Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ValorVie/custom-skills --skill work-log-codexgit clone --depth 1 https://github.com/ValorVie/custom-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/valorvie/custom-skills/work-log-codex)<a href="https://agentmods.dev/skills/valorvie/custom-skills/work-log-codex"><img src="https://agentmods.dev/badge/skills/valorvie/custom-skills/work-log-codex.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00067 | $0.01816 |
| Opus 5 | $0.00034 | $0.00908 |
| Sonnet 5 | $0.00013 | $0.00363 |
| Haiku 4.5 | $0.00007 | $0.00182 |
Grade A, and why
work-log-codex scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work Log Codex
根據本機的 Codex 與 Claude Code session 紀錄,產生可讀、可保存的工作日誌。
When To Use
Use this skill when the user wants to:
- 針對
今天、昨天、本週或自訂日期區間整理工作日誌 - 想知道某段時間做了哪些專案、主要交付與研究內容
- 想把對話紀錄與 git 歷史整理成可讀的 Markdown 日誌
- 想輸出到
docs/work-logs/或 Obsidian
Workflow
這個 skill 的最佳路徑不是單次摘要,而是 parser -> project-level AI summary -> final synthesis -> layered formatter。
Step 1: 解析時間範圍
支援:
todayyesterdaythis-weekthis-monthYYYY-MM-DDYYYY-MM-DD YYYY-MM-DD
可選輸入:
--project <name>:只看單一專案--output/--format:控制輸出方式
Step 2: 執行 parser
優先用 uv run python,失敗再 fallback python3。
SKILL_DIR="$PWD/.agents/skills/work-log-codex"
PYTHONPATH="$SKILL_DIR" uv run python -m wl_parser.work_log_parser \
TIME_RANGE \
[END_DATE] \
--timezone "Asia/Taipei" \
[--project "PROJECT"] \
--claude-home "$HOME/.claude" \
--codex-home "$HOME/.codex" \
--emit-project-dir /tmp/wl_projects \
> /tmp/wl_report.json \
|| PYTHONPATH="$SKILL_DIR" python3 -m wl_parser.work_log_parser \
TIME_RANGE \
[END_DATE] \
--timezone "Asia/Taipei" \
[--project "PROJECT"] \
--claude-home "$HOME/.claude" \
--codex-home "$HOME/.codex" \
--emit-project-dir /tmp/wl_projects \
> /tmp/wl_report.json
Step 3: 逐專案 AI 摘要
不要直接把整份 /tmp/wl_report.json 全讀進上下文。優先讀:
/tmp/wl_projects/manifest.json- 每個 project bundle JSON
prompts/project_summary.md
每個專案各做一次摘要:
- 優先從
git_commits理解實際交付主題 - 用
session_summaries補足未提交、研究、規劃中的工作 session_hints只當快速導覽,真正判讀以session_summaries為主- 合併 related commits,不要逐 commit 轉寫
- 沒有 commit 時才寫成研究/探索
- Token 成本不是主要限制;必要時可以逐專案、多次呼叫 AI 做摘要,不要為了省 token 犧牲語意品質
將每個專案摘要暫存到 /tmp/wl_project_<name>.md。
Step 4: 生成最終摘要前段
讀取:
/tmp/wl_report.json的summary- 所有
/tmp/wl_project_<name>.md prompts/final_summary.md
產出 /tmp/wl_summary.md,內容必須只有:
### 當日總結### 逐專案摘要
Step 5: formatter 組裝
預設輸出是 report + appendix 兩個檔案;debug 只有在明確要求時才產生。
主報告只保留:
### 當日總結### 逐專案摘要### 工時統計### 每日摘要
What ships with it
24 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/report-template.md 187 B
- prompts/final_summary.md 1.0 KB
- prompts/project_summary.md 1.4 KB
- references/report-schema.md 1.4 KB
- references/sources.md 960 B
- scripts/__init__.py 38 B runs code
- scripts/generate_work_log.py 9.5 KB runs code
- scripts/normalize.py 19 KB runs code
- scripts/render.py 13 KB runs code
- scripts/source_claude.py 9.7 KB runs code
- scripts/source_codex.py 5.5 KB runs code
- tests/fixtures/claude_sample/history.jsonl 137 B
- tests/fixtures/claude_sample/transcripts/repo-b-session.jsonl 221 B
- tests/fixtures/codex_sample/sessions/2026/03/11/rollout-sample.jsonl 521 B
- tests/test_claude_source.py 7.8 KB runs code
- tests/test_cli_smoke.py 4.6 KB runs code
- tests/test_codex_source.py 4.6 KB runs code
- tests/test_formatters.py 11 KB runs code
- tests/test_git_collector.py 1.0 KB runs code
- tests/test_parser.py 18 KB runs code
- wl_parser/__init__.py 62 B runs code
- wl_parser/formatters.py 14 KB runs code
- wl_parser/git_collector.py 4.4 KB runs code
- wl_parser/work_log_parser.py 31 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 172 lines · 67 tokens per session scan A 2e1378f150e8
work-log-codex is a skill published in the GitHub repository ValorVie/custom-skills (5 stars, last pushed 8d ago), licensed MIT. It adds 67 tokens to every session and 1,816 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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