Frasma

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 fully covered. The description adds the list of returned content, which is more about output than behavior, and no additional traits such as localization defaults are mentioned beyond the schema. It does not contradict 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?

A single sentence states the verb, resource, and content components without any filler. The most important information is front-loaded, 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?

This is a simple read-only getter with one optional parameter, full schema coverage, an output schema, and comprehensive annotations. Nothing an agent needs to invoke it correctly is missing from the available structured data.

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 the only parameter 'locale' fully documented by an enum and a default. The tool description adds no parameter-specific meaning, but with full schema coverage the baseline 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 the specific verb 'Returns' with a clear resource ('diagnostic framework') and enumerates the framework's contents: diagnostic method, evidence to collect, fit criteria, and commercial limits. It is clear enough to separate from sibling tools like get_frasma_profile or search_frasma_knowledge, though it does not explicitly name an alternative.

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 guidance on when to use this tool versus the siblings, nor any mention of prerequisites or exclusions. The description only states what is returned, leaving the agent to infer appropriate usage from the tool name and context.

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

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the safety profile is fully handled. The description adds useful context by specifying that the profile is 'verified public' and enumerating the distinct content categories returned, which signals the scope and sensitivity of the data. Nothing in the description contradicts the annotations.

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

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

The description is a single front-loaded sentence with a clear verb and a concrete list of returned content. There is no filler, repeated tool name, or redundant restatement of schema details.

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 zero required parameters, one optional locale, a full output schema, and annotations covering side effects, the description plus schema provide everything an agent needs to decide whether and how to call it. No hidden prerequisites, caveats, or return-value explanations are needed.

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%: the sole parameter 'locale' is fully documented with its enum values and default. The description does not add parameter-level detail beyond the schema, so the baseline score of 3 applies.

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

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

The description uses a specific verb ('Returns') and names a unique resource: the verified public profile for Frasma, including focus areas, sectors, commercial boundaries, and discovery URLs. This makes it clearly distinguishable from sibling tools like get_diagnostic_framework or search_frasma_knowledge without needing to open their schemas.

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 intended use is implied: call this when you need Frasma's public profile or commercial-boundary data. However, there is no explicit statement of when to prefer this tool over alternatives or any exclusions. For a simple read-only lookup this is acceptable, but the guidance is not fully explicit.

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

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, so the description does not need to repeat that. It adds value by disclosing that no email is sent and that the actual POST is deferred until user confirmation, clarifying side-effect boundaries 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?

Three short sentences with the main action first, a side-effect disclaimer second, and workflow guidance third. There is no redundant restating of schema or annotations.

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 20-parameter tool, the description gives the essential orchestration context: it validates a summary, returns a payload, sends nothing, and is a prerequisite to a user-confirmed POST; the output schema and parameter schema cover the remaining details. The ambiguous 'process brief' mapping and lack of validation-criteria detail keep it from a 5.

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 parameters are already fully documented with rich descriptions, giving a baseline of 3. The tool description adds no additional parameter-level semantics; the only adjacent hint, 'Map the diagnosis to a process brief,' is too vague to clarify any specific argument.

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 first sentence states a concrete action: validates a complete diagnostic summary and returns a handoff payload, and 'Does not send email' narrows the scope. However, it does not clearly distinguish itself from the prepare_project_brief sibling, and the instruction 'Map the diagnosis to a process brief' blurs the tool's exact 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?

It gives useful when-to-use context: this is a validation/handoff step, not an email or submission action, and it must precede POST /api/request-process-assessment only after user confirmation. It does not explicitly name alternatives or state when to prefer prepare_project_brief, so the guidance is clear but not exhaustive.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds concrete behavioral boundaries beyond those: it does not send email, and it must be followed by a user-confirmed POST. Validation-failure behavior is not described, but the output schema reduces that 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 two short sentences with three clear clauses. It is front-loaded with the core purpose and includes only high-value information: what is validated, the no-email side effect, and the required next step.

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 output schema, full parameter coverage, and annotations, the description is nearly complete: it identifies the input groups, side-effect boundaries, and next action. Explicitly naming or contrasting with prepare_diagnostic_summary would make it fully complete, but the current content is sufficient 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 100%, with each parameter already documented. The description only groups parameters into required and optional sets, adding no new semantic meaning beyond the schema, so the 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 states a specific verb ('validates'), resource ('process brief'), and context ('used for a quote'), and lists the fields involved. It is clear overall, but it does not explicitly differentiate from the sibling tool prepare_diagnostic_summary, so it stops short of a 5.

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

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

The description gives clear context: this tool validates before the actual POST, does not send email, and requires user confirmation first. It lacks explicit when-not-to-use guidance or named alternatives, but the workflow placement is unambiguous.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that the knowledge is 'verified' and lists the semantic scope, but it does not describe behavioral details such as result limits, pagination, or how to interpret absent matches.

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 short sentences with no filler. The first states the tool's scope, and the second provides a crisp usage directive. 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?

The description, combined with full schema documentation and rich annotations, gives an agent enough to select and call the tool correctly. The only minor gap is not mentioning sibling-tool alternatives, but 'Use before making factual claims' already anchors the primary use case.

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

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

Schema description coverage is 100%, so the input schema fully documents query, locale, and pagePath. The description itself adds no parameter-level meaning beyond the schema, 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 uses a specific verb ('searches') and names a concrete resource ('verified Frasma services, sectors, case studies, methodology, fit criteria, and commercial boundaries'). It clearly distinguishes itself from the get_/prepare_ sibling tools by framing this as a knowledge retrieval operation rather than a profile or document generation 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 gives direct usage guidance: 'Use before making factual claims.' This tells an agent when the tool is appropriate, though it does not explicitly mention alternatives or exclusions. This is clear practical context for tool selection.

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