submit_feedback
Submit structured claims outcome feedback via POST /v1/feedback
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | Yes | Structured feedback payload for a prior Sentinel scoring event. |
Submit structured claims outcome feedback via POST /v1/feedback
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | Yes | Structured feedback payload for a prior Sentinel scoring event. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, providing no safety or behavioral hints. The description simply says 'Submit' without disclosing effects such as whether feedback can be overwritten, duplicated, or what happens on invalid payloads.
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, direct sentence with a clear verb-first structure and no filler. It is appropriately concise for a simple 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?
For a tool with one parameter and no output schema, the description covers the core purpose but omits expected response behavior, error conditions, or the typical workflow context. It is acceptable but leaves 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?
The input schema already documents the single 'feedback' parameter well with a description referencing 'prior Sentinel scoring event.' The tool description adds the phrase 'claims outcome' but does not meaningfully enrich the semantic understanding 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 identifies the action ('Submit'), the resource ('structured claims outcome feedback'), and the transport method/endpoint ('POST /v1/feedback'). This is specific and distinct from sibling scoring tools like score_batch and score_workflow.
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 alternatives. It does not mention that feedback is intended for prior scoring events, nor does it explain any prerequisites or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct concern: account limits, usage, workflow schema, workflow list, single scoring, batch scoring, feedback, and payload validation. The only potential overlap (score_workflow vs score_batch) is clearly delineated by batch versus single operation.
All tool names follow a consistent verb_noun pattern with underscore separation (get_*, list_*, score_*, submit_*, validate_*). The naming convention is uniform and predictable.
With 8 tools, the server is well-scoped for a scoring API, covering account management, workflow discovery, scoring, validation, and feedback without unnecessary redundancy.
The tool set provides full lifecycle coverage for the domain: discovering workflows, fetching schemas, validating payloads, scoring (single or batch), checking account limits/usage, and submitting feedback. No obvious gaps exist.