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 RickyTong1/audit-harness --skill audit-report-dailygit clone --depth 1 https://github.com/RickyTong1/audit-harnessWrote 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/rickytong1/audit-harness/audit-report-daily)<a href="https://agentmods.dev/skills/rickytong1/audit-harness/audit-report-daily"><img src="https://agentmods.dev/badge/skills/rickytong1/audit-harness/audit-report-daily/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rickytong1/audit-harness/audit-report-daily"><img src="https://agentmods.dev/badge/skills/rickytong1/audit-harness/audit-report-daily.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00079 | $0.01192 |
| Opus 5 | $0.00039 | $0.00596 |
| Sonnet 5 | $0.00016 | $0.00238 |
| Haiku 4.5 | $0.00008 | $0.00119 |
Grade A, and why
audit-report-daily scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/report-daily — 审计驱动工作日报
触发方式
/report-daily # 生成今天的日报（截止到当前时刻）
/report-daily 20260319 # 生成指定日期的日报
/report-daily review # 生成日报 + 晨间自我修正报告
数据源
日报的每个数字都有明确的数据源，不允许"凭记忆"填写。
所有数据来自 .claude/runs/ 目录：
| 日报板块 | 数据源 |
|---|---|
| 任务总览 | .claude/runs/index.json |
| 工具操作统计 | .claude/runs/*/audit_trail.jsonl 中的 tool 记录 |
| 变更记录 | .claude/runs/*/audit_trail.jsonl 中含 "change"/"prompt"/"edit" 的条目 |
| [AUDIT] 块汇总 | .claude/runs/audit_pending.jsonl + 各 session 的 audit_trail |
| 异常与告警 | .claude/runs/*/anomalies.json（如果存在） |
| 用户反馈与修正 | audit_trail 中含 "user_correction" 的条目 |
| 昨日待办跟进 | 前一天日报（.claude/runs/daily/ 下） |
执行步骤
1. 收集数据
target_date="${1:-$(date +%Y%m%d)}"
# 1. 读取 index.json，筛选 target_date 相关的 session
# 2. 逐个读取各 session 的 audit_trail.jsonl
# 3. 读取 audit_pending.jsonl（可能有未归档的最新数据）
# 4. 如果有前一天的日报，提取 §七 待办（用于跟进）
2. 生成日报
按以下结构填充，每个数字旁标注数据来源：
# 工作日报 | {DATE}
> 自动生成时间: {NOW}
> 数据来源: .claude/runs/index.json + 各 session audit_trail
> 覆盖时间段: {DATE} 00:00 — {DATE} 23:59
---
## 一、任务总览
| # | 类型 | session_id | 任务描述 | 状态 | 审计记录数 |
|---|------|-----------|---------|------|-----------|
> 来源: .claude/runs/index.json
---
## 二、操作统计
| 指标 | 数量 | 来源 |
|------|------|------|
| Write/Edit 操作 | {N} | audit_trail tool=Write/Edit |
| Bash 执行 | {N} | audit_trail tool=Bash |
| [AUDIT] 块 | {N} | audit_pending + audit_trail |
---
## 三、变更记录
| # | 时间 | 变更对象 | 变更内容 | 来源 |
|---|------|---------|---------|------|
> 从 audit_trail 和 audit_pending 中提取涉及文件修改的条目
---
## 四、用户反馈与修正
| # | 反馈内容 | 修正后 | 已固化到 |
|---|---------|-------|---------|
> 从 audit_trail 中提取 user_correction 类型条目
---
## 五、昨日待办跟进
| # | 昨日待办 | 今日状态 | 说明 |
|---|---------|---------|------|
---
## 六、明日待办
- [ ] ...
---
## 七、审计完整性
| 检查项 | 结果 |
|--------|------|
| 所有 session 有审计记录 | {结果} |
| [AUDIT] 块已持久化 | {结果} |
| 用户修正已固化 | {结果} |
3. 保存
mkdir -p .claude/runs/daily
# 写入 .claude/runs/daily/{YYYYMMDD}_daily.md
What ships with it
1 file 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.
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.
- 11d ago First seen · 147 lines · 79 tokens per session scan A 87fc0bf1e3be
audit-report-daily is a skill published in the GitHub repository RickyTong1/audit-harness (472 stars, last pushed 3mo ago), licensed MIT. It adds 79 tokens to every session and 1,192 once invoked, about $0.0004 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 2026-08-30.
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