chore: remove completed eval plan, extract architecture to .cards
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Plan fully implemented: CLI (run/report/diff/list), runner, 4 builtin judges, CAS storage, task loader, 6 test files. New card captures design decisions.
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---
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title: "Eval Architecture — Task + Judge + CAS"
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created: "2026-06-07"
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source: "openclaw-xiaomo"
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tags: [architecture, decision]
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category: "architecture"
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links:
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- eval-closes-the-trust-chain
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- agent-cli-protocol
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- frontmatter-fast-path
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---
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uwf-eval 的三层架构：
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1. **Task = 可分发的评估单元**（task.yaml + fixture 目录 + judge 脚本）。定义 prompt、workflow 引用、limits、judges 列表及权重。
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2. **Judge = 独立评分脚本**。`node <entry> <cwd> <thread-id>`，stdout 输出 `{score, data}` JSON。分 builtin（frontmatter 合规、upstream 消费、幻觉检测、token 统计）和 task-specific 两类。
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3. **CAS 存储**：每次 eval run 的结果是 OCAS typed node，支持 diff 对比不同 run。
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关键设计：uwf-eval **不是 uwf 的一部分**——它作为独立包 shell out 到 uwf CLI，保持解耦。Judge 之间独立，可并行执行。
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四个 builtin judges：
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- `frontmatter` — 确定性校验，每步 frontmatter 是否合规
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- `upstream` — LLM-as-judge，上游信息是否被消费
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- `hallucination` — LLM-as-judge，是否有幻觉
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- `token-stats` — 信息性指标，不参与评分
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# Eval Framework Implementation Plan
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## Goal
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Build `uwf-eval` CLI + eval task infrastructure for evaluating uwf workflow quality with real agents.
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## Architecture
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```
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uwf-eval (runner) task package (npm) OCAS (storage)
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│ │ │
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├─ unpack tarball ───────► fixture/ → tmp cwd │
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├─ read task.yaml │ │
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├─ uwf thread start/exec │ │
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├─ run judges ───────────► dist/judges/*.js │
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├─ collect scores │ │
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└─ store results ─────────────────────────────────────► CAS nodes + variables
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```
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### Key Design Decisions
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- **uwf-eval is NOT part of uwf** — separate package, shells out to uwf CLI
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- **Task = npm package** — fixture + task.yaml + judge scripts, distributable as tarball
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- **Judge = Node script** — `node <entry> <cwd> <thread-id>`, outputs `{score, data}` JSON
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- **Every output is OCAS typed** — eval-run, judge results all have registered schemas
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- **Builtin judges** — frontmatter compliance, upstream consumption, hallucination, token stats
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- **Task-specific judges** — bundled in the task package, custom schema per judge
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## Deliverables
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### Phase 1: Foundation (`@united-workforce/eval`)
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New package in the uwf monorepo.
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```
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packages/eval/
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src/
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cli.ts # uwf-eval entry point
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commands/
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run.ts # uwf-eval run
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report.ts # uwf-eval report <hash>
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diff.ts # uwf-eval diff <hash> <hash>
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list.ts # uwf-eval list
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runner/
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prepare.ts # unpack tarball/dir → tmp cwd
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execute.ts # shell out to uwf thread start/exec
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collect.ts # run judges, collect scores
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judge/
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types.ts # JudgeInput, JudgeOutput types
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builtin/
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frontmatter.ts # frontmatter compliance check
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upstream.ts # upstream info consumption (LLM-as-judge)
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hallucination.ts # hallucination detection (LLM-as-judge)
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token-stats.ts # token usage from $usage field (#68)
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storage/
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schemas.ts # OCAS schema definitions
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store.ts # CAS read/write helpers
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index.ts # variable indexing (@uwf/eval/*)
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task/
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types.ts # TaskManifest type (task.yaml)
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loader.ts # parse task.yaml, validate
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package.json
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tsconfig.json
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```
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#### OCAS Schemas to Register
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1. `@uwf/eval-run` — full eval execution record
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```
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{ task, config: {agent, model, engineVersion}, threadId,
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judges: [{name, score, weight, dataHash}], overall, timestamp }
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```
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2. `@uwf/eval-judge-frontmatter` — frontmatter judge data
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```
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{ stepsTotal, stepsValid, invalidSteps: [{stepIndex, role, errors: string[]}] }
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```
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3. `@uwf/eval-judge-upstream` — upstream consumption judge data
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```
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{ perStep: [{role, consumed: string[], missed: string[], score}] }
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```
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4. `@uwf/eval-judge-hallucination` — hallucination judge data
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```
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{ perStep: [{role, hallucinations: string[], score}] }
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```
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5. `@uwf/eval-judge-token-stats` — token stats (not scored, informational)
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```
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{ totalInput, totalOutput, totalTurns, perStep: [{role, input, output, turns, duration}] }
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```
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#### CLI Design
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```bash
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# Run eval
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uwf-eval run <task-dir-or-tarball> [--agent hermes] [--model claude-sonnet-4] [--count 20]
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# View results
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uwf-eval report <run-hash> # render via ocas render
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uwf-eval diff <hash1> <hash2> # side-by-side comparison
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uwf-eval list # list past runs
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```
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### Phase 2: Task Package Scaffold
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Template for creating eval tasks. Also serves as the first real task.
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```
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eval-tasks/ # shazhou/uwf-eval-tasks monorepo
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packages/
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_template/ # copypaste template
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package.json
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task.yaml
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fixture/
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src/judges/
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tsconfig.json
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fix-off-by-one/ # first real task
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package.json # @uwf-eval/fix-off-by-one
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task.yaml
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fixture/
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src/calc.ts # buggy calculator
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src/calc.test.ts # test that exposes the bug
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package.json
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src/judges/
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test-pass.ts # runs pnpm test, checks exit code
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code-quality.ts # LLM judge: minimal change, correct fix
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schemas/
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test-pass.json # OCAS schema for test-pass data
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code-quality.json # OCAS schema for code-quality data
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tsconfig.json
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pnpm-workspace.yaml
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tsconfig.json
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biome.json
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```
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#### task.yaml Format
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```yaml
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name: fix-off-by-one
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description: Fix an off-by-one error in a calculator's add function
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workflow: solve-issue # registered workflow name, or relative path to .yaml
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prompt: "Fix the bug: add(1,2) returns 4 instead of 3"
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limits:
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maxSteps: 15
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timeoutMinutes: 30
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judges:
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- name: frontmatter-compliance
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weight: 0.15
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builtin: true
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- name: upstream-consumption
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weight: 0.15
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builtin: true
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- name: hallucination
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weight: 0.1
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builtin: true
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- name: token-stats
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weight: 0 # informational, not scored
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builtin: true
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- name: test-pass
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weight: 0.3
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entry: dist/judges/test-pass.js
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schema: schemas/test-pass.json
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- name: code-quality
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weight: 0.3
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entry: dist/judges/code-quality.js
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schema: schemas/code-quality.json
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```
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#### Judge Script Contract
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```typescript
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// Input: process.argv = [node, script, cwd, threadId]
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// Output: stdout JSON
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// Exit 0 = success, non-zero = judge error (not low score)
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import type { JudgeOutput } from "@united-workforce/eval";
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const result: JudgeOutput<TestPassData> = {
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score: 1.0, // 0.0 - 1.0
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data: { // typed per judge schema
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command: "pnpm test",
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exitCode: 0,
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output: "3 tests passed"
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}
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};
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console.log(JSON.stringify(result));
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```
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### Phase 3: Prerequisite — $usage in Adapter Protocol (#68)
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Blocked by #68. Token stats judge needs `$usage` in step nodes.
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Can proceed with Phase 1+2 without it — token-stats judge just returns zeros until adapters report usage.
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## Implementation Order
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1. **Phase 1a**: `@united-workforce/eval` package scaffold + CLI skeleton + OCAS schemas
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2. **Phase 1b**: `run` command — prepare, execute, collect flow
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3. **Phase 1c**: Builtin judges — frontmatter (deterministic), upstream + hallucination (LLM-as-judge)
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4. **Phase 2a**: Create `shazhou/uwf-eval-tasks` monorepo with proman
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5. **Phase 2b**: First task `fix-off-by-one` with fixture repo + 2 custom judges
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6. **Phase 2c**: End-to-end test: `uwf-eval run packages/fix-off-by-one --agent hermes`
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7. **Phase 1d**: `report`, `diff`, `list` commands (read from CAS, render via ocas render)
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## Dependencies
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- `@ocas/core` + `@ocas/fs` — CAS storage
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- `@united-workforce/protocol` — step node types
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- `commander` — CLI framework (consistent with uwf)
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- LLM API access — for LLM-as-judge (upstream, hallucination, task-specific quality judges)
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## Open Questions
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1. **LLM-as-judge provider config** — reuse uwf's `~/.uwf/config.yaml` provider settings? Or separate config?
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2. **Workflow file location** — task.yaml references a workflow. Should the workflow YAML be inside the tarball, or reference a registered workflow by name?
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3. **Non-coding tasks** — debate workflow has no fixture repo. task.yaml needs `fixture: null` or simply omit the `fixture/` dir. Runner creates empty cwd.
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4. **Parallel judge execution** — judges are independent, can run in parallel. Worth the complexity?
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## Risks
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- LLM-as-judge consistency — same input may get different scores. Mitigation: run judge multiple times, take average? Or accept variance.
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- Token cost of judges — each LLM judge call costs tokens. For a 10-step workflow with 2 LLM judges = 20 LLM calls just for judging. Acceptable?
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- Fixture repo drift — if the fixture evolves, old eval runs become non-comparable. Pin fixture version in task.yaml.
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