readme-skill

Readme.skill — AI-Native 开发者档案生成器

You (the AI agent invoking this skill) will read local Claude Code + Codex CLI

• Kiro (AWS) + Trae (ByteDance) data, compute a fixed set of dimensions, and

render a Markdown profile under ./output/ in the user's requested language (Chinese by default; English when the user asks in English or explicitly requests English). You do all of the work — read the files with Read, query sqlite via Bash, and synthesize the prose yourself. Do not write helper scripts; the skill is the recipe.

支持的 4 个 AI 编程工具（任一缺失都自动降级跳过）：

1. Claude Code (~/.claude/) — Step 2

2. Codex CLI (~/.codex/) — Step 3

3. Kiro CLI / IDE (~/.kiro/ + ~/.local/share/kiro-cli/) — Step 3b

4. Trae IDE (~/Library/Application Support/Trae/ + 项目 .trae/) — Step 3c

默认行为：对外分享版 —— 项目名匿名、敏感信息脱敏。

如果用户明确说"私人版 / 不要脱敏 / show real names"，跳过匿名步骤。

Step 1 — 准备

cd <repo-with-this-skill>   # e.g. ~/Projects/Readme.skill
mkdir -p output
DATE=$(date +%Y%m%d)

Decide anonymization mode (default = on). Build an in-memory mapping real_path → "项目 A/B/C" as you encounter project paths in later steps. Use the same mapping consistently across all sections.

Step 2 — 读取 Claude Code 数据 (~/.claude/ + 项目 .claude/)

2.1 预聚合统计（最权威，先看这个）

Read ~/.claude/stats-cache.json. Extract:

| 字段 | 含义 | | --- | --- | | totalSessions | session 总数 | | totalMessages | 消息总数 | | firstSessionDate | 首个 session ISO 时间 | | longestSession.{duration,messageCount,timestamp} | 最长 session | | hourCounts | {hour: count} 24h 热力 | | modelUsage[model].{inputTokens,outputTokens,cacheReadInputTokens,cacheCreationInputTokens} | 每模型 token 细分 | | dailyActivity[].{date,messageCount,sessionCount,toolCallCount} | 每日活跃 | | dailyModelTokens[].{date,tokensByModel} | 每日按模型 token |

派生量（你来算）:

• claude_tokens_spent = Σ (inputTokens + outputTokens + cacheCreationInputTokens) —— 真实新付费 token
• claude_cache_read = Σ cacheReadInputTokens —— 缓存复用，反映 prompt-caching 熟练度
• cache_to_spent_ratio = claude_cache_read / claude_tokens_spent —— 比值越大越熟

2.2 Slash-command 热度

~/.claude/history.jsonl —— 每行 {display, timestamp, project, sessionId}。

# Top 15 slash commands
jq -r 'select(.display | startswith("/")) | (.display | split(" ")[0])' \
   ~/.claude/history.jsonl | sort | uniq -c | sort -rn | head -15

# 总条数 vs 命令条数 vs 直接 prompt 条数
total=$(wc -l < ~/.claude/history.jsonl)
cmd=$(jq -r 'select(.display | startswith("/")) | .display' ~/.claude/history.jsonl | wc -l)
echo "total=$total cmd=$cmd plain=$((total - cmd))"

记录：/effort、/plan、/skill*、/usage、/clear、/resume、/compact、/init 各自次数。

2.3 项目分布 (~/.claude/projects/)

Each subdir is one project; per-project *.jsonl files = sessions. The dir name encodes the absolute path with / → - (ambiguous when the original path itself contains -).

# Top 15 by session-file count
for d in ~/.claude/projects/*/; do
  n=$(ls "$d"*.jsonl 2>/dev/null | wc -l | tr -d ' ')
  echo "$n $(basename "$d")"
done | sort -rn | head -15

To recover the canonical real path (so you can run git log later), read the cwd field from the first JSONL in each dir:

head -1 ~/.claude/projects/<encoded>/*.jsonl 2>/dev/null \
  | jq -r 'select(.cwd) | .cwd' | head -1

2.4 计划与 skill 自研

Claude Code 的 plan 文件目录不是固定值。默认在 ~/.claude/plans, 但用户可以通过 plansDirectory 改到项目工作目录下，例如 "./.claude/plans"。统计 plans 时必须先解析候选 plan 目录，不能只枚举 ~/.claude/plans/*.md。

解析规则：

• 先从 ~/.claude/projects//.jsonl 的 cwd 字段恢复 Claude Code 访问过的项目根目录。
• 对每个项目根目录，按 Claude Code settings 优先级读取：

.claude/settings.local.json > .claude/settings.json > ~/.claude/settings.json > default。

• 如果有效 settings 中存在 plansDirectory：
• 绝对路径保持不变；
• ~/... 展开为 $HOME/...；
• ./... 或其他相对路径按该项目根目录解析。
• 如果没有配置，使用默认 ~/.claude/plans。
• 把所有候选目录下的 *.md 真实路径去重后，再统计 plan 数量和标题。

# Plan titles (first # heading of each plan) from all resolved plan dirs.
# Include ~/.claude/plans plus any per-project plansDirectory targets.
# Count plan files by file count, not by title extraction success.
plan_count=<resolved-plan-file-count>
for f in <resolved-plan-files>; do
  awk '/^# / { sub(/^# /, ""); print; exit }' "$f"
done

ls ~/.claude/skills/ | wc -l       # skills installed / authored
ls ~/.claude/tasks/  | wc -l        # tasks tracked
ls ~/.claude/todos/  | wc -l

2.4b Skill 清单（AI 基础设施采集）

For each ~/.claude/skills//SKILL.md and ~/.codex/skills//SKILL.md, use the Read tool to inspect the frontmatter (top of file, between --- markers). Extract name and the full description as YAML semantics dictate.

Support all four YAML scalar styles：

| 写法 | 处理 | | --- | --- | | 单行: description: foo bar | 直接取冒号后内容 | | 引号: description: "foo bar" 或 'foo bar' | 去掉首尾引号 | | > folded（多行折叠） | join indented continuation lines with spaces | | \| literal（多行保留） | preserve line breaks |

停止条件：遇到下一个未缩进的 frontmatter key（行首无空格且形如 key:），或遇到关闭的 --- 行。如果 description 字段缺失，回落到 <目录名> (no description)。

绝不使用 head \| grep —— 那会把 >/\| 多行风格静默截断到只剩 >，这是 v2.2 之前的真实 bug。务必 Read 完整 frontmatter 后按 YAML 语义解析。

枚举候选 skill 目录：

ls -d ~/.claude/skills/*/ ~/.codex/skills/*/ 2>/dev/null

然后对每个目录：Read 它的 SKILL.md 头部 ~30 行 → 按上表解析 YAML → 输出 <source>|<name>|<full_description>。

记录每个 skill 是「自建」还是「安装」。如果 skill 目录下有 git remote 指向用户自己的 repo，标记为自建；否则标记为安装。

2.5 配置深度

Read ~/.claude/settings.json. Count:

• hooks 个数（结构化自动化能力）
• mcpServers 个数（外部能力接入）
• permissions.defaultMode

Step 3 — 读取 Codex CLI 数据 (~/.codex/)

3.1 SQLite (read-only)

The primary analytics store is ~/.codex/state_5.sqlite, table threads. Always open with mode=ro so you can never write:

SQ='sqlite3 file:'"$HOME"'/.codex/state_5.sqlite?mode=ro&immutable=1'

# Aggregate
$SQ "SELECT COUNT(*), SUM(tokens_used), MIN(created_at), MAX(created_at) FROM threads;"

# Model breakdown (note: empty/NULL model = older sessions, label as 'Codex (未标注)')
$SQ "SELECT COALESCE(NULLIF(model,''),'Codex(未标注)'), COUNT(*), SUM(tokens_used) \
     FROM threads GROUP BY 1 ORDER BY 3 DESC;"

# Reasoning effort distribution (xhigh / high / medium / low / unspecified)
$SQ "SELECT COALESCE(NULLIF(reasoning_effort,''),'unspecified'), COUNT(*) \
     FROM threads GROUP BY 1 ORDER BY 2 DESC;"

# Top 15 working dirs
$SQ "SELECT cwd, COUNT(*), SUM(tokens_used) FROM threads \
     WHERE cwd != '' GROUP BY cwd ORDER BY 2 DESC LIMIT 15;"

# Hour-of-day heatmap
$SQ "SELECT strftime('%H', datetime(created_at,'unixepoch')), COUNT(*) \
     FROM threads GROUP BY 1 ORDER BY 1;"

# Day-of-activity timeseries
$SQ "SELECT date(created_at,'unixepoch'), COUNT(*) FROM threads GROUP BY 1;"

# Sample titles + first user messages for keyword extraction (titles only — no body)
$SQ "SELECT title FROM threads WHERE title != '' ORDER BY created_at DESC LIMIT 200;"
$SQ "SELECT first_user_message FROM threads WHERE first_user_message != '' \
     ORDER BY created_at DESC LIMIT 200;"

# CLI versions used (Codex evolution signal)
$SQ "SELECT cli_version, COUNT(*) FROM threads WHERE cli_version != '' \
     GROUP BY 1 ORDER BY 2 DESC LIMIT 10;"

# --- 以下为 v2.0 新增查询 ---

# 月度聚合（Evolution 曲线用）
$SQ "SELECT strftime('%Y-%m', datetime(created_at,'unixepoch')), COUNT(*), \
     SUM(tokens_used), COALESCE(NULLIF(model,''),'unknown') \
     FROM threads GROUP BY 1,4 ORDER BY 1,3 DESC;"

# CLI 版本时间线（Evolution 曲线用）
$SQ "SELECT cli_version, MIN(date(created_at,'unixepoch','localtime')), \
     MAX(date(created_at,'unixepoch','localtime')), COUNT(*) \
     FROM threads WHERE cli_version != '' GROUP BY 1 ORDER BY 2;"

# 每项目 token 消耗（双工具编排分析用）
$SQ "SELECT cwd, COALESCE(NULLIF(model,''),'unknown'), COUNT(*), SUM(tokens_used) \
     FROM threads WHERE cwd != '' GROUP BY 1,2 ORDER BY 1,4 DESC;"

3.2 Codex 全局历史

~/.codex/history.jsonl — {session_id, ts, text}. Sample for keywords:

wc