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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, signaling a safe read-only operation. The description adds the specific focus and inputs, but does not disclose additional behavioral traits such as whether it returns a numeric range or a structured estimate, or whether it uses heuristics. However, given the annotations, the description is not misleading, and the extra context about inputs is useful.

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 the primary action ('Estimate a transparent capacity envelope'). It lists the key inputs without unnecessary detail. It could be argued it is slightly under-specified regarding usage, but what is written is efficient and clear.

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 has an output schema and simple parameter (a single 'project' object), the description covers the essential purpose and inputs. However, the lack of guidance on when to use it, and the opaque 'project' parameter structure, leave room for improvement. The description is adequate for a basic understanding but not comprehensive.

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 schema provides no semantics for the single parameter 'project'. The description mentions the relevant fields (model, context, concurrency, growth), which partially compensates, but it does not explain the structure or expected format of the 'project' object. With only one parameter, the baseline for requiring description compensation is moderate, and the description provides some 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 states a specific verb ('Estimate') and resource ('capacity envelope'), and mentions the key inputs (model, context, concurrency, growth). It clearly indicates the tool performs an analysis. However, it does not explicitly distinguish it from siblings like 'assess_existing_infrastructure_tool' or 'recommend_architecture_tool', though the 'capacity envelope' focus helps.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives. The sibling list includes 'assess_existing_infrastructure_tool' and 'recommend_architecture_tool', but no conditions are given to select between them. The context hints that it analyzes inputs, but when to choose it over others is left entirely to inference.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety and side-effect profile. The description adds outcome context about identifying reuse and gaps, which aligns with the read-only behavior. It does not introduce any conflicting behavior and provides modest extra 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, focused sentence with no filler. It front-loads the core action and delivers the essential purpose efficiently. Every word contributes value, and no unnecessary information is present.

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 complex nested object parameters with no property descriptions, and the description does not clarify their structure or roles. Although an output schema exists, the input side is under-specified for an agent to invoke the tool correctly. The description explains what the tool does but not how to properly construct the required inputs.

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 carries the full burden of explaining parameters. It mentions 'declared infrastructure' and 'planning envelope' but fails to map these concepts to the actual parameters 'project' and 'existing_infrastructure'. An agent cannot determine which input is which or what fields are expected, making parameter usage ambiguous.

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 action: compare declared infrastructure with the planning envelope, and output reuse and gaps. It uses a specific verb and resource, making the tool's purpose unmistakable. However, it does not explicitly differentiate itself from sibling tools like analyze_inference_project_tool or recommend_architecture_tool, so sibling distinction is left to inference.

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: this tool is intended for situations where there is declared infrastructure and a planning envelope to compare against. However, it provides no explicit when-to-use instructions, no exclusions, and no mention of alternatives among the sibling tools. The usage context is reasonable but not explicitly stated.

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

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context beyond the annotations by stating the tool compares evidence completeness and known costs and explicitly avoids fabricating a winner, which sets expectations for the kind of output it produces.

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 sentence delivers the purpose and a behavioral caveat with no filler. The main comparison dimensions are front-loaded before the caveat, and 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 low-complexity tool with one parameter and rich annotations, the one-line description is near-minimal but leaves gaps: the expected shape/content of 'boms' is undocumented and 'evidence completeness' and 'known costs' are not defined. The presence of an output schema reduces the need to explain return values, but the description still lacks enough detail for confident invocation without further 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 provides 0% description coverage and the sole parameter 'boms' has no defined properties beyond an array of arbitrary objects. The description implies the array contains BOM options but does not explain what fields each BOM object should have, how evidence completeness or known costs are represented, or what structure is expected.

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 uses a specific verb ('Compare'), a clear resource ('BOM options'), and specifies the dimensions ('evidence completeness and known costs'). The phrase 'without fabricating a winner' clarifies it is an evaluative comparison rather than a generation tool, distinguishing it from siblings like generate_bom_tool and recommend_architecture_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 the tool should be used when comparing multiple BOMs on evidence and cost, which is some guidance. However, it does not explicitly state when to prefer this tool over siblings such as screen_bom_for_compliance_tool or generate_bom_tool, and gives no 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 adds meaningful behavioral context beyond the annotations: it states that product, price, and origin fields will remain unknown without evidence, which tells the agent the tool will not fabricate or infer those values. This complements the readOnlyHint and idempotentHint annotations without contradicting 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 that conveys the core purpose and a key behavioral constraint with no filler. Every part earns its place.

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

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

The tool has an open, nested 'project' parameter, no output schema, and zero schema-level parameter descriptions, yet the description does not explain what a valid project looks like, what 'specification-first' means operationally, or what the BOM output contains beyond the mentioned unknown fields. The description is too sparse to fully equip an agent to call this 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?

Schema description coverage is 0%, so the description carries the burden of explaining parameters, but it does not clarify the shape of the 'project' object or the allowed values/behavior of 'output_format'. The mention of product, price, and origin fields hints at output semantics but does not map to the input 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 names a specific verb ('Generate'), a concrete resource ('BOM'), and a distinguishing approach ('specification-first'), so an agent can tell it apart from sibling tools like generate_hardware_spec_tool or compare_bom_options_tool. The added note about product, price, and origin fields further sharpens the purpose.

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 'specification-first' implies the tool should be used when a specification is available and a BOM is needed, but the description gives no explicit when-to-use/when-not-to-use guidance and does not mention alternatives. Usage context is only implied, not stated.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful context about the plan's content (staged, verification, approval, rollback) but does not disclose additional behavioral traits such as side effects, output handling, or dependencies beyond what annotations already establish. No contradiction exists.

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, dense sentence that front-loads the primary action and deliverable. It contains no filler or repetition, and every word adds meaning. This is an example of efficient description writing.

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 one required parameter with no description, no usage context, and no guidance on input structure. Although an output schema exists, it is not shown, and the description does not cover input requirements or how the tool fits into the workflow with its many siblings. Significant information is missing 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?

Schema description coverage is 0%, and the description does not even mention the required 'project' parameter. The parameter is an open-ended object with additionalProperties=true and no field descriptions, leaving the agent with no information about what properties are needed or expected. This is a critical gap.

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 ('Produce') and names a concrete deliverable ('staged deployment, verification, approval and rollback plan'), which clearly distinguishes this from sibling tools like hardware spec, BOM, or architecture generation. An agent can immediately tell what the tool outputs.

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 given on when to use this tool versus alternatives. There is no mention of prerequisites, sequencing relative to sibling tools, or scenarios where this tool should be skipped in favor of another. The context is left entirely to inference.

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 useful scope context ('vendor-neutral') and the domains included, but it does not disclose additional behavioral details such as output format, error conditions, or assumptions about the project object.

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 with no filler or redundant statements. It front-loads the core action and resource, and every phrase contributes useful scope 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?

While annotations and output schema cover some context, the description leaves a major gap around the required project parameter and provides no guidance on workflow placement relative to siblings. For a tool with a nested unconstrained parameter and no schema documentation, this is insufficient for reliable 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 description coverage is 0%, and the description does not explain the required 'project' parameter at all. Since the parameter is a free-form object with additionalProperties true, an agent cannot determine what fields or structure are expected. The description must compensate for the missing schema information 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 uses a specific verb ('Generate') and clearly identifies the output as a vendor-neutral specification covering compute, memory, storage, network, power, cooling, and security. It distinguishes itself from siblings like generate_bom_tool, which targets a bill of materials, and recommend_architecture_tool. However, it does not explicitly contrast itself with these siblings, so it is clear but not fully differentiated.

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 its siblings such as analyze_inference_project_tool, recommend_architecture_tool, or generate_bom_tool. The context of a pipeline is implied by the sibling list, but the description does not state conditions, exclusions, or sequence.

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 readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context by specifying that the tool performs a comparison and returns a reasoned classification, alternatives, and risks. This is consistent with the annotations, and no contradiction exists.

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 states the action and the expected output without any filler. Every word contributes meaning, making it appropriately 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?

The output schema exists and annotations provide the safety profile, so return values and side effects are largely covered. However, the description still leaves clear gaps around when to use the tool and what the 'project' parameter must contain, making it minimally viable rather than fully self-contained.

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 required 'project' parameter at all. The schema only indicates a free-form object with additionalProperties true, so the agent receives no guidance on what fields or structure the project object should contain.

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: 'Compare integration patterns' and states the output as 'a reasoned classification, alternatives and risks.' It is clearly distinguishable from sibling tools like compare_bom_options_tool because it targets integration patterns rather than BOM options, though it does not explicitly name any sibling.

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 assess_existing_infrastructure_tool or analyze_inference_project_tool. It also gives no context about the workflow position or prerequisites, leaving the agent to infer usage solely from the tool 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?

Beyond annotations (which are all false hints), the description adds that the operation is a persist operation on non-secret artifacts and that it returns a content hash and resource URI. It does not disclose details about overwriting, storage behavior, authorization needs, or artifact size limits, so there is still a meaningful transparency 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 sentence with no redundant wording. It front-loads the core purpose and then adds the return behavior, earning its place with every phrase.

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 two-parameter tool with an output schema, the description is minimally viable: it says what to persist and what will be returned. Still, it leaves the artifacts object format unspecified and omits any operational context like whether artifacts are replaced, merged, or versioned. This is adequate but has clear 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?

Schema description coverage is 0%, so the description must carry parameter semantics. It broadly indicates that 'artifacts' are generated and non-secret, but it does not define the structure of the artifacts object, what values it may contain, or clarify project_id beyond the property name. This is insufficient for 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 uses a specific verb ('Persist') with a clear resource ('generated non-secret project artifacts') and states the return value ('content hash and resource URI'). It clearly distinguishes this tool from the sibling analysis, validation, and generation tools by framing it as a storage/persistence 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?

The description signals when to use the tool: for generated artifacts that are non-secret. It implicitly excludes secret artifacts and manual/non-generated artifacts, which gives solid context. However, it does not name an alternative tool or explicitly state when-not-to-use relative to a 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?

The description adds one behavioral rule beyond annotations: unknown origin fails if the policy requires evidence. However, it leaves ambiguity about what 'cannot pass' means and what happens with known origins. The annotations already cover read-only/idempotent/destructive safety, so the description adds some context but not full 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 front-loaded sentence with no filler words and both clauses carry meaning. It scores well on conciseness, though the extreme terseness contributes to the lack of helpful detail captured in other dimensions.

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 two required nested-object parameters with zero schema descriptions, an output schema that is not visible, and no usage guidance, the description is not complete enough. It leaves crucial questions about workflow configuration, policy structure, and pass/fail behavior unanswered.

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% for both parameters (bom and policy), so the description must compensate. It only implies that bom contains origins and policy may require evidence, but it gives no structural hints, allowed fields, nesting, or relationship between the two objects. This is insufficient for an agent to construct valid inputs.

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 conveys a general action ('Apply a configurable sourcing workflow') and a consequence ('unknown origin cannot pass a policy requiring evidence'), but it never explicitly names the BOM, compliance screening, or what 'pass' means. It is not a tautology, but the purpose is vague and does not distinguish the tool 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?

There is no stated when-to-use, no mention of alternatives, and no exclusion criteria. The phrase 'unknown origin cannot pass a policy requiring evidence' implies a compliance-checking use case, but it does not tell an agent when to choose this over sibling tools like compare_bom_options_tool or generate_bom_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?

The annotations already declare read-only, idempotent, and non-destructive behavior. The description adds non-obvious behavioral guarantees: it reports gaps and contradictions, and it will not fabricate values. This is useful context an agent can rely on when selecting and trusting the 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?

The description is a single sentence with no filler. The core action is front-loaded, and the behavioral constraint 'without inventing values' adds meaningful information without bloating the 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?

The output schema and annotations cover return values and safety, but the input contract for `project` remains opaque. Combined with the lack of usage guidance, the description is adequate for basic selection but not fully sufficient for confident invocation in an unfamiliar 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?

Schema description coverage is 0%, and the lone `project` parameter is an open object with no property descriptions. The description only implies that the object should hold requirements; it does not clarify expected fields, nesting, or shape, so it does not compensate for the empty 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 action ('Validate and normalize') and names its object ('project requirements'), so the tool's purpose is immediately clear. It does not explicitly contrast with siblings like analyze_inference_project_tool, but 'without inventing values' signals a diagnostic rather than generative role.

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 about when to use this tool versus any of the nine siblings. The name and action imply it belongs early in a requirements-analysis workflow, but the description does not state when to prefer it or when to use an alternative.

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