engineering-principle-recorder

engineering-principle-recorder is a skill for Claude Code, Codex from TashanGKD/tashan-cursor-skills. It costs 118 tokens per session (3,919 once invoked), scanned A, original, MIT.

A process for turning an agreed engineering rule into instructions that an AI system or codebase must follow during execution.

In plain words
What is it for?
Use it to clarify a rule, classify it, and record it in the appropriate role instructions, rules, or tracking documents.
Why use it?
It helps ensure that an important operating principle remains active in later sessions instead of being forgotten in a note.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to clarify a rule, classify it, and record it in the appropriate role instructions, rules, or tracking documents.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tashangkd/tashan-cursor-skills/engineering-principle-recorder
Install

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.

Any agent
npx skills add TashanGKD/tashan-cursor-skills --skill engineering-principle-recorder
Clone the repo
git clone --depth 1 https://github.com/TashanGKD/tashan-cursor-skills

Made for: Claude Code, Codex.

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README.md
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<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/engineering-principle-recorder"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/engineering-principle-recorder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 118 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,919 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00118 $0.03919
Opus 5 $0.00059 $0.01959
Sonnet 5 $0.00024 $0.00784
Haiku 4.5 $0.00012 $0.00392

Measured 8d ago against content hash 9b39c8622381, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

engineering-principle-recorder 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.

skills/engineering-principle-recorder/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

工程/执行原则录入器(engineering-principle-recorder)

核心目标:一条原则被说出来 → 两周后,另一个 AI session 自动被它约束。 这不是「记在本子里」,而是「写入 AI 每次必读的执行层」。


认知根

认知根:_内部总控/认知结构/L1_系统性文档/系统架构思维维度/Skill体系设计原则_v1.0.md 关联:本 Skill 维护「Skill 体系执行约束」的完整性,与设计原则中「执行层」概念直接对应。


两类原则的本质区别(AI 执行者必须先理解)

类型 内容 走哪里
认知原则 郑总如何思考/判断(「先从小点出发升维」) cognitive-extract-principle → L1.5
执行原则 AI系统/代码应如何运行(「LLM调用不截断」) → 本 Skill → Role Skill / Rule / 追踪台

知识导航表(执行前按顺序读取)

层级 文档 读取目的
D0 _内部总控/元项目导航.md 提取当前活跃项目路径,用于 Step 2-D 的代码搜索目录和追踪台路径
.cursor/skills/skill-index/SKILL-INDEX.md 确认 Step 2-C 中相关 Role Skill 的实际文件路径

激活后立即执行

Step 0  【读取必要上下文】(静默完成,不向用户输出)
        Read: _内部总控/元项目导航.md
        → 记录当前活跃项目名称 + 代码路径 + 追踪台路径
        Read: .cursor/skills/skill-index/SKILL-INDEX.md
        → 记录 Role Skill 的实际文件路径

Step 1  【精确化原则 + 类型分类(必须与用户交互完成)】

        ⚠️ 执行铁律:先确认原则精确表述 + 分类,再执行写入。禁止跳过。
        ⚠️ 分类完成后,无需用户再次指示,立即执行对应的 Step 2。

        Step 1-1  精确化原则表述
                  向用户确认:「我理解您要立的原则是:[提炼后的精确表述]。
                  判断标准是:[什么情况算违反了此原则]?」
                  → 等待用户确认后,以确认版本作为写入内容,不用原话

        Step 1-1.5  【等效三问声明(A1.9 门禁前置满足)】
                    本 Skill 在 Step 1 已等效完成 skill-rule-修改规范 三问:
                    ① 根因 = Step 1-1 用户确认的原则内容(为什么要改)
                    ② 影响范围 = Step 1-2 分类后确定的写入目标文件
                    ③ 验证方法 = Step 3 覆盖报告中的可靠性评估
                    → AI 执行时在 Step 1 末尾内部记录:「A1.9 三问已完成,可继续写入 .cursor/ 文件」
                    → 不需要再次触发 skill-rule-修改规范 的完整流程

        Step 1-2  类型分类

                  ─── 类型 A:认知/思维原则 ───
                  判据:原则描述的是「郑总如何思考/判断/分析问题的方式」
                  示例:「我倾向于先从小点出发」「推断前先验证」
                  处理:告知用户「这条原则描述的是您的思维方式,应通过
                        cognitive-extract-principle 流程录入到 L1.5 底层原则库。
                        本 Skill 在此停止——请您说『提炼原则』以激活该流程。」
                  → 本 Skill 在此终止,不执行 Step 2 和 Step 3。

                  ─── 类型 B:AI 行为约束 ───
                  判据:原则描述的是「AI 执行任务时如何使用工具/读文档/调用资源」
                        (不涉及代码设计,只约束 AI agent 的操作方式)
                  示例:「读文档不截断,分次读但不遗漏」
                        「连接服务器前先确认是哪台机器」
                  → 标记 B = true,进入 Step 2-B

                  ─── 类型 C:工程设计原则 ───
                  判据:原则描述的是「代码/LLM调用/系统架构应如何设计」
                  示例:「LLM 调用上下文不截断,qwen3.5plus 256K 够用」
                        「认证必须复用现有服务,不得重新实现」
                  → 标记 C = true,进入 Step 2-C

                  ─── 类型 D:当前代码存在违规 ───
                  判据:用户明确指出「现在代码里已有违反这条原则的地方」
                        OR 本 Skill 执行 Step 2-C 后判断极可能有历史违规
                  → 标记 D = true,在 Step 2-C 完成后进入 Step 2-D

                  ⚠️ 多类型并发:B+D 和 C+D 都是合法组合,逐类处理,不跳过任何一类
                  ⚠️ 若分类不确定 → 问用户:「这条原则是关于AI的操作方式(B),
                     还是代码的设计方式(C),还是两者都是?」

                  ─── 与相似 Skill 的区分 ───
                  「这里有个规范问题/这次违反了规范」(已有规范被违反一次)→ project-convention-resolver
                  「要立一条新原则」(原则本身尚不存在)→ 本 Skill
                  若不确定 → 问用户:「是要修复这次违反,还是建立一条新规范?」

Step 2-B  【AI 行为约束 → 写入执行层(B类)】(仅当 B = true)

          ⚠️ 必须实际工具调用写文件,禁止只口头描述「已录入」

          B-1  判断写入目标(判据如下)
               普遍约束(对所有角色/所有会话均生效)→ session-bootstrap.mdc
               特定角色约束(仅当某 Role Skill 激活时生效)→ 对应 Role Skill 的约束节
               判断标准:「去掉所有角色限定词,这条原则还成立吗?」
               → 是 → 普遍约束 → session-bootstrap
               → 否 → 特定角色约束 → 对应 Role Skill

          B-2  Read 目标文件(必须先读后写)

          B-3  按 skill-rule-修改规范 备份
               Shell: cp [目标文件] [history/目录/文件名_vX_YYYYMMDD_before_principle.md]

          B-4  StrReplace 写入
               → 在目标文件「约束」节或等效节末尾追加:
               `- [原则标题]:[精确描述](来源:engineering-principle-recorder,[日期])`

          B-5  StrReplace 追加变更记录到文件末尾

          B-6  输出:「[B类] 已写入 [文件路径] / [节名称]」
               → 完成后无需等待,继续检查是否有 D = true

Step 2-C  【工程设计原则 → 写入 Role Skill 第一性原理(C类)】(仅当 C = true)

          ⚠️ 必须实际工具调用写文件,禁止只口头描述「已录入」

          C-1  识别最相关的 Role Skill(可多选,用 SKILL-INDEX.md 确认路径)
               LLM/AI调用/Prompt → `.cursor/skills/role-AI工程师/SKILL.md`
               部署/运维/服务器 → `.cursor/skills/role-DevOps/SKILL.md` 或 `REFERENCE.md`
               前端实现 → `.cursor/skills/role-前端开发/SKILL.md`
               后端实现 → `.cursor/skills/role-后端开发/SKILL.md`
               技术架构 → `.cursor/skills/role-技术架构师/SKILL.md`
               所有角色通用 → 同时写 session-bootstrap(B类处理)

          C-2  Read 目标 Skill 文件
               → 找「第一性原理」节或等效约束节
               → 若无该节 → 在 Skill 文件正文开头(---分隔符之后)新建「## 第一性原理」节
               → 检查是否有语义相近的已有原则(如有矛盾 → 暂停,告知用户)

          C-3  按 skill-rule-修改规范 备份 + StrReplace 写入 + 追加变更记录
               写入格式:`- [原则标题]:[精确描述](来源:engineering-principle-recorder,[日期])`

          C-4  输出:「[C类] 已写入 [文件路径] / [节名称]」
               → 完成后无需等待,继续检查是否有 D = true
               → ⚠️ 若任一目标文件写入失败:
                  - 在 Step 3 报告中标注「未覆盖:[文件路径](写入失败)」
                  - StrReplace 追加到 PENDING-EXPERIENCES.md:
                    `| [今日] | engineering-principle-recorder | 步骤偏差 | 原则[名称]写入[文件]失败,需补录 | 🔲 待处理 |`
                  - 不静默跳过,不假装写入成功

Step 2-D  【代码违规审计 + 追踪(D类)】(仅当 D = true)

          D-1  构建搜索模式(必须至少 3 个候选词,覆盖不同代码写法)
               基于原则语义推导代码中可能的违规模式,例如:
               「不截断」原则 → 搜索词:`[:6000]` `[:3000]` `[:500]` `max_tokens=` `content[:`
               「必须复用认证」原则 → 搜索词:`jwt.encode` `create_token` `def authenticate`
               ⚠️ 不同原则需不同搜索词,必须基于原则语义推导,不可照抄示例

          D-2  执行代码搜索
               Grep: [当前项目代码目录](从 Step 0 的元项目导航获取路径)
               → 找出语义违规位置(非机械匹配,需要 AI 判断)
               → 区分「日志打印截断」([:120] 等,无害)vs「LLM输入截断」(有害)

          D-3  写入技术问题追踪台
               Read: [项目路径]/技术架构师/技术问题追踪台.md
               → 对每个违规位置,StrReplace 追加一条 issue:
               格式:| P1 | [日期] | [文件路径:行号] | 违反「[原则名]」:[具体描述] | 🔲 待修复 |

          D-4  输出违规清单给用户:
               「发现 N 处违规(已记录到追踪台):
               1. [文件:行号] — [描述]
               ...
               是否立即触发 bug-fix-loop-coordinator 修复?」
               ⚠️ 等待用户回复后继续执行 Step 3(无论用户如何回答,Step 3 必须执行)

Step 3  【输出覆盖报告】(所有工具调用完成后才执行,禁止提前输出)

        ⚠️ Step 3 是强制步骤,无论走了哪些 Step 2,都必须执行

        输出格式:
        ────────────────────────────────────────────
        ✅ 原则录入完成

        原则名称:[提炼后的标题]
        原则内容:[精确描述,含判断标准]

        执行层覆盖:
        [B类] [文件路径] / [节名称]:alwaysApply → 每次会话强制生效(高可靠)
        [C类] [文件路径] / [节名称]:角色激活时必读(中高可靠)
        [D类] 发现 N 处历史违规 → 已记录到 [追踪台路径]

        可靠性评估:
        - [当前录入方式] → [可靠性等级]
        - 如需最高可靠性建议:[具体建议,如「也写入 session-bootstrap」]
        ────────────────────────────────────────────

Read the full file on GitHub · 267 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. 8d ago First seen · 267 lines · 118 tokens per session scan A 9b39c8622381

Subscribe to this mod's changes

engineering-principle-recorder is a skill published in the GitHub repository TashanGKD/tashan-cursor-skills (20 stars, last pushed 5mo ago), licensed MIT. It adds 118 tokens to every session and 3,919 once invoked, about $0.0006 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 2026-09-03.

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