company name to organization record. These are important behavioral traits beyond the core update action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the primary purpose. Each sentence provides unique information (update details, staleness propagation, name sync). No unnecessary 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?

The description lacks information about the return value or response format, and does not explain what happens after the update beyond the mentioned side effects. With no output schema and moderate complexity, this is a notable 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 input schema covers 100% of parameters, so baseline is 3. The description adds value by listing example valid keys and mentioning the sync behavior, which goes beyond the schema's field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it updates business profile fields, lists examples, and distinguishes from siblings like create_business_profile and get_business_profile. The action and resource are specific.

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 updating business profile fields but does not explicitly state when to use this tool versus other update tools (e.g., update_blueprint) or provide 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?

No annotations present, so description carries full burden. It clearly states 'shallow-merges' and 'terminal artifact' providing key behavioral insight beyond schema. Could mention idempotency or permissions.

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, each serving a distinct purpose: action and behavioral note. No unnecessary 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?

Explains merge behavior and staleness impact, but no mention of return value or error states. Adequate for a simple update tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all parameters are well-documented in the schema. The description adds minimal extra meaning beyond the schema's 'Top-level sections to merge'.

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 'Update' and resource 'implementation plan sections', and clarifies the merge behavior, distinguishing it from sibling update tools like update_blueprint.

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 mentions 'terminal artifact with no downstream staleness propagation', offering some guidance on when it's safe to use, but lacks explicit when-to-use vs alternatives 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?

The description mentions the key behavioral side effect of propagating staleness to the blueprint, which adds value beyond the schema. However, it omits details such as whether the use case must exist, authorization requirements, or error handling. With no annotations, more transparency is expected.

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 extremely concise (two sentences, 18 words) with the key action upfront and the side effect in the second sentence. Every word is informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description covers the basic action and one side effect, it lacks information about response format, error conditions, and the nature of the update (partial vs full). Given the nested object parameter and lack of output schema, the description is not sufficiently complete for an agent to use reliably without additional 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 description coverage is 100%, so the baseline is 3. The tool description does not elaborate on any parameters beyond what the schema provides. No additional semantic information is added.

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 ('Update use case fields for a blueprint') and specifies the relationship to the blueprint. It distinguishes from sibling tools like 'update_blueprint' by focusing on use case fields.

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 like 'get_use_case' or 'update_blueprint'. It does not mention prerequisites or exclusions.

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