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by SourceParts

dfm_add_findings

Add review findings to a DFM request by specifying category, severity, description, recommendation, and affected area for each finding.

Instructions

Add review findings to a DFM request (admin-only).

Each finding should include category, severity, description, recommendation, and affected_area. The API validates all fields and stores them in the dfm_review_findings table.

IMPORTANT: Review all findings before generating the customer report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesDFM review request ID (e.g. DFM-A1B2C3D4)
findingsYesList of finding dicts, each with: - category: e.g. design_issue, manufacturability, material - severity: info, low, medium, high, or critical - description: What the issue is - recommendation: How to fix it - affected_area: Which part of the design is affected - image_ref: (optional) reference to annotated image

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description discloses that the tool is admin-only, validates fields, and stores data in a specific table. It also includes a workflow tip about reviewing before report generation, adding behavioral context beyond the bare minimum.

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

Conciseness5/5

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

Three sentences with no fluff: first sentence defines purpose and restriction, second details finding structure, third gives an important workflow note. Front-loaded and efficient.

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

Completeness4/5

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

Given the existence of an output schema and high schema coverage, the description covers purpose, admin constraint, field expectations, and a workflow hint. It could mention idempotency or whether findings can be added incrementally, but is largely sufficient for a simple add operation.

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 coverage is 100%, so the baseline is 3. The description reinforces the required fields (category, severity, description, recommendation, affected_area) and adds the optional image_ref, but does not clarify the additionalProperties behavior in the schema. This provides marginal added value.

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

Purpose5/5

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

The description clearly states the action 'Add review findings' and the resource 'DFM request', with an explicit admin-only restriction. It distinguishes itself from sibling DFM tools like dfm_check_status, dfm_generate_report, and dfm_submit by specifying the add operation.

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 provides implicit guidance ('review all findings before generating the customer report') but does not explicitly state when to use this tool versus alternatives like dfm_submit or dfm_check_status. No direct comparison or exclusion criteria are given.

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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