AI-Coding-Insights: Instructions file for Claude Code

CLAUDE.md

AI-Coding-Insights CLAUDE.md is an instructions file for Claude Code from BigKunLun/AI-Coding-Insights. It costs 4,427 tokens per session, scanned A, original, MIT.

Project instructions for AI-Coding-Insights, a plugin that analyzes Claude Code session records and produces reports about coding-tool use.

In plain words
What is it for?
Use them when developing or operating AI-Coding-Insights, including scanning session data, checking results, rendering reports, and running tests.
Why use it?
They give the coding agent the repository’s purpose, commands, and rules for testing and debugging the plugin.

Instructions file for Claude Code

Written for Claude Code: SessionEnd hook event. Also seen: mentions CLAUDE.md; mentions Claude Code; mentions Codex.

This is BigKunLun/AI-Coding-Insights's own configuration. It tells Claude Code how to work on AI-Coding-Insights itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AI-Coding-Insights configures →

Reuse

Borrowing it

Nothing to install: this file belongs to BigKunLun/AI-Coding-Insights. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/BigKunLun/AI-Coding-Insights/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/BigKunLun/AI-Coding-Insights

Made for: Claude Code.

Wrote 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.

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README.md
[![agentmods](https://agentmods.dev/badge/instructions/bigkunlun/ai-coding-insights/claude-md.svg)](https://agentmods.dev/instructions/bigkunlun/ai-coding-insights/claude-md)
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<a href="https://agentmods.dev/instructions/bigkunlun/ai-coding-insights/claude-md"><img src="https://agentmods.dev/badge/instructions/bigkunlun/ai-coding-insights/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 4,427 This file is loaded in full into every session.
When invoked 4,427 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.04427 $0.04427
Opus 5 $0.02214 $0.02214
Sonnet 5 $0.00885 $0.00885
Haiku 4.5 $0.00443 $0.00443

Measured 6d ago against content hash 5b680081a982, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

AI-Coding-Insights CLAUDE.md 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 6d 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.

CLAUDE.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

项目定位

评估一个人对 AI 编码工具的使用情况:分析其本机的 Claude Code 会话记录,做深度分析,给出画像与改进建议。形态是 Claude Code plugin,由用户本人手动触发,产出本机报告。机器只给分析与证据,结论与奖惩判决在人。

常用命令

uv run pytest                                  # 全量测试
uv run pytest tests/test_window.py             # 单文件
uv run pytest tests/test_window.py::test_xxx   # 单用例

# 规则层手动调试(正常由 skill 编排调用)
uv run python -m ai_coding_insights scan --plugin-root . --emit-batches ~/.ai-coding-insights/run

# 指定来源(不传则跟触发环境走)
uv run python -m ai_coding_insights scan --source codex --emit-batches ~/.ai-coding-insights/run

# 安装器预演:看 playbook 会落到哪、有没有走降级版(不写盘)
uv run python -m ai_coding_insights install --print

零运行时依赖(纯 stdlib),dev 仅 pytest。

规则层共 8 个子命令,正常由 skill 编排调用,单独调试时也可直接跑(点到存在即可,参数以代码为准)。这份清单有测试守着tests/test_skill_contract.py):子命令名与条数必须与 cli.py 实际注册面一致,加了子命令不补这里即测试红。

  • scan —— 扫描 / 窗口决策 / 分批 / 硬指标;--emit-batches 是编排主路径,四种输出形态互斥(--emit-batches / --profile-input / --json / 默认渲染 HTML)。
  • init —— 交互配置向导,从本机会话来源勾选团队归属。
  • verify-obs —— 校验 LLM 观测(obs)对批次的覆盖与 posture 计数完整性。
  • render-profile —— 渲染最终画像 HTML 报告。
  • auto-scan —— SessionEnd hook 后台自动评估(接线在 hooks/hooks.json;自带 lock 防重入 + 滚动日志,失败对用户静默)。
  • reset —— 清空本机可再生产物(snapshots/ / reports/ / run/ / auto-scan.log)解除 30 天增量窗口闸门,并把今日写进 .auto-scan.lock(而非删它),压住 SessionEnd 的 auto-scan 当天抢先写新快照重新武装闸门——这是「reset 后重跑仍 too_soon」的根因修复。按白名单删、--dry-run 只预览,永不碰 config.toml 与会话原文。slash 入口 commands/reset.md
  • install —— 统一安装器:把单一真相源 playbookskills/ai-coding-insights/SKILL.md)渲染并落到当前 harness 该放的位置。「装哪一家」与取数一样跟触发环境走--source 可覆盖);--print 只预演落点不写盘,目标已存在须 --force 才覆盖(用户可能改过自己的 playbook)。三个薄适配器在 installers.py,各配一条契约测试。无子代理能力的 harness 会装降级编排版,且降级状态写进报告 caveat——静默劣化是本项目定义的最危险故障。
  • calibrate —— 手动调试命令:给出各指标分布与当前阈值的分位定位,不进 SKILL.md 编排、不产 HTML。两种取数来源:默认读 snapshots/ 里已脱敏的历史标量;--replay 则把本机会话按等长窗口切片重放成伪快照(--replay-window 默认对齐 WINDOW_FLOOR_DAYS--replay-step 可滑动)。回放存在的理由:窗口闸门是「不足 30 天即 too_soon」,快照最快 30 天落一个,攒 20 个要 1.6 年——靠等快照校准阈值走不通,而档位闸门用的全是规则层硬指标,可直接从既有会话按同口径重算。切片长度必须与评估窗口同口径,改小即跨口径(阈值是按「一个 30 天窗口内的量级」定的)。回放不跑 git log、不跑 LLM,git 三键与姿态四档整键不放进伪快照(未测量 ≠ 0)。只给本机单人分布,不是人群分位;样本不足时逐层挂 caveat,且 n < 5 时压住「过门/未过门」的定性读法,只给数字。

Read the full file on GitHub · 81 lines

Changes

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.

  1. 6d ago First seen · 81 lines · 4,427 tokens per session scan A 5b680081a982

Subscribe to this mod's changes

AI-Coding-Insights CLAUDE.md is an instructions file published in the GitHub repository BigKunLun/AI-Coding-Insights (5 stars, last pushed 18d ago), licensed MIT. It adds 4,427 tokens to every session, about $0.0221 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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