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Classify post-write schematic QA results

easyeda_post_write_qa
Idempotent

Run post-write schematic QA that classifies DRC/ERC results using policy-aware rules, reporting duplicate nets, floating pins, and unconnected pins as pass/fail/inconclusive.

Instructions

Run and classify post-write schematic QA after generated edits. Combines native DRC/ERC results with policy-aware classification so duplicate net names, free networks, and unconnected pins are reported as pass/fail/inconclusive instead of raw warning counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drcNoOptional explicit DRC result override for tests or log ingestion
ercNoOptional explicit ERC result override for tests or log ingestion
policyNocircuit
projectIdYes
useNativeChecksNo
manualDrcMessagesNoOptional user-copied EasyEDA DRC log lines for classification when native details are unavailable
manualErcMessagesNoOptional user-copied EasyEDA ERC log lines for classification when native details are unavailable

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
issuesYes
passedYes
policyYes
statusYes
summaryYes
categoriesYes
project_idYes
fatal_countYes
issue_countYes
detail_sourceNo
warning_countYes
inconclusive_countYes
Behavior4/5

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

Description discloses that it combines DRC/ERC results and classifies them, which aligns with idempotentHint. It does not contradict annotations. Could mention that rerunning is safe (idempotent) but overall good.

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?

Two sentences, highly concise and front-loaded with the core purpose. No unnecessary words.

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

Completeness3/5

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

Description covers the main output format but omits details on required projectId, policy enum options, and use of manual messages. Given the tool's complexity (7 params, nested objects), more context would help.

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

Parameters2/5

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

Schema coverage is 57%, but description adds no extra meaning for parameters like 'policy' or 'useNativeChecks'. Critical parameters are not explained, leaving the agent to rely solely on the schema's brief descriptions.

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?

Description clearly states the verb ('run and classify'), resource ('post-write schematic QA'), and context ('after generated edits'). It differentiates from sibling tools like easyeda_drc_run by specifying policy-aware classification and output format (pass/fail/inconclusive instead of raw counts).

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?

Implied usage as a post-write step, but no explicit guidance on when to use this tool versus alternatives (e.g., raw DRC/ERC runs). No exclusions or scenario examples provided.

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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