scoring

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds limited behavioral context beyond the endpoint. It does not mention any potential side effects or limitations, but no contradictions exist.

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, clear sentence with no unnecessary words. It is front-loaded with the action and resources.

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 provides a reasonable outline of the return content (plan limits, trial quota, upgrade state). It is complete for a simple retrieval tool with strong annotations.

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

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

There are zero parameters, so the input schema is fully covered. The description does not need to add parameter details, and the baseline score of 4 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 clearly states the action 'Retrieve' and the resources 'plan limits, trial quota, and upgrade state', specifying the exact endpoint. It effectively distinguishes from sibling tools like 'get_usage' by naming the specific data retrieved.

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 minimal usage guidance by stating the purpose and endpoint, but it does not explicitly mention when to use this tool versus alternatives like 'get_usage' 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?

Annotations already indicate readOnlyHint and idempotentHint. Description adds HTTP method but no additional behavioral traits (e.g., data freshness, error handling).

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

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

One succinct sentence, front-loaded with key information. No wasted 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?

For a simple tool with one optional parameter and no output schema, the description is mostly adequate. Missing typical return value shape, but not critical.

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% for the single parameter 'month'. Description adds no extra meaning beyond the schema's 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?

Description clearly states verb 'retrieve' and resource 'monthly scoring call usage', and includes the HTTP method and path. It is distinct from sibling tools like get_limits.

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 instead of alternatives (e.g., get_limits for limits). The description only states what it does.

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 read-only, idempotent, and not open-world. Description adds HTTP method (GET) and endpoint path, providing context beyond annotations. No behavioral contradictions.

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?

Single concise sentence containing all essential information: action, resource, and what is returned. No filler or redundancy.

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

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

Given the tool's simplicity (1 param, no output schema), the description covers all necessary context: what is fetched, from where, and the return contents. No 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 covers 100% of the single parameter with a clear description. Description adds no extra meaning beyond the schema, so 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?

Description clearly states the action (Fetch), resource (workflow schema), and specific outputs (required fields, optional fields, enums, example payload). It uniquely distinguishes from sibling tools like list_workflows or validate_workflow_payload.

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?

Description implies usage when schema details are needed, but does not explicitly state when to use this tool versus alternatives (e.g., validate_workflow_payload for validation). No when-not-to-use or exclusion 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds little behavioral insight beyond the HTTP method GET. It does not disclose rate limits, pagination, or other traits, but the annotations cover the core safety profile.

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

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

The description is a single sentence, front-loaded with the action and resource, with no wasteful words. It is maximally concise.

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 fully explains the purpose (listing workflows and model versions) for a parameterless tool. No output schema exists, so the description must cover return values, which it does adequately. However, it could mention the endpoint format for 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 description coverage is 100% with zero parameters, so baseline is 3. The description adds no parameter info, but none is needed.

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 lists supported workflows and current model versions, with a specific verb 'list' and resource 'workflows and model versions'. It distinguishes from sibling tools like get_workflow_schema or score_workflow, which are more 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 provides no guidance on when to use this tool versus alternatives like get_workflow_schema. Usage is implied by the action, but no exclusions or context are given, so the agent must infer.

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 states a writing operation (scoring items) but annotations declare 'readOnlyHint: true', a direct contradiction. Additionally, the description lacks disclosure of key behaviors like error handling, idempotency details, or limits beyond the item count.

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

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

The description is a single, efficient sentence with no wasted words. It clearly communicates the key aspects of the tool.

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 an output schema and the presence of a sibling with similar purpose ('score_workflow'), the description is somewhat minimal. It does not explain return values, error behavior, or how this tool fits with others, but annotations partially compensate.

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 any parameter-specific details beyond what the schema already provides, such as the structure of 'items' or the effect of 'continue_on_error'.

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 the action ('Score up to 25 workflow items') and the HTTP method/resource ('POST /v1/score/batch'), clearly distinguishing it from the sibling 'score_workflow' which likely handles single items.

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 batch usage with a limit of 25 items and sequential processing, but does not explicitly contrast with 'score_workflow' or explain when to use one over the other. No guidance on prerequisites or error handling.

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 and idempotentHint, indicating the tool does not modify state. The description adds the HTTP method (POST) but does not elaborate on potential side effects, authorization needs, rate limits, or response behavior. The claimed read-only nature via POST could be seen as slightly contradictory, but it is not flagged as a contradiction since scoring might be a side-effect-free operation.

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 fluff, making it concise. However, it could be slightly more informative without losing efficiency, such as hinting at the type of workflows or the purpose of scoring.

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 nested objects, no output schema, and multiple sibling tools with similar purposes, the description is too minimal. It does not explain the return value, provide context on when to use this vs score_batch, or clarify the payload format, leaving significant gaps for an AI 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?

The input schema covers 100% of parameters with descriptions, so the parameter semantics are already well-defined. The description adds no extra meaning beyond what is in the schema, falling to the baseline of 3. It does not explain the structure of the payload or provide examples.

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 ('Score'), the resource ('Sentinel healthcare workflows'), and the method ('via POST /v1/score'). It is specific enough to distinguish from tools like list_workflows or get_workflow_schema, but it does not differentiate from the sibling score_batch tool, which performs a similar action.

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

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

No guidance is provided on when to use this tool versus alternatives such as score_batch for batch scoring or validate_workflow_payload for validation. The description lacks any context about prerequisites, typical workflows, or exclusion scenarios.

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 provide minimal behavioral hints (all false). The description adds no additional behavioral context, such as whether the submission is idempotent, what side effects occur, or what errors might arise. It merely restates the 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?

The description is a single, concise sentence that front-loads the purpose and includes the HTTP method. No extraneous 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 the required nested object and no output schema, the description lacks details on expected feedback structure, constraints, or return values. It is incomplete for a submission tool that likely produces a confirmation or error response.

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 covers the single parameter 'feedback' with a description. The tool description adds no further semantic value beyond the schema. With 100% schema coverage, 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 (Submit) and resource (structured claims outcome feedback) and specifies the HTTP method and endpoint. However, it does not differentiate from sibling tools like score_batch or score_workflow, which might also deal with scoring outcomes.

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 after a scoring event ('for a prior Sentinel scoring event'), but it does not explicitly state when to use this tool versus alternatives like score_batch 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, describing the tool as safe. The description adds that it uses a POST endpoint, but does not elaborate on behavior like error handling or side effects beyond normalization.

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

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

One sentence that is front-loaded with the action and includes the HTTP method and endpoint. Every word contributes meaning; 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?

The description does not mention the return value or output format. Since there is no output schema, the agent relies on the description for what the tool returns (e.g., validation errors, normalized payload). This omission leaves the agent guessing.

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 descriptions for both parameters. The description restates the purpose of the payload parameter ('workflow payload to validate') but adds no extra meaning beyond what the schema provides. 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 'Validate and normalize' and the resource 'workflow payload', and distinguishes from siblings by specifying 'without consuming a scoring call'.

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?

Implicit usage context is given (use for validation before scoring), but no explicit when-not-to-use or alternative tools are mentioned. The mention of 'without consuming a scoring call' hints at when to prefer this over score_workflow.

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