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name: r1v4-api-testing description: "Draft, inspect, parse, and summarize Skywork R1V4 API batch tests without leaking API keys." disable-model-invocation: true metadata: disco-role: operating license: MIT

R1V4 API Testing

Use this sub-skill when you need to prepare Skywork R1V4 API batch tests, dry-run request payloads, parse tagged tool-use responses, summarize result JSONL, or troubleshoot the batch viewer safely.

Start here

1. Read references/api-batch-workflows.md for the four batch modes and Chinese terminology.
2. Check references/data-formats.md for test_cases.jsonl, request payload, and result JSONL schemas.
3. Validate input cases with scripts/validate_cases.py before any API run.
4. Build a no-network payload preview with scripts/build_api_payload.py.
5. Parse a tagged response or a result file with scripts/parse_r1v4_response.py.
6. Summarize a result JSONL with scripts/summarize_results.py.

Bundled files

• references/api-batch-workflows.md — workflow map for batch_nonstream.py, batch_stream.py, batch_planner_nonstream.py, and batch_planner_stream.py.
• references/data-formats.md — input/output schemas and tagged response grammar.
• references/result-analysis.md — safe headless analysis path and visualizer guidance.
• references/troubleshooting.md — API, image, stream, parse, and viewer failure modes.
• scripts/validate_cases.py — schema and optional image-path validation.
• scripts/build_api_payload.py — OpenAI-compatible payload builder with data URL support.
• scripts/parse_r1v4_response.py — tagged response parser and JSONL parser CLI.
• scripts/summarize_results.py — batch result counters and response-length summary.

Routing notes

• Use skywork/r1v4-lite for the regular batch modes and skywork/r1v4-vl-planner-lite for planner batch modes.
• Keep the message order as image first, then text.
• Bundled helpers do not make live API calls by default.
• Leave API keys to env or caller config; do not hard-code them in payloads or scripts.
• Use the bundled summary helper instead of copying the full Flask viewer into a workflow.
• Route local Transformers/vLLM inference, CUDA setup, and model-weight issues to the sibling local-inference sub-skill.
• Route VLMEvalKit, EMMA, MMK12, and benchmark reproduction tasks to the sibling evaluation-reproduction sub-skill.