design-ship vs langchain-eval-harness

Two General Claude Code skills, side by side. Pick the right skill for your workflow with a side-by-side look at metadata, sample code, and install commands.

Side-by-side

Tag overlap

Sample code from each SKILL.md

/ork:design-ship https://claude.ai/design/abc123     # From handoff URL
/ork:design-ship /tmp/handoff-bundle.json            # From local file

# evals/golden_set/v2026.04.jsonl
{"id": "gs-0001", "input": "Refund policy for SKU ABC-42?", "expected": "30 days with receipt", "contexts": ["policy_v3.md"], "tags": ["refund"], "difficulty": "easy", "dataset_version": "2026.04"}
{"id": "gs-0002", "input": "Return policy for opened software?", "expected": "No, opened software is final sale", "contexts": ["policy_v3.md#returns"], "tags": ["refund"], "difficulty": "medium", "dataset_version": "2026.04"}

When to choose each

design-ship — End-to-end Claude Design handoff to pull request: imports a handoff bundle from claude.ai/design, generates Storybook stories and Playwright tests, runs diff-aware browser verification, and opens a PR with the bundle…

langchain-eval-harness — Build reproducible evaluation pipelines for LangChain 1.0 chains and LangGraph 1.0 agents — golden datasets, LangSmith evaluate(), ragas RAG metrics, deepeval LLM-as-judge, agent trajectory analysis, and CI gating on…

Both are free to install. If you're unsure, install both — Claude Code skills are isolated by filename and only collide if their trigger phrases overlap (rare). The richest signal is the SKILL.md body itself — open both skill pages and read the first paragraph of each.

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