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orca-onboard

orca-onboard

github.com/rheinmir开发10271 次安装2 周前更新
代码仓库

关于 orca-onboard

用于将代码库整理为可浏览文档的工作流技能,通过代码图谱、领域图谱、Wiki 和 HTML 文档进行引导式分析。分阶段执行并设有用户确认关卡,支持更新已有分析。

主要功能

  1. 01扫描代码并结合 Git 历史
  2. 02生成知识图谱与引导式导览
  3. 03构建领域图谱并检查覆盖率
  4. 04生成 Wiki 与 HTML 文档
  5. 05支持全量重建和增量更新

适用场景

  1. 01为新项目建立代码库概览
  2. 02梳理领域流程及其代码位置
  3. 03更新已有代码库分析与文档

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/rheinmir/setup --skill orca-onboard

安装后在 Claude Code 中输入/orca-onboard确认已加载。

附带文件assets/docs-site-skeleton.html

详细介绍

orca-onboard

🧭 调度后端 — 选择成本较低的 Agent/模型、并行运行多个 worker、opencode/orchestration 语法 → 请参阅 orca-dispatch-reference(唯一真实来源,请勿在此重复语法)。

通过提炼后的 understand-anything 流程接入代码库(图谱 + Git 历史,不使用插件),然后进行领域增强 + wiki + HTML。

WHAT

目的和背景
  • 目的: 将任意代码库接入为可用知识:知识图谱(扫描 + Git 历史 + 批量分析 + 分层/导览,不使用插件)、领域图谱(领域 → 流程 → 步骤)、wiki llmwiki/wiki/ 和 HTML 文档页面 — 推理由 Claude 主线程负责,机械性工作则调度给 opencode + DeepSeek Flash v4。
  • 触发条件(何时使用):“onboard codebase”、“analyze codebase”、“knowledge graph”、“guided tour”、“/orca-onboard”。
  • 非目标: 不安装 Understand-Anything 插件;不将推理(领域、架构、分层/导览)调度到 opencode/agy;不自行编写原始 HTML(始终通过 skeleton v2);不捏造文件路径或 file:line;不重复调度语法(真实来源为 orca-dispatch-reference)。
心智模型

Phase 0 pre-flight/bootstrap → Phase 0.5 GATE (draft + dispatch board → 用户审批) → Phase 1 graph (scan → git history → analyze → merge → layers+tour → validate → [code-graph index]) → Phase 2 domain graph → Phase 3 wiki → Phase 4 HTML (JSON → skeleton v2 → wiki-graph vector) → output report。Draft llmwiki/wiki/draft/orca/<DATE>-onboard-<slug>.md 是状态日志:每个 phase 状态为 pending → in-progress → done,恢复时从中读取。

输入和输出约定
FieldRequired?含义
In<path>否(默认为 .)目标项目目录;@<draft> = 从现有 draft 恢复
In--full否删除 .overstack/graph/ 后重建
In--update否仅重新分析上次运行后有变化的文件(需要已有 graph + meta.json)
In--language <lang>否输出语言(vi、en、zh 等)
In--skip-wiki否跳过 wiki 生成
In用户在 Phase 0.5 的审批是dispatch board + propose 内容已输出到终端后
Inopencode、skill docs-site-macos是缺少时 → Phase 0 以状态码 1 退出,并附带安装命令
Out.overstack/graph/knowledge-graph.json、ONBOARDING.md、meta.json是Phase 1(Phase 1 最终 gate 检查前两个文件)
Out.overstack/onboard/intermediate/domain-graph.json是Phase 2
Out.overstack/onboard/intermediate/surface.json + coverage.json是Phase 2 — 实际表面 @commit + 覆盖日志;输出报告会打印 已覆盖 N/M 个表面项(skill surface-coverage)
Outllmwiki/wiki/(index、concepts、entities)是,除非使用 --skip-wikiPhase 3;每个页面都有 ## Origin + index 行
Outllmwiki/html/onboarding-<slug>.html + llmwiki/html/wiki-graph.html是(vector 失败时放行)Phase 4
Outdraft 状态 + index/log 行是每个 phase 结束后更新

“完成” = draft 中 4 个 phase 均为 done,HTML 文件存在,并已记录输出报告。

规则与能力
  • RULE-01 (MUST):Phase 0 完成前,DO NOT run Phase 0.5 or Phases 1–4。 顺序不可颠倒:Phase 0(验证 llmwiki/ 存在)→ Phase 0.5(先创建草稿,再询问用户)→ Phases 1–4。
  • RULE-02 (MUST):缺少 llmwiki/ → 在 Phase 0 引导初始化,NEVER defer;引导初始化失败 → 完全 STOP,并报告错误。
  • RULE-03 (MUST):每个 phase 结束后 → 立即更新 status draft,不要留到最后。
  • RULE-04 (MUST):Dispatch board + 提议内容必须通过 bash 打印(在终端中可见),然后才能提出 gate 问题;草稿中的 Agent Task Assignment 行必须与 board 一致。
  • RULE-05 (MUST):推理任务 MUST 留在 Claude 主线程中。NO reasoning to opencode/agy。 opencode + DeepSeek:仅用于填充模板、渲染 wiki 和 HTML。
  • RULE-06 (MUST):先读再操作——每个 phase 都要在采取任何操作前读取 READ FIRST 块中的所有输入。不要向用户询问文件中已有的信息。
  • RULE-07 (MUST):Phase 1 之后,NO full knowledge-graph.json reads——改用 ONBOARDING.md。
  • RULE-08 (MUST):仅使用真实文件路径——绝不捏造;domain graph 只引用真实的 file:line,并对照代码进行验证。
  • RULE-12 (MUST):domain graph 的覆盖度必须通过与真实表面进行 diff 报告(surface-coverage.py check),格式为 N/M 项;绝不要报告 flow/文章数量,仿佛它们已经解释了整个应用。
  • RULE-09 (MUST):Wiki:wikilink 格式为 [[page-name]];tour:5-15 个步骤,从项目概览开始。
  • RULE-10 (MUST):Phase 4 绝不自行编写原始 HTML——始终通过 skeleton v2。
  • RULE-11 (MUST):仅当 dep-health.py --json 报告 status == "ok" 时,才索引 code-graph——在 config 中声明 ≠ 服务正常运行。
  • Capabilities:读取目标仓库 + VCS 历史记录;运行本地脚本(bash/python);分派低成本 LLM 处理机械性工作;写入 .overstack/、llmwiki/;联网以引导初始化/安装依赖。
失败边界
  • 缺少依赖项(opencode、docs-site-macos)或 project root 不存在 → blocked(exit 1 + 安装命令)。
  • --update 但尚无 graph/meta.json → blocked,提示先不带 --update 运行。
  • 引导初始化失败 → failed,完全 STOP。
  • 用户未在 gate 批准 → cancelled,只保留草稿。
  • Batch analyze 失败 2 次 → 放弃 batch,记录 PHASE_WARNINGS → partial graph(partial graph 优于 no graph)。
  • Phase 1 gate 缺少 knowledge-graph.json/ONBOARDING.md → Phase 1 failed。
  • 没有 HTTP/CLI/event 入口点 → domains 为空(狭义 succeeded)。
  • 绘制 wiki-graph.html 失败 → fail-open,不阻止 onboard。

HOW

主要工作流
步骤类型输入操作输出/退出失败/后续
W01确定性args, máy阶段 0 — 检查依赖、resume/root、更新模式,初始化 llmwiki+harness,创建目录、统计文件、探测 Agent环境变量 + files.txt缺少依赖/root → 退出码 1
W02效果W01 的结果阶段 0.5 Gate — 先创建草稿,再建立索引+日志,打印调度板 + 提案,询问用户草稿 pending,等待批准未批准 → 已取消
W03确定性repo阶段 1 1.1 SCAN + 1.2 GIT HISTORY(bash)+ 1.3 ANALYZE(静态解析;opencode 仅用于增强)+ 1.4 MERGE(python)assembled-graph.json批次失败 → 重试 1 次 → 放弃,记录到 PHASE_WARNINGS
W04判断assembled graph、目录树、README1.5 LAYERS + TOUR(Claude 主线程)layers + 5-15 步导览—
W05确定性graph1.6 VALIDATE + SAVE + 阶段 1 最终关卡knowledge-graph.json、meta.json、ONBOARDING.md缺少文件 → 退出码 1
W06判断ONBOARDING.md、layers、surface.json阶段 2 实际覆盖面(surface-coverage.py scan)→ 领域增强(Claude)→ check 关卡domain-graph.json + coverage.json、N/M 项一行没有入口点 → domains 为空;3 轮后 check 仍显示红色 → 部分完成,并附上尚未覆盖的列表
W07效果ONBOARDING + domain graph阶段 3 wiki(opencode,填充模板)llmwiki/wiki/opencode 出错 → Claude 备用方案
W08效果ONBOARDING + domain graph + skeleton阶段 4 STEP A JSON → STEP B 填充骨架(python)→ STEP C vectorHTML + wiki-graph.htmlskeleton 缺失 → 退出码 1;vector 出错 → 失败时继续开放
W09效果结果输出报告 + 更新状态 + 同步推送最终草稿、索引/日志—

各步骤详情(W01–W09 的事实来源):

触发条件
  • “onboard codebase”、“analyze codebase”、“knowledge graph”、“guided tour”
选项
  • --full — 删除 .overstack/graph/ 并重新构建
  • --update — 增量更新:仅重新分析上次运行后发生变化的文件
  • --language <lang> — 输出语言(vi、en、zh 等)
  • --skip-wiki — 跳过 wiki 生成
  • <path> — 目标目录(默认:.)
进度
[Phase 1/4] Graph generation (scan + git history + batch analyze + layers/tour)...
[Phase 2/4] Domain enrichment (Claude)...
[Phase 3/4] Wiki generation (opencode + DeepSeek Flash v4)...
[Phase 4/4] HTML docs (opencode + DeepSeek Flash v4)...

⚠️ 硬性规则

⛔ 在阶段 0 完成前,禁止运行阶段 0.5 或阶段 1–4。

严格按顺序执行,不得颠倒:

  1. 阶段 0 → 完成,确认 llmwiki/ 存在 ✅
  2. 阶段 0.5(Gate) → 先创建草稿文件,再询问用户
  3. 阶段 1–4 → 执行,每个阶段结束后立即更新状态
  • 若缺少 llmwiki/ → 在阶段 0 初始化,绝不延后
  • 初始化失败 → 立即完全停止并报告错误
  • 每个阶段结束后 → 立即更新草稿状态,绝不留到最后

调度规则
TASK TYPE          → AGENT               → MODEL
──────────────────────────────────────────────────────
Scan + git history → bash/python direct  → (no LLM)
Batch file analyze → python static parse → (no LLM — PRIMARY; opencode chỉ enrich)
Merge + validate   → python inline       → (no LLM)
Layers / tour      → Claude main thread  → Sonnet (never dispatch out)
Domain reasoning   → Claude main thread  → Sonnet (never dispatch out)
Wiki / HTML render → opencode            → opencode/deepseek-v4-flash-free

推理任务必须留在 Claude 主线程中。不得将推理任务交给 opencode/agy。 opencode + DeepSeek:仅用于填充模板、渲染 wiki 和生成 HTML。


Agent 二进制文件
Agent二进制文件默认模型检查命令
AntigravityagyClaude(Sonnet/Opus)agy --version
OpenCodeopencode可配置opencode --version
Kirokiro-cli—kiro-cli --version

无需安装 Understand-Anything 插件。 阶段 1 直接在此技能中实现从 Understand-Anything 提炼出的方法(scan → batch analyze → merge → layers → tour → validate)——使用 bash/python + 纯 opencode prompt + Claude 主线程运行。无需在 agy/opencode 中安装任何额外组件。

OpenCode 搭配 DeepSeek Flash v4:

opencode run "$SPEC" --model opencode/deepseek-v4-flash-free < /dev/null \
# Fallback if flag unsupported:
echo "$SPEC" | opencode --model opencode/deepseek-v4-flash-free
# Last resort: Claude main thread

状态更新辅助工具
update_phase_status() {
  local keyword="$1"
  local status="$2"
  [ -z "$DRAFT_FILE" ] && echo "[WARN] DRAFT_FILE unset" && return 0
  local f=$(echo "$DRAFT_FILE" | tr '\\' '/')
  [ ! -f "$f" ] && echo "[WARN] DRAFT_FILE not found: $f" && return 0
  perl -i -pe "s/(\Q$keyword\E.*?)\| (?:pending|in-progress|done)/\$1| $status/g if /\Q$keyword\E/" "$f" \
    || sed -i "s/\(.*$(echo "$keyword" | sed 's/[^^]/[&]/g').*\)| [a-z-]*/\1| $status/" "$f" \
    || echo "[WARN] status update failed for: $keyword"
}

阶段 0 — 预检与设置
# --- 1. Dependency check (agy optional — Phase 1 dùng distilled pipeline, không cần agy) ---
MISSING=()
opencode --version >/dev/null 2>&1  || MISSING+=("opencode")
ls ~/.agents/skills/docs-site-macos/SKILL.md >/dev/null 2>&1 || MISSING+=("docs-site-macos skill")

if [ ${#MISSING[@]} -gt 0 ]; then
  echo "❌ Missing dependencies:"
  for dep in "${MISSING[@]}"; do echo "   - $dep"; done
  echo ""
  echo "docs-site-macos: npx skills add rheinmir/setup@orca --skill docs-site-macos --global -y"
  exit 1
fi

# --- 2. Resume Mode check & Project Root resolution ---
if [[ "$1" == @* ]]; then
  DRAFT_FILE="${1#@}"
  DRAFT_FILE=$(echo "$DRAFT_FILE" | tr '\\' '/')
  RESUME_MODE=true
  PROJECT_ROOT=$(grep "Project root:" "$DRAFT_FILE" | grep -oP '(?<=`)[^`]+(?=`)' | head -1)
  PROJECT_ROOT=$(echo "$PROJECT_ROOT" | tr '\\' '/')
else
  RESUME_MODE=false
  PROJECT_ROOT=${1:-.}
  PROJECT_ROOT=$(echo "$PROJECT_ROOT" | tr '\\' '/')
fi

test -d "$PROJECT_ROOT" || { echo "❌ Project root directory not found: $PROJECT_ROOT"; exit 1; }

# --- 3. Update Mode check ---
UPDATE_MODE=false
for arg in "$@"; do
  [ "$arg" = "--update" ] && UPDATE_MODE=true
done

if [ "$UPDATE_MODE" = "true" ]; then
  [ ! -f "$PROJECT_ROOT/.overstack/graph/knowledge-graph.json" ] \
    && echo "❌ --update requires existing graph. Run without --update first." && exit 1
  [ ! -f "$PROJECT_ROOT/.overstack/graph/meta.json" ] \
    && echo "❌ --update requires meta.json. Run without --update first." && exit 1
  echo "[update] Incremental mode — reading changed files from meta.json"
  
  CHANGED_FILES=$(python3 -c "
import json, sys
meta = json.load(open('$PROJECT_ROOT/.overstack/graph/meta.json'))
changed = meta.get('changedFiles', meta.get('changed', []))
print('\n'.join(changed))
" 2>/dev/null || echo "")

  if [ -z "$CHANGED_FILES" ]; then
    echo "[update] no changedFiles in meta.json — falling back to full rebuild"
    UPDATE_MODE=false
  else
    echo "[update] Changed files:"; echo "$CHANGED_FILES"
  fi
fi

# --- 4. Bootstrap llmwiki + harness if missing ---
# Harness có 2 mode: GLOBAL (~/.claude/harness + hooks trong ~/.claude/settings.json,
# bảo vệ mọi project llmwiki trên máy này) và PER-PROJECT (harness/ commit vào repo,
# bảo vệ teammate). Global đủ cho máy dev cá nhân — chỉ WARN per-project khi cả 2 thiếu.
GLOBAL_HARNESS=false
[ -f "$HOME/.claude/harness/hooks/pre_tool_use.py" ] \
  && grep -q 'harness/hooks/pre_tool_use.py' "$HOME/.claude/settings.json" 2>/dev/null \
  && GLOBAL_HARNESS=true
echo "[harness] global=$GLOBAL_HARNESS project=$([ -d "$PROJECT_ROOT/harness" ] && echo yes || echo no)"

if [ -f "$PROJECT_ROOT/.llmwiki/.harness-stamp" ]; then
  # Dự án layout DOT (cài bằng bootstrap v4): wiki ở .llmwiki/, engine ở GLOBAL — KHÔNG chép llmwiki/ trần, KHÔNG gọi đường per-project
  # (install-harness.sh sẽ tự dừng rc 5). Thiếu/cũ thì cập nhật bằng: curl -fsSL …/harness/poc-vendor-neutral/bootstrap.sh | bash
  echo "[orca-onboard] dự án dot-layout đã có overstack (.llmwiki/.harness-stamp) — bỏ qua bootstrap"
elif [ ! -d "$PROJECT_ROOT/llmwiki" ] || { [ "$GLOBAL_HARNESS" = "false" ] && [ ! -d "$PROJECT_ROOT/harness" ]; }; then
  echo "[orca-onboard] bootstrapping llmwiki + harness..."
  git clone https://github.com/rheinmir/setup.git /tmp/orca-llmwiki-bootstrap --depth 1 -b orca -q
  [ ! -d "$PROJECT_ROOT/llmwiki" ] && cp -r /tmp/orca-llmwiki-bootstrap/llmwiki "$PROJECT_ROOT/llmwiki"
  if [ "$GLOBAL_HARNESS" = "false" ] && [ ! -d "$PROJECT_ROOT/harness" ]; then
    bash /tmp/orca-llmwiki-bootstrap/harness/scripts/install-harness.sh "$PROJECT_ROOT" \
      && echo "[orca-onboard] harness installed OK" \
      || echo "[WARN] harness install failed/denied — đường khuyên dùng: curl -fsSL https://raw.githubusercontent.com/Rheinmir/setup/orca/harness/poc-vendor-neutral/bootstrap.sh | bash (cài global + kéo orca-graph); hoặc 'install-harness.sh --global'"
  fi
  rm -rf /tmp/orca-llmwiki-bootstrap
  echo "[orca-onboard] bootstrap done"
fi

# --- 5. Create dirs ---
mkdir -p $PROJECT_ROOT/.overstack/onboard/{intermediate,tmp}
mkdir -p $PROJECT_ROOT/llmwiki/wiki/draft/{cave,uiux,orca}

# --- 6. File count & availability check ---
git rev-parse HEAD 2>/dev/null > $PROJECT_ROOT/.overstack/onboard/tmp/commit.txt
git ls-files > $PROJECT_ROOT/.overstack/onboard/tmp/files.txt 2>/dev/null \
  || find $PROJECT_ROOT -type f \
       ! -path "*/.overstack/onboard/*" ! -path "*/llmwiki/*" ! -path "*/.git/*" \
     > $PROJECT_ROOT/.overstack/onboard/tmp/files.txt
FILE_COUNT=$(wc -l < $PROJECT_ROOT/.overstack/onboard/tmp/files.txt | tr -d ' ')

# Probe agent availability
AGY_OK=$(agy --version 2>/dev/null && echo "✅ usable" || echo "❌ not found")
OC_OK=$(opencode --version 2>/dev/null && echo "✅ usable" || echo "❌ not found")
KIRO_OK=$(kiro-cli --version 2>/dev/null && echo "✅ usable" || echo "❌ not found")

echo "[pre-flight] $FILE_COUNT files | agy=$AGY_OK | opencode=$OC_OK"

# Parse statuses if in resume mode
parse_status() {
  local keyword="$1"
  awk '/## Agent Task Assignment/{p=1} p && /^## [^A]/{p=0} p' "$DRAFT_FILE" \
    | grep "$keyword" | grep -oE 'pending|in-progress|done' | head -1
}

if [ "$RESUME_MODE" = true ]; then
  PHASE1_STATUS=$(parse_status "Phase 1 —")
  PHASE2_STATUS=$(parse_status "Phase 2 —")
  PHASE3_STATUS=$(parse_status "Phase 3 —")
  PHASE4_STATUS=$(parse_status "Phase 4 —")
  echo "[Resume] P1=$PHASE1_STATUS P2=$PHASE2_STATUS P3=$PHASE3_STATUS P4=$PHASE4_STATUS"
fi

阶段 0.5 — 确认关卡

必需:先创建草稿文件,再询问用户。绝不能颠倒顺序。

DATE=$(date +%d%m%y)
PROJECT_SLUG=$(basename "$PROJECT_ROOT" | tr '[:upper:]' '[:lower:]' | tr ' ' '-')
DRAFT_FILE="$PROJECT_ROOT/llmwiki/wiki/draft/orca/${DATE}-onboard-${PROJECT_SLUG}.md"

# Graph = distilled pipeline (no plugin): scan/history bash → batch opencode → layers/tour Claude
OC_AVAIL=$(opencode --version 2>/dev/null && echo "yes" || echo "no")
if [ "$OC_AVAIL" = "yes" ]; then
  AGENT_GRAPH="distilled pipeline: bash + opencode (batch) + Claude (layers/tour)"
else
  AGENT_GRAPH="distilled pipeline: bash + Claude main thread (opencode unavailable)"
fi

cat > "$DRAFT_FILE" << EOF
---
type: draft
title: ${DATE}-onboard-${PROJECT_SLUG}
status: proposed
tags: [orca-onboard, output-report]
timestamp: $(date +%Y-%m-%d)
---

# ${DATE}-onboard-${PROJECT_SLUG}

**Status:** proposed

## Agent CLI Availability
| Agent | Binary | Status |
|-------|--------|--------|
| Antigravity | \`agy\` | $AGY_OK |
| OpenCode | \`opencode\` | $OC_OK |
| Kiro | \`kiro-cli\` | $KIRO_OK |

## Agent Task Assignment
| Task | Agent | Model | Status |
|------|-------|-------|--------|
| Phase 1 — Graph generation ($FILE_COUNT files) | $AGENT_GRAPH | DeepSeek Flash v4 + Sonnet | pending |
| Phase 2 — Domain enrichment | Claude main thread | Sonnet | pending |
| Phase 3 — Wiki generation | opencode | DeepSeek Flash v4 | pending |
| Phase 4 — HTML docs | opencode | DeepSeek Flash v4 | pending |

## What
Onboard \`$PROJECT_ROOT\` — understand-anything graph, domain enrichment, wiki, HTML.

## Output
- \`.overstack/graph/knowledge-graph.json\` (tree-sitter + Louvain)
- \`.overstack/graph/ONBOARDING.md\` (~20k tokens distilled)
- \`.overstack/onboard/intermediate/domain-graph.json\`
- \`llmwiki/wiki/\` (index, concepts, entities, architecture, tours)
- \`llmwiki/html/onboarding-${PROJECT_SLUG}.html\`
- \`llmwiki/html/wiki-graph.html\` (vector quan hệ concept↔code — STEP C)

## Files
| File | Action |
|------|--------|
| \`.overstack/graph/knowledge-graph.json\` | created by Phase 1 pipeline |
| \`.overstack/graph/ONBOARDING.md\` | created by Phase 1 pipeline |
| \`.overstack/onboard/intermediate/domain-graph.json\` | created by Claude |
| \`llmwiki/wiki/index.md\` | created/modified |
| \`llmwiki/wiki/concepts/architecture.md\` | created |
| \`llmwiki/wiki/concepts/*.md\` | created |
| \`llmwiki/wiki/entities/*.md\` | created |
| \`llmwiki/wiki/concepts/onboarding-tour.md\` | created |
| \`llmwiki/html/onboarding-${PROJECT_SLUG}.html\` | created |
| \`llmwiki/html/wiki-graph.html\` | created by STEP C (vector) |

## Notes
- Invoked via: \`/orca-onboard\` skill
- Project root: \`$PROJECT_ROOT\`
- Files tracked: $FILE_COUNT
- Reasoning phases in Claude main thread — NOT dispatched to cheap models
- Mechanical phases: opencode + DeepSeek Flash v4

## Cost Estimate
| Phase | Agent | Est. tokens | Est. cost |
|-------|-------|-------------|-----------|
| Phase 1 (graph) | bash + opencode batches + Claude layers/tour | ~1.5M (DeepSeek) + ~50k (Sonnet) | ~\$0.50 |
| Phase 2 (domain) | Claude Sonnet | ~50k | ~\$0.50 |
| Phase 3 (wiki) | DeepSeek Flash | ~100k | ~\$0.02 |
| Phase 4 (HTML) | DeepSeek Flash | ~50k | ~\$0.01 |

## Origin
- **Draft:** \`wiki/draft/orca/${DATE}-onboard-${PROJECT_SLUG}.md\`
- **Commit:** _(filled by verify-before-commit)_
- **Date promoted:** _(filled by verify-before-commit)_
EOF

# Update wiki index + log
echo "| [${DATE}-onboard-${PROJECT_SLUG}](draft/orca/${DATE}-onboard-${PROJECT_SLUG}.md) | draft | $(date +%Y-%m-%d) |" >> "$PROJECT_ROOT/llmwiki/wiki/index.md"
echo "## $(date +%Y-%m-%d) — orca-onboard — onboard-${PROJECT_SLUG}" >> "$PROJECT_ROOT/llmwiki/wiki/log.md"

echo "DRAFT_FILE=$DRAFT_FILE"

# --- Terminal dispatch board (REQUIRED — must print in terminal BEFORE the gate question) ---
P1_NOTE="(distilled pipeline: 1.1-1.2 bash, 1.3 opencode batches, 1.4/1.6 python, 1.5 Claude)"

echo ""
echo "==================== ORCA-ONBOARD DISPATCH BOARD ===================="
echo " Project : $PROJECT_SLUG"
echo " Files   : $FILE_COUNT"
echo " Draft   : $DRAFT_FILE"
echo "----------------------------------------------------------------------"
printf " %-7s %-22s %-24s %-20s %s\n" "PHASE" "TASK" "AGENT" "MODEL" "EST.COST"
printf " %-7s %-22s %-24s %-20s %s\n" "1" "Graph generation" "bash+opencode+Claude" "DeepSeek+Sonnet" "~\$0.50"
printf " %-7s %-22s %-24s %-20s %s\n" "2" "Domain enrichment" "Claude main thread" "Sonnet" "~\$0.50"
printf " %-7s %-22s %-24s %-20s %s\n" "3" "Wiki generation" "opencode" "DeepSeek Flash v4" "~\$0.02"
printf " %-7s %-22s %-24s %-20s %s\n" "4" "HTML docs" "opencode" "DeepSeek Flash v4" "~\$0.01"
[ -n "$P1_NOTE" ] && echo " Phase 1 $P1_NOTE"
echo "======================================================================"

# --- Print propose file path + content (REQUIRED — user reviews this before approving) ---
echo ""
echo "PROPOSE FILE: $DRAFT_FILE"
echo "----------------------------------------------------------------------"
cat "$DRAFT_FILE"

⛔ 必须通过 bash 打印调度板和上方的提案文件内容(在终端中可见)——仅在聊天中或仅在草稿文件中重述都不够。用户会根据此调度板和提案来决定是否编排。草稿中的 Agent 任务分配行必须与调度板一致(例如,如果因文件数 >100 将阶段 1 改派给 opencode,草稿必须写 opencode,而不是 agy)。

继续之前,请先征求用户确认。


阶段 1 — 图谱生成(精简版 understand-anything — KHÔNG cần plugin)

**流程:**扫描(bash)→ git 历史(bash)→ 批量分析(opencode + DeepSeek)→ 合并(python)→ 层级 + 导览(Claude 主线程)→ 验证 + 保存(python + Claude)。方法从 Understand-Anything 精简而来;所有提示词/模式都在下方——不调用 /understand,不安装插件。

必需输出:

  • .overstack/graph/knowledge-graph.json(nodes、edges、layers、tour)
  • .overstack/graph/ONBOARDING.md(约 20k tokens 的精简内容)
  • .overstack/graph/meta.json

跳过检查:RESUME_MODE=true + PHASE1_STATUS=done → 跳到阶段 2。

决策表:

图谱是否存在标记操作
否(无)完整流程
是(无)跳过阶段 1,使用现有图谱
是--update仅重新分析 git diff <meta.gitCommitHash>..HEAD --name-only 中的文件,并合并到现有图谱
是--full删除 .overstack/graph/,执行完整流程
1.1 扫描(bash — 无 LLM)
mkdir -p "$PROJECT_ROOT/.overstack/graph" "$PROJECT_ROOT/.overstack/onboard/tmp"
git -C "$PROJECT_ROOT" ls-files > "$PROJECT_ROOT/.overstack/onboard/tmp/files.txt"
# Loại file nhị phân/lock/vendor; phân loại theo extension: code/config/docs/infra/data/script
# Đọc context: README (3000 chars đầu), manifest (package.json/pyproject.toml/Cargo.toml/go.mod), dir tree 2 cấp
# Detect entry point: src/index.ts, main.py, app.py, main.go, src/main.rs, cmd/*/main.go, manage.py, __main__.py...
1.2 GIT 历史(bash — 无 LLM)

Git 历史信号可丰富图谱——这是静态分析无法提供的:

# Churn — file nóng (hay sửa nhất, 365 ngày)
git -C "$PROJECT_ROOT" log --since="365 days ago" --name-only --pretty=format: \
  | grep -v '^$' | sort | uniq -c | sort -rn | head -40 > "$PROJECT_ROOT/.overstack/onboard/tmp/churn.txt"
# Recent — file vừa đổi (30 ngày)
git -C "$PROJECT_ROOT" log --since="30 days ago" --name-only --pretty=format: | grep -v '^$' | sort -u \
  > "$PROJECT_ROOT/.overstack/onboard/tmp/recent.txt"
# Commit subjects gần nhất — chủ đề đang phát triển
git -C "$PROJECT_ROOT" log --since="90 days ago" --pretty=format:'%s' | head -50 \
  > "$PROJECT_ROOT/.overstack/onboard/tmp/recent-subjects.txt"
# Co-change — python đọc `git log --name-only` theo commit, đếm cặp file đổi cùng nhau, ngưỡng ≥3

应用方式:将 churn 排名前列的节点标记为 hot;将 recent.txt 中的节点标记为 recent;将共同变更 ≥3 次的文件对添加为 related 边(weight 0.5);导览 + ONBOARDING 优先介绍 hot 文件;recent-subjects 用于「正在处理的内容」部分。

1.3 分析 — 首选:静态解析(0 token)· 仅用 opencode 补充信息

默认使用 python 静态解析(run 120626-zca-bridge 的经验——既省成本又确定): 使用正则表达式解析 import/export ... from + require() → 解析相对路径 → 添加 imports 边; test/**.test.ts → tested_by;summary = 文件开头的注释 / exports 列表 / md 标题; 根据扩展名确定 type(file/config/document)。Imports 属于机械性工作——LLM 并不比正则表达式更准确。 仅当复杂文件需要更丰富的语义 summary 时才调用 opencode(可选增强):

将文件列表分成每批约 25 个文件(把相关文件放在同一批:Dockerfile+compose、migrations、CI configs、docs)。每批调用:

opencode run "$BATCH_SPEC" --model opencode/deepseek-v4-flash-free < /dev/null
# ⚠ KHÔNG thêm --dangerously-skip-permissions: Claude Code auto-mode classifier sẽ DENY lệnh dispatch.
# opencode treo chờ permission / bị chặn → dùng STATIC PARSE fallback bên dưới (ưu tiên mặc định).

BATCH_SPEC(注入完整上下文——DeepSeek 不会自行读取分配列表以外的任何内容):

分析项目 (,语言:)中的这些文件。为每个文件生成 GraphNode {id, type, name, filePath, summary(1-2 句), tags[]},并根据文件内容中可见的 imports/calls/configures/documents 关系生成 GraphEdges {source, target, type, weight}。读取列出的每个文件。只将有效 JSON {"nodes":[...], "edges":[...]} 写入 .overstack/onboard/tmp/batch-<i>.json。ID 约定:file:<relpath>、config:<relpath>、document:<relpath>。文件:<包含行数的列表>

最多并行处理 5 个批次。批次失败 → 重试 1 次 → 再次失败则跳过,并记录到 PHASE_WARNINGS(部分图谱胜过没有图谱)。如果 opencode 不可用 → 由 Claude 主线程自行分析批次。

1.4 合并 + 规范化(内联 python — 无 LLM)

Claude 编写脚本 .overstack/onboard/tmp/merge.py(逻辑精简自 Understand-Anything 的 merge-batch-graphs.py):读取所有 batch-*.json → 合并 nodes/edges → 规范化 ID 前缀(移除重复前缀,补上缺失前缀)→ 按 id 去重 node(保留最后一个),按 (source,target,type) 去重 edge → 丢弃悬空 edge(写入 stderr 日志)→ 根据共同变更(1.2)添加 related 边 → 写入 assembled-graph.json。

1.5 层 + 导览(Claude 主线程——推理,不派发)

根据 assembled-graph、目录树和 README:

  • 层: [{id: "layer:<kebab>", name, description, nodeIds[]}]——每个文件级节点恰好属于一个层;目录结构是最有力的依据。
  • 导览: 5-15 个步骤 [{order, title, description, nodeIds[]}]——第 1 步始终是项目概览(README),然后遵循入口点,优先介绍 hot 文件;讲述 README 所讲的同一个故事,但通过真实代码呈现。
1.6 验证 + 保存(python + Claude)

进行确定性验证(脚本):不重复节点 ID、不存在悬空边、每个文件节点恰好属于一个层、导览中的 nodeIds 均存在,并统计孤立节点。能自动修复的就自动修复(删除悬空边、填充默认值),其余情况记录警告——仍然保存部分图谱。

写入:

  • knowledge-graph.json:{version, project: {name, languages, frameworks, description, analyzedAt, gitCommitHash}, nodes, edges, layers, tour}
  • meta.json:{lastAnalyzedAt, gitCommitHash, analyzedFiles}
  • ONBOARDING.md(由 Claude 提炼,约 20k 个 token):概览、各层 + 描述、关键流程、重要文件 + 原因(变更频率)、“正在处理的内容”(recent-subjects)、导览叙述、统计信息。

最后:删除 batch-*.json,报告摘要(已分析的文件数、按类型统计的节点/边、层数、导览步骤数、警告)。

Schema(从 Understand-Anything 提炼)
  • 节点类型: file, function, class, module, concept, config, document, service, table, endpoint, pipeline, schema, resource——ID:<type>:<relpath>[:<name>]
  • 主要边类型: imports、exports、contains、inherits、implements、calls、reads_from、writes_to、depends_on、tested_by、configures、related、documents、deploys、triggers、routes、defines_schema
  • 权重: contains 1.0 · inherits/implements 0.9 · calls/exports 0.8 · imports 0.7 · depends_on/configures 0.6 · 其余 0.5
# Gate cuối Phase 1
[ ! -f "$PROJECT_ROOT/.overstack/graph/knowledge-graph.json" ] \
  && echo "❌ Phase 1 FAIL: knowledge-graph.json missing" && exit 1
[ ! -f "$PROJECT_ROOT/.overstack/graph/ONBOARDING.md" ] \
  && echo "❌ Phase 1 FAIL: ONBOARDING.md missing" && exit 1
echo "✅ Phase 1 done"
# update_phase_status "Phase 1 —" "done"
1.7 CODE-GRAPH MCP 索引(可选——仅当 mcpServers 中存在 code-graph 服务时)

用于按精确行号查询代码关系的层,补充上述提炼出的图谱:search_symbols、get_callers/callees 可即时检查影响。code-graph 服务(~/.claude.json → mcpServers)会在每个仓库的 <repo>/.graph-agent/index.db 中写入一个 SQLite 数据库。

**何时运行:**项目包含真实代码子模块/仓库(Go/TS/Py……),并且 code-graph 确实可用——通过 python3 harness/scripts/dep-health.py --json 检查,并要求 status == "ok";不要只看它是否在 ~/.claude.json 中声明。配置中有声明 ≠ 服务正在运行:0 字节数据库、缺少 symbols 表的数据库,或已停止的服务,仍会显示为“已声明”(2026-07-20 的教训——code-graph 连续数周不可用,但每个会话仍被引导去使用它)。状态为 degraded/absent 时跳过此步骤。

# 1. Index từng repo code (auto-detect root từ .git/go.mod/package.json).
#    Gọi MCP tool reindex_repo(<abs path repo>, force=true) cho MỖI repo code.
#    Lưu ý: code có thể nằm ở SUBDIR của submodule (vd <sub>/<svc>/go.mod chứ không phải <sub>/).
#    → trỏ vào thư mục chứa go.mod/package.json, không phải submodule root rỗng.
# 2. reindex_repo tự thêm repo vào registry ~/.graph-agent/repos.txt
#    → server --watch re-watch sau restart (durability).
# 3. Verify: get_stats() phải thấy symbols thật (>0), không phải stub.
echo "[1.7] code-graph: gọi reindex_repo cho mỗi repo code có manifest"

持久性保障: SessionStart hook code_graph_keeper.py(随 install-harness.sh 一起安装)会在仓库从注册表中掉出时自动重新注册,并提醒尚未建立索引的仓库。故障时放行,若项目未使用 code-graph,则为空操作——判断条件是存在可用的 .graph-agent/index.db(可打开且包含 symbols/files 表),而不仅仅是存在该文件:空数据库曾导致 keeper 错误写入注册表,并彻底压掉“尚未建立索引”的警告。不要每次编辑都重新索引(watcher 已负责处理,防抖时间为 2 秒)。之后编写一个 wiki 概念页面 concepts/code-graph-nav.md(介绍工具用法 + caller trace 示例),让团队了解如何使用。

后续会自动保持最新:编辑文件 → watcher 约 2 秒后重新索引。除非是新克隆仓库,或服务器关闭期间发生了大量更改,否则无需手动重新索引。


阶段 2 — 领域扩充

Agent: Claude 主线程(不分发) | 模型: Sonnet

先阅读(按顺序,在编写任何内容之前):

  1. .overstack/graph/ONBOARDING.md — 完整阅读(约 20k 个 token)
  2. .overstack/graph/knowledge-graph.json — 仅阅读 layers 数组和带有 entry-point 标签的节点(⛔ 不要读取整个文件,以免上下文溢出)
  3. 如果 UPDATE_MODE=true:读取现有的 .overstack/onboard/intermediate/domain-graph.json(合并,不要覆盖)

执行: 0. 先覆盖真实表面,再选择流程(技能 surface-coverage,GH#191 — 曾有 18 个流程被报告为覆盖了一个包含 62 个页面和 37 个模块的应用): python3 "$FDK_TOOLS/surface-coverage.py" scan "$PROJECT_ROOT" [--modules '<thư mục module API>/*'] --out .overstack/onboard/intermediate/surface.json 其中 FDK_TOOLS=$([ -f fdk/tools/surface-coverage.py ] && echo fdk/tools || echo "$HOME/.claude/harness/fdk/tools")(框架仓库 → 使用仓库内版本;客户机器 → 使用全局引擎)。对于非基于文件的框架,编写脚本列出路由,然后合并到同一文件。

  1. 从入口点识别 HTTP 端点 / CLI 命令 / 事件 / cron 作业 — surface.json 中的每个条目都必须由某个流程覆盖,或有理由地排除
  2. 逆向分析:入口点 → 流程(过程)→ 步骤(操作 @ 文件:行号)
  3. 构建 domain → flow → step 层级结构
  4. 写入 .overstack/onboard/intermediate/domain-graph.json + 覆盖记录 .overstack/onboard/intermediate/coverage.json({"commit", "items": {"page:/x": {"by": ["flow:…"]} | {"exclude": "理由"}}})
  5. 门禁: python3 "$FDK_TOOLS/surface-coverage.py" check surface.json coverage.json --flows domain-graph.json --root "$PROJECT_ROOT" — 返回码为 1(存在未覆盖条目、流程 ID 错误、file:line 错误)→ 下一轮编码时补齐,最多 3 轮;如果仍未通过,则阶段 2 = 部分完成。最终报告(W09)必须逐字输出 N/M 个表面条目已覆盖,K 个已排除 + 未覆盖条目列表 — 绝不能只报告流程数量,仿佛已经覆盖完整。

领域图谱架构:

{
  "domains": [
    {
      "id": "domain:order-management",
      "name": "Order Management",
      "flows": [
        {
          "id": "flow:create-order",
          "name": "Create Order",
          "steps": [
            { "order": 0.1, "id": "step:validate-input", "file": "src/orders/validator.ts", "line": 42 },
            { "order": 0.2, "id": "step:check-inventory", "file": "src/inventory/checker.ts", "line": 15 }
          ]
        }
      ]
    }
  ]
}

输出: .overstack/onboard/intermediate/domain-graph.json

跳过检查: RESUME_MODE=true + PHASE2_STATUS=done → 跳至阶段 3。

if [ "$RESUME_MODE" != "true" ] || [ "$PHASE2_STATUS" != "done" ]; then
  update_phase_status "Phase 2 —" "in-progress"
  # Claude main thread — no dispatch
  if [ "$UPDATE_MODE" = "true" ] && [ -n "$CHANGED_FILES" ]; then
    echo "[Phase 2] Update mode: re-enrich domain steps for changed files only"
    # Read existing domain-graph.json
    # Filter steps with filePath in CHANGED_FILES
    # Re-analyze those steps from ONBOARDING.md
    # Merge back into domain-graph.json (keep unchanged steps)
  else
    echo "[Phase 2] Full domain enrichment from ONBOARDING.md"
    # Read ONBOARDING.md + layers from knowledge-graph.json, write new domain-graph.json
  fi
  update_phase_status "Phase 2 —" "done"
fi

阶段 3 — Wiki 生成

Agent: opencode | 模型: opencode/deepseek-v4-flash-free

先阅读(在分发前注入 SPEC — DeepSeek 除非注入内容,否则不会读取文件):

  1. .overstack/graph/ONBOARDING.md — 完整阅读
  2. .overstack/onboard/intermediate/domain-graph.json — 完整阅读
  3. 如果 UPDATE_MODE=true:在 llmwiki/wiki/ 中 grep 对 CHANGED_FILES 的引用 → 找出过时页面
  • ⛔ 不要读取 .overstack/graph/knowledge-graph.json — 文件太大,会导致上下文溢出

执行: 根据提炼后的内容填写 Wiki 模板。不进行推理 — 机械地填写模板。

输出结构:

llmwiki/wiki/
├── index.md
├── concepts/          ← architecture.md, message-sync/flows, onboarding-tour.md (R5: KHÔNG tạo folder architecture/ hay tours/ — validator folder_structure chặn)
└── entities/          ← domain entities + project-structure.md
# Mọi trang PHẢI có '## Origin' (R2) và row trong index.md (R3)

跳过检查: RESUME_MODE=true + PHASE3_STATUS=done → 跳至阶段 4。

if [ "$RESUME_MODE" != "true" ] || [ "$PHASE3_STATUS" != "done" ]; then
  update_phase_status "Phase 3 —" "in-progress"

  if [ "$UPDATE_MODE" = "true" ] && [ -n "$CHANGED_FILES" ]; then
    STALE_PAGES=$(grep -rl "$CHANGED_FILES" "$PROJECT_ROOT/llmwiki/wiki/" 2>/dev/null | tr '\n' ' ')
    if [ -n "$STALE_PAGES" ]; then
      echo "[Phase 3] Stale wiki pages: $STALE_PAGES"
      SPEC="Update these wiki pages based on changes in ONBOARDING.md: $STALE_PAGES
Changed source files: $CHANGED_FILES
Do NOT regenerate unchanged pages. Preserve existing content in unchanged pages."
    else
      echo "[Phase 3] No stale wiki pages — skipping"
      update_phase_status "Phase 3 —" "done"
    fi
  else
    SPEC="Generate wiki pages from .overstack/graph/ONBOARDING.md and .overstack/onboard/intermediate/domain-graph.json.
Create: llmwiki/wiki/index.md, llmwiki/wiki/concepts/*.md (architecture.md + flow pages + onboarding-tour.md),
llmwiki/wiki/entities/*.md (domain entities + project-structure.md).
R5: chỉ được ghi vào concepts/ hoặc entities/. R2: mọi trang có '## Origin'. R3: cập nhật index.md.
Use wikilink format [[page-name]]. Do NOT read knowledge-graph.json directly."
  fi

  opencode run "$SPEC" --model opencode/deepseek-v4-flash-free < /dev/null \
    || echo "[WARN] opencode unavailable — Claude main thread fallback for wiki"

  update_phase_status "Phase 3 —" "done"
fi

阶段 4 — HTML 文档(skeleton v2 + JSON island)

Agent: 组装 JSON = opencode(机械操作)/ Claude 备用 · 填充 skeleton = python(不使用 LLM)

工作原理(与旧版不同 — 防止内容简陋 + UX 中断): 不要让模型生成原始 HTML (DeepSeek 会自行编造 CSS/JS → “镜像”丢失、点击无响应,输出行数在 173–816 之间且不稳定)。 改为:模型只生成一个 JSON 对象,并遵循 schema;UI 由冻结的 skeleton v2 (assets/docs-site-skeleton.html,已应用 /docs-site-macos 设计系统)渲染。 Skeleton = 固定导航栏(Overview/What & How/Architecture/Guided Tour/Modules/Docker;如果 JSON 中 what 和 how 均缺失,则隐藏 What & How)+ 固定侧边栏 + 折叠 + 滚动侦测 + 旅游主从视图 + 可拖动图表;Mono 项目会自动隐藏 Modules/Docker。子内容(layer/tour/module/docker)由 JSON 数据驱动。

先阅读(丰富来源 — 注入 SPEC;DeepSeek 不会自行读取文件):

  1. .overstack/graph/ONBOARDING.md — 全文(overview、hot files、flows、tour narrative)
  2. .overstack/onboard/intermediate/domain-graph.json — domain→flow→step(tour + lifecycle)
  3. knowledge-graph.json 中仅包含 layers + tour + node entry-point 的部分(⛔ 不要读取全文 — 会超出上下文容量) ⛔ 不要使用单薄的 wiki md 作为主要来源(这正是旧版内容简陋的原因)。

跳过检查: RESUME_MODE=true + PHASE4_STATUS=done → 跳过。

if [ "$RESUME_MODE" != "true" ] || [ "$PHASE4_STATUS" != "done" ]; then
  update_phase_status "Phase 4 —" "in-progress"

  # --- locate skeleton v2 ---
  SKELETON=$(ls ~/.agents/skills/orca-onboard/assets/docs-site-skeleton.html \
                ~/.claude/skills/orca-onboard/assets/docs-site-skeleton.html \
                "$PROJECT_ROOT/skills/orca-onboard/assets/docs-site-skeleton.html" 2>/dev/null | head -1)
  [ -z "$SKELETON" ] && echo "❌ Phase 4: skeleton v2 not found" && exit 1

  # --- detect Docker (multi-service → tab Docker; mono → docker:null, Modules:[]) ---
  DKFILE=$(ls "$PROJECT_ROOT"/docker-compose.y*ml "$PROJECT_ROOT"/compose.y*ml 2>/dev/null | head -1)
  N_SVC=0; [ -n "$DKFILE" ] && N_SVC=$(grep -cE '^  [a-zA-Z0-9_-]+:' "$DKFILE" 2>/dev/null || echo 0)
  echo "[Phase 4] skeleton=$SKELETON | compose=$DKFILE | services=$N_SVC"

  # --- STEP A: assemble ONBOARD_JSON (model emit JSON ONLY → file) ---
  JSON_OUT="$PROJECT_ROOT/.overstack/onboard/tmp/onboard.json"
  SPEC="Đọc .overstack/graph/ONBOARDING.md + .overstack/onboard/intermediate/domain-graph.json.
Phát ra MỘT object JSON (KHÔNG markdown, KHÔNG giải thích) theo ĐÚNG schema trong header của
$SKELETON, ghi vào $JSON_OUT. Yêu cầu chất lượng:
- project: name/subtitle/about thật; stack[] + versions[] từ manifest; stats[] (files, services, layers, tour steps).
- project.what = 2–4 câu LỜI THƯỜNG: dự án làm gì, cho ai, giải quyết vấn đề gì (không thuật ngữ nội bộ); project.how[] = 3–7 bước {t,d} kể luồng chạy đầu→cuối bằng lời người — hiện thành mục What & How NGAY SAU Overview.
- architecture.layers[] = layers thật; architecture.diagram.nodes[] (toạ độ trong ~760×rộng, rect≥70×30) + edges[] theo luồng.
- tour[] 5–15 bước, MỖI bước GIÀU: role(1-2 câu), file+line THẬT, in[]/out[], hot(churn), narr — KHÔNG 1–2 dòng.
- modules[] = mỗi container/image (đọc $DKFILE): name,img,meta(port/env/volume),life[[read|proc|write,desc]],arch. Repo mono ($N_SVC≤1) → modules:[].
- docker = {strategy, cmd[[text,c|p|]], table[[svc,img,cmd/port,deps]], order[]} nếu có compose; mono → docker:null."
  opencode run "$SPEC" --model opencode/deepseek-v4-flash-free < /dev/null 2>/dev/null \
    || echo "[Phase 4] opencode unavailable — Claude main thread tự assemble $JSON_OUT theo schema skeleton"
  # Nếu opencode treo/trống → Claude main thread đọc 2 nguồn trên, tự viết $JSON_OUT (reasoning OK ở đây).

  # --- STEP B: fill skeleton (python, no LLM) — thay {{TITLE}} + {{ONBOARD_JSON}} ---
  OUT="$PROJECT_ROOT/llmwiki/html/onboarding-${PROJECT_SLUG}.html"
  mkdir -p "$PROJECT_ROOT/llmwiki/html"
  python3 - "$SKELETON" "$JSON_OUT" "$OUT" <<'PY'
import json,sys,html
sk=open(sys.argv[1]).read(); data=json.load(open(sys.argv[2]))
name=(data.get("project") or {}).get("name","Project")
out=sk.replace("{{TITLE}}",html.escape(name)).replace("{{ONBOARD_JSON}}",json.dumps(data,ensure_ascii=False))
assert "{{ONBOARD_JSON}}" not in out and "{{TITLE}}" not in out, "token chưa thay hết"
open(sys.argv[3],"w").write(out); print("✅ filled →",sys.argv[3],len(out),"bytes")
PY

  ls "$OUT" && echo "✅ Phase 4 done" || echo "❌ Phase 4 FAIL: HTML not found"
  update_phase_status "Phase 4 —" "done"
fi

备用方案: opencode 崩溃/挂起 → Claude 主线程自行读取 ONBOARDING.md + domain-graph.json,按 schema 编写 $JSON_OUT(这是组装数据,可以由 Claude 完成), 然后运行 STEP B。绝不要自行编写原始 HTML — 始终使用 skeleton v2。

STEP C — 绘制矢量图 wiki-graph.html(Phase 3 刚生成的 wiki → 现在已有概念可供绘制):

Onboard 会生成 wiki,但不会自行绘制关系矢量图 — 在此处立即绘制,这样仅代码项目完成 onboard 后就会同时拥有矢量图(正好解决关键瓶颈:build-wiki-graph.py 会读取 llmwiki/wiki/*.md + 代码,不会直接读取代码来生成概念图)。采用 fail-open,不阻止 onboard。

# engine: repo-local → global (cùng thứ tự hook Stop resolve)
WG=$(ls "$PROJECT_ROOT/fdk/tools/build-wiki-graph.py" \
        "$HOME/.claude/harness/fdk/tools/build-wiki-graph.py" 2>/dev/null | head -1)
if [ -n "$WG" ] && [ -d "$PROJECT_ROOT/llmwiki/wiki" ]; then
  ALSO=""; [ -d "$PROJECT_ROOT/fdk/wiki" ] && ALSO="--also fdk/wiki"
  ( cd "$PROJECT_ROOT" && python3 "$WG" llmwiki/wiki $ALSO --code-root . ) \
    && echo "✅ vector: llmwiki/html/wiki-graph.html (concept↔code)" \
    || echo "⚠️ wiki-graph vẽ lỗi — không chặn onboard (Stop hook sẽ vẽ khi wiki/code đổi)"
else
  echo "⚠️ bỏ vẽ vector — thiếu engine build-wiki-graph.py (cài harness global) hoặc chưa có llmwiki/wiki"
fi

完成后:

lsof -ti :8765 >/dev/null 2>&1 || nohup npx serve -p 8765 > /tmp/serve.log 2>&1 &
echo "→ http://localhost:8765/llmwiki/html/onboarding-${PROJECT_SLUG}.html"

规则
  • 先读取,再操作 — 每个阶段在采取任何操作前,都要读取 READ FIRST 块中的所有输入。不要询问用户文件中已有的信息。
  • Phase 1 之后禁止读取完整的 knowledge-graph.json — 改为使用 ONBOARDING.md
  • 只能使用真实文件路径 — 绝不捏造
  • Domain graph:只引用真实的 file:line,并对照代码验证
  • Wiki:wikilink 格式 [[page-name]]
  • Tour:5–15 个步骤,从项目概览开始
  • 推理任务(domain、architecture):只能由 Claude 主线程执行
错误处理
  • Phase 1 批次失败(opencode)→ 重试 1 次,再次失败 → Claude 主线程自行分析该批次;写入 PHASE_WARNINGS
  • Phase 1 失败(没有 graph)→ 检查 batch-*.json 是否存在;如果 merge 脚本出错 → 阅读 stderr,修复后重新运行
  • Phase 2 domain 为空 → 未找到 HTTP/CLI/event 入口点;写入空的 domains 数组
  • Phase 3 失败 → 检查 opencode 模型配置;备用方案为 Claude 主线程
  • Phase 4 失败 → 备用方案:在 Claude 中直接调用 docs-site-macos skill

输出报告

所有阶段完成后,将提案草稿写入 wiki。

1. 文件名: DDMMYY-<ten>.md — 今天的日期 + 2–4 个 kebab-case 摘要词

2. 写入 llmwiki/wiki/draft/orca/DDMMYY-<ten>.md:

---
type: draft
title: DDMMYY-<ten>
status: proposed
tags: [orca-onboard, output-report]
timestamp: YYYY-MM-DD
---

# DDMMYY-<ten>

**Status:** proposed

## Agent Task Assignment
| Task | Agent | Model | Status |
|------|-------|-------|--------|
| Phase 1 — Graph generation | agy /understand | Claude (agy) | done |
| Phase 2 — Domain enrichment | Claude main | Sonnet | done |
| Phase 3 — Wiki generation | opencode | DeepSeek Flash v4 | done |
| Phase 4 — HTML docs | opencode | DeepSeek Flash v4 | done |

## What
<One sentence>

## Output
<Key artefacts>

## Files
| File | Action |
|------|--------|
| `.overstack/graph/knowledge-graph.json` | created |
| `llmwiki/wiki/index.md` | created/modified |
| `llmwiki/html/onboarding-<slug>.html` | created |

## Notes
- Invoked via: `/orca-onboard` skill

## Origin
- **Draft:** `wiki/draft/orca/DDMMYY-<ten>.md`
- **Commit:** _(filled by verify-before-commit)_
- **Date promoted:** _(filled by verify-before-commit)_

3. 更新 wiki 索引和日志:

  • llmwiki/wiki/index.md — 追加:| [DDMMYY-<ten>](draft/orca/DDMMYY-<ten>.md) | draft | YYYY-MM-DD |
  • llmwiki/wiki/log.md — 追加:## YYYY-MM-DD — orca-onboard — <ten>

4. 更新状态并同步推送 — 必须执行:

  • 更新草稿文件中的 Status 列,使其反映实际运行状态
  • 克隆 rheinmir/setup 的 orca 分支,复制更新后的 SKILL.md 并推送:
    git clone [email protected]:rheinmir/setup.git /tmp/rheinmir-setup-sync -b orca --depth 1
    cp ~/.agents/skills/orca-onboard/SKILL.md /tmp/rheinmir-setup-sync/skills/orca-onboard/SKILL.md
    cd /tmp/rheinmir-setup-sync
    git add .
    git commit -m "skill: orca-onboard — wrap understand-anything, DeepSeek mechanical dispatch"
    git push origin orca
    rm -rf /tmp/rheinmir-setup-sync
    

只有当 skill 未生成任何产物且未做出任何决策时,才跳过输出报告。


输出报告

所有阶段完成后,将提案草稿写入 wiki。

1. 文件名: DDMMYY-<ten>.md — 当天日期 + 2-4 个 kebab-case 摘要词

2. 写入 llmwiki/wiki/draft/orca/DDMMYY-<ten>.md:

---
type: draft
status: proposed
tags: [orca-onboard, output-report]
proposed: YYYY-MM-DD
---
# DDMMYY-<ten>

## Agent Task Assignment
| Task | Agent | Model | Status |
|------|-------|-------|--------|
| Phase 1 — Graph generation | agy /understand | Claude (agy) | done |
| Phase 2 — Domain enrichment | Claude main | Sonnet | done |
| Phase 3 — Wiki generation | opencode | DeepSeek Flash v4 | done |
| Phase 4 — HTML docs | opencode | DeepSeek Flash v4 | done |

## What
<One sentence>

## Output
<Key artefacts>

## Files
| File | Action |
|------|--------|
| `.overstack/graph/knowledge-graph.json` | created |
| `llmwiki/wiki/index.md` | created/modified |
| `llmwiki/html/onboarding-<slug>.html` | created |

## Notes
- Invoked via: `/orca-onboard` skill

## Origin
- **Draft:** `wiki/draft/orca/DDMMYY-<ten>.md`
- **Commit:** _(filled by verify-before-commit)_
- **Date promoted:** _(filled by verify-before-commit)_

3. 更新 wiki 索引和日志:

  • llmwiki/wiki/index.md — 追加:| [DDMMYY-<ten>](draft/orca/DDMMYY-<ten>.md) | draft | YYYY-MM-DD |
  • llmwiki/wiki/log.md — 追加:## YYYY-MM-DD — orca-onboard — <ten>

4. 更新状态并同步推送 — 必须执行:

  • 更新草稿文件中的 Status 列,反映实际运行情况
  • 克隆 rheinmir/setup 的 orca 分支,复制更新后的 SKILL.md 并推送:
    git clone [email protected]:rheinmir/setup.git /tmp/rheinmir-setup-sync -b orca --depth 1
    cp ~/.agents/skills/orca-onboard/SKILL.md /tmp/rheinmir-setup-sync/skills/orca-onboard/SKILL.md
    cd /tmp/rheinmir-setup-sync
    git add .
    git commit -m "skill: orca-onboard — wrap understand-anything, DeepSeek mechanical dispatch"
    git push origin orca
    rm -rf /tmp/rheinmir-setup-sync
    

仅当技能未生成任何产物且未作出任何决策时,才跳过输出报告。

分支
ID类型条件行为跳过/失败返回
B01user_optional@<draft> (RESUME_MODE)从草稿读取各阶段的状态;done 阶段则跳过草稿缺少 Project root: → root 为空 → exit 1第一个尚未 done 的阶段
B02user_optional--update + 已有 graph仅重新分析变更的文件,并合并到现有 graph/domain/wiki没有 graph/meta.json → exit 1;changedFiles 为空 → 完整重建W03
B03user_optional--full删除 .overstack/graph/,运行完整流程—W03
B04conditional_required已有 graph,且未指定标志跳过 Phase 1,使用旧 graph—W06
B05capability_optionalcode-graph dep-health.py --json 返回 status == "ok"1.7 CODE-GRAPH MCP INDEX:对每个代码仓库运行 reindex_repo,验证 get_stats() >0,并写入 concepts/code-graph-nav.mddegraded/absent → 跳过W06
B06recoveryopencode 在 1.3、Phase 3、Phase 4 STEP A 中不可用/卡住Claude 主线程自行处理(分析批次/wiki/组装 JSON)— Phase 4 仍通过 skeletonPhase 4 完全失败 → 直接调用 docs-site-macos该阶段的下一步
B07user_optional--skip-wiki跳过 Phase 3—W08
B08conditional_required单体仓库(N_SVC ≤ 1)modules:[]、docker:null → skeleton 自动隐藏 Modules/Docker 标签页多服务 → 显示 Docker 标签页W08
验证与停止

使用脚本进行确定性检查:Phase 1 末尾的 gate(必须有 2 个文件)、验证 graph 1.6(无重复 ID、无悬空边、每个文件节点恰好属于 1 个 layer、tour nodeIds 均存在)、断言 STEP B 中的 {{TITLE}}/{{ONBOARD_JSON}} 均已替换、Phase 4 末尾运行 ls "$OUT"。需要人工审查:layers/tour、domain graph(对照实际 file:line)、wiki 质量。当草稿中 4 个阶段均为 done 时停止;批次最多重试 1 次。

示例
  • 正向: 在包含 180 个文件且有 opencode 的仓库上运行 /orca-onboard ~/code/zca-bridge → 在终端输出草稿 + dispatch board → 用户回复“ok” → 生成 180 个节点、7 个 layer 和 9 个步骤的 tour → domain-graph.json 包含 3 个 domain → wiki concepts/entities → llmwiki/html/onboarding-zca-bridge.html + wiki-graph.html;草稿中的 4 个阶段均为 done。
  • 边界/失败: 在从未执行过 onboard 的仓库上运行 /orca-onboard --update → Phase 0 输出“❌ --update requires existing graph. Run without --update first.”并 exit 1,不创建草稿。
  • 边界: opencode 在 Phase 4 STEP A 卡住 → Claude 按照 skeleton schema 自行编写 onboard.json,然后运行 STEP B;不要直接编写 HTML。

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