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propose_new_endpoint

Generate endpoint and DTO proposals by analyzing patterns in existing OpenAPI specifications to maintain consistency across API design.

Instructions

Create a best-effort endpoint + DTO proposal aligned with deterministic patterns found in the current OpenAPI spec.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
backendIdYesRequired backend id from list_backends.
resourceYesBusiness resource name, e.g. pet, order, invoice.
actionYesEndpoint action pattern.
customActionNameNoRequired when action=custom.
includePaginationNoAdd page/size params for list action.
specUrlNoOptional docs URL override for this call.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'best-effort' which hints at non-guaranteed results, but doesn't disclose critical behavioral traits like whether this is a read-only analysis or actually modifies the backend, what 'proposal' entails (e.g., returns structured data, generates code), error handling, or any rate limits. For a tool with no annotations and potentially complex behavior, this is a significant gap.

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

Conciseness4/5

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids repetition of parameter info already in the schema. However, it could be slightly more structured by explicitly separating endpoint and DTO aspects, but overall it's appropriately sized with zero waste.

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

Completeness2/5

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

Given no annotations, no output schema, and a tool that likely involves complex proposal generation (implied by 'best-effort' and pattern analysis), the description is incomplete. It doesn't explain what the output looks like (e.g., a JSON proposal, code snippets), success/failure conditions, or how it interfaces with the backend. For a 6-parameter tool with no structured output documentation, this leaves too many gaps for effective agent use.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional meaning beyond what the schema provides—it doesn't explain how parameters interact (e.g., backendId's role) or clarify semantics like 'deterministic patterns.' With high schema coverage, the baseline 3 is appropriate as the description doesn't compensate but also doesn't detract.

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

Purpose4/5

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

The description clearly states the tool creates a 'best-effort endpoint + DTO proposal' based on patterns in an OpenAPI spec, specifying both the action (create proposal) and resource (endpoint/DTO). It distinguishes from siblings like list_backends or get_endpoint_contract by focusing on proposal generation rather than listing or retrieving existing data. However, it doesn't explicitly contrast with generate_typescript_dto, which might have overlapping DTO-related functionality.

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

Usage Guidelines3/5

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

The description implies usage when needing to propose new endpoints aligned with existing patterns, but provides no explicit guidance on when to use this vs. alternatives like generate_typescript_dto or get_endpoint_contract. It mentions 'deterministic patterns found in the current OpenAPI spec' which suggests context, but lacks clear when/when-not rules or prerequisites beyond what the parameters imply.

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

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