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session-continuity-protocol

该技能规定新会话开局的四步记忆回灌:读取全局项目索引、账号与项目 MEMORY,再用本地语义召回兜底;强调文件层优先,用于跨工作区续接并避免重复询问。它主要提供协议文本,依赖已有记忆文件和 localmem 工具,不含自动校验;文档内权限声明与读写路径存在矛盾。

zhaoxinghua09-cell
zhaoxinghua09-cell
热度 24.10
最近更新 2026-10-17 07:37:08
分类:知识依赖:读写文件 / MCP 服务 / 内部调用大模型应用场景:笔记整理 / 工作流 / 任务管理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add zhaoxinghua09-cell/session-continuity-protocol
Metadata
name
session-continuity-protocol
description
跨工作区 / 跨会话记忆连续性协议(潘布达首发)。触发场景:新会话开局、用户说「续上上下文 / 你还记得吗 / 你失忆了」、或要做任何连续性敏感任务(公众号发稿、品牌资产、发布阻塞、密钥投递、项目状态)之前。加载后严格跑「开局四步」把已固化事实回灌,避免在已定稿事项上重复问用户、避免失忆。真源 = 文件层(_ACTIVE_PROJECTS.md + 账号 MEMORY.md)优先于 localmem 语义层兜底。 适用场景:当需要跨会话连续性协议(开局四步)能力时使用本技能;触发词:continuity、memory、localmem、cross-session、开局四步。
version
1.0.1
agent_created
true
author
潘布达 (Buda Pan) @SynomosAI
license
MIT
license_scope
代码(.py 文件)MIT;本 SKILL.md 与其中理论文本不在 MIT 覆盖范围内(见文末「License & attribution」)
allowed-tools
Read, Glob, Grep, Write, Edit, WebFetch, WebSearch
category
通用技能
platforms
["windows","macos","linux","cli"]
platform_compatibility
["windows","macos","linux"]
read_when
["新会话开始、用户还没说具体任务前(默认主动跑)","用户质疑「你失忆了 / 怎么又忘了 / 昨天不是已经…」","要做公众号发稿、品牌资产、发布阻塞、密钥投递类任务前","跨工作区接续上一个会话的半成品(如推送草稿箱仍卡在哪)"]
tags
["continuity","memory","localmem","cross-session","开局四步","失忆","跨工作区"]
slug
session-continuity-protocol
displayName
跨会话连续性协议(开局四步)
display_name
跨会话连续性协议(开局四步)
title
跨会话连续性协议(开局四步)
description_zh
跨工作区 / 跨会话记忆连续性协议(潘布达首发)。触发场景:新会话开局、用户说「续上上下文 / 你还记得吗 / 你失忆了」、或要做任何连续性敏感任务(公众号发稿、品牌资产、发布阻塞、密钥投递、项目状态)之前。加载后严格跑「开局四步」把已固化事实回灌,避免在已定稿事项上重复问用户、避免失忆。真源 = 文件层(_ACTIVE_PROJECTS.md + 账号 MEMORY.md)优先于 localmem 语义层兜底。
description_en
Cross-workspace and cross-session memory continuity protocol: session-opening and continuity-sensitive task flows so context survives account, workspace and device switches.
classification
{"skillhub":["knowledge"],"iso_25010":["Maintainability"]}
risk_tier
medium
risk_rationale
门禁批量补丁默认 medium(内部约定:本 skill 设计为中等风险):调用 API/读写文件/本地执行,最小权限,密钥走 Secret;若实际涉对外代执行(push/发布/发送/上架)须人工复评,改 high 并走负责人批准。
ai_protocol
true
spec
usk/1.0
interface
{"type":"prompt","entry_point":"SKILL.md","runtime":"none","call_pattern":"prompt"}
input_schema
{"task":{"type":"string","description":"本技能为协议型:新会话开局主动执行「开局四步」,把已固化事实从记忆文件回灌,避免重复询问用户。","required":true}}
output_schema
{"result":"按 SKILL.md 规定的结构化产出(协议步骤 / 团队派单 / 选题打分卡)"}
exit
无进程退出码;由主 agent 依文档执行
capabilities
["memory","continuity","session"]
permissions
{"network":false,"filesystem":false,"subprocess":false}
requirements
{"python_packages":[],"min_python":"3.8"}
changelog
1.0.1: Bilingual rewrite (full EN+ZH, English first); internal platform names neutralized; 1.0.0: initial upload (USK v3)

凡自治之物 · LGD 治理学 · 创造术家族 | 评测协议:skill-quality-gate

English

When to use

  • Session starts and the user has not stated the task yet (run proactively by default).
  • The user questions "you forgot / how come you forgot again / wasn't this settled yesterday".
  • Before continuity-sensitive work: official-account publishing, brand assets, publishing blocks, key delivery, project status.
  • Resuming half-finished work from a previous session across workspaces (e.g. where exactly the push draft box is stuck).
  • Trigger words: continuity, memory, localmem, cross-session, opening four steps.

Not for: anything outside the protocol scope (see body / description).

Usage

Invocation and parameters are detailed in section "I. Opening four steps (run every new session; order mandatory)" below.

Workflow

Step 1 · read the global master index Step 2 · read the account-level source MEMORY Step 3 · localmem semantic recall (fallback) Step 4 · scan project-level MEMORY from the last 14 days

Author: Buda Pan (content-publishing ops lead) · finalized 2026-09-04 · background: the user repeatedly pointed out "amnesia" — the root cause was not a missing plan, but that known facts were not re-loaded via protocol at session start.

Why this protocol is needed

The baseline finding on GitHub about agent memory (memory-systems skill + LoCoMo benchmark): file-level memory reads beat dedicated memory tools — basic file operations already reach 74%, above the 68.5% of dedicated tools like Mem0. So the "local-first minimal stack" already in place is right: no migration, no cloud.

  • localmem-mcp (v0.1.1 installed): SQLite+FTS5+local fastembed, hybrid cosine+keyword retrieval, zero LLM / zero API.
  • Config LOCALMEM_DB_PATH=<your-workspace-root>/_localmem_memories.db — one db shared across workspaces / accounts.
  • Global master index: <your-workspace-root>/_ACTIVE_PROJECTS.md.
  • Account-level source: <memory-root>/MEMORY.md.

The only gap: facts were not re-loaded at session start. Amnesia = the continuity owner failing to run the protocol. This skill turns that protocol into a callable, reusable action.

I. Opening four steps (every new session; order mandatory)

Run all four before any substantive task. < 1 minute; saves repeated user questions.

Step 1 · read the global master index

Read <your-workspace-root>/_ACTIVE_PROJECTS.md

Get: active project list, RACI, per-project block status, latest handoff points — the overview of "what is on my plate now".

Step 2 · read account-level source MEMORY

Read <memory-root>/MEMORY.md

Get finalized hard facts that must never be re-asked. Key sections:

  • 🔴 "Official-account articles · template & VI master entry" — take templates, SynomosAI red VI palette and QR-code paths from here first.
  • Real account name = SynomosAI (CTA reads "Follow 【SynomosAI】"; the old platform purple is forbidden).
  • The 4 big blocks in the push draft box.
  • Publishing-gate iron rule (if a platform flags content as suspicious → do not appeal).
  • Key-delivery iron rule (DPAPI / key_drop; plaintext forbidden).
  • Signature / copyright system.

Step 3 · localmem semantic recall (fallback) Use localmem MCP tools: recall_memory (15 cross-workspace seeds loaded) or search_memory.

  • Model cache: <your-workspace-root>/_localmem_models (must be kept / backed up; search works offline; the model download source now returns 401 and cannot be re-pulled).
  • Recall limit=5~8; hard facts already loaded at file level hit even at low semantic scores.
  • Verified hit queries: brand color, VI, account name, push blocks, project index, WeChat preview pitfalls, publishing gate, SOP.

Step 4 · scan project-level MEMORY from the last 14 days

Glob <your-workspace-root>/*/memory/MEMORY.md  → read the most recently modified

Get: each workspace's own project iron rules (e.g. "base64 QR inlining", "remove old platform name from CTA", "VI iron rules" in the 2026-09-03 workspace).

II. Source hierarchy (whose word wins on conflict)

  1. First source = file layer: _ACTIVE_PROJECTS.md + account MEMORY.md + project MEMORY.md. Conflicts resolve to the file layer.
  2. Second layer = localmem semantic layer: recall fallback only; never write new facts there (facts go to Step 2 file layer).
  3. localmem is only "fallback when I can't recall", never a replacement for the file layer.

III. Seed cheat-sheet (15 core seeds in localmem)

id Content Example hit query
4 SynomosAI brand name + red VI palette + template path "what brand color for the official account"
6 The 4 big push-draft-box blocks "where is the push draft stuck"
9 Publishing-gate iron rule (no appeal when platform flags suspicious) "platform flags content suspicious before publish, what to do"
10 Key-delivery iron rule (DPAPI / key_drop) "how to deliver keys safely" (limit≈8)
13 Pointers to 6 in-flight projects "which projects are active now"
14 WeChat X5 preview pitfall + LAN channel "images don't show in WeChat"
15 Content-publishing ops SOP "how does the publish flow run"

Note: id10 scores low semantically; Step 2 file-layer loading is the double insurance — always run Step 2 first in a new session.

IV. Durability reminders (already-trodden pits)

  • ⚠️ <your-workspace-root>/_localmem_models embedding cache must be kept and backed up — verification showed HuggingFace re-pull returns 401 (cas-server unreachable). Already-written vectors remain searchable; but adding new seeds in the future depends on this local cache — delete it and new memories cannot be written (old ones still searchable).
  • ⚠️ localmem is secondary recall; the file layer is always the protagonist. Do not skip writing _ACTIVE_PROJECTS.md / MEMORY.md just because localmem exists.

V. When to add seeds (write path)

When a new finalized hard fact appears (user decided it; it will not change):

  1. First write the file layer: account MEMORY.md top "official-account template" section / project MEMORY.md.
  2. Then write one semantic seed via localmem store_memory (tags incl. SynomosAI / publish / continuity).
  3. Verify recall_memory hits it before considering it done.

VI. DoD (definition of done)

  • Steps 1~4 all run, none skipped.
  • Before continuity-sensitive tasks, already hold finalized items (account name / VI / QR / blocks / keys).
  • Did not re-ask the user for already-settled items.
  • If new finalized facts were found, persisted to file layer + localmem.

中文

何时用

  • 新会话开始、用户还没说具体任务前(默认主动跑)
  • 用户质疑「你失忆了 / 怎么又忘了 / 昨天不是已经…」
  • 要做公众号发稿、品牌资产、发布阻塞、密钥投递类任务前
  • 跨工作区接续上一个会话的半成品(如推送草稿箱仍卡在哪)
  • 触发词:continuity、memory、localmem、cross-session、开局四步、失忆。

不用于:不适用(详见正文/描述)。

用法

调用方式与参数详见正文「## 一、开局四步(每次新会话必跑,顺序不可省)」节。

流程

Step 1 · 读全局总索引 Step 2 · 读账号级真源 MEMORY Step 3 · localmem 语义召回(兜底) Step 4 · 扫近 14 天项目级 MEMORY

作者:潘布达(内容发布运营团主理人)|定稿:2026-09-04|背景:用户多次指出「失忆」——根因不是方案缺失,而是开局没按协议回灌已知事实。

〇、为什么需要这个协议

GitHub 上 agent 记忆的基准结论(memory-systems 技能 + LoCoMo 基准):文件级记忆读取比专用记忆工具更可靠——基础文件操作就能拿 74%,高于 Mem0 专用工具 68.5%。所以本机已搭的「本地优先最小栈」是对的,不用换方案、不用上云:

  • ✅ localmem-mcp(已装 v0.1.1):SQLite+FTS5+本地 fastembed,余弦+关键词混合检索,零 LLM/零 API
  • ✅ 配置 LOCALMEM_DB_PATH=<你的工作区根>/_localmem_memories.db,跨工作区/跨账号共享同一 db
  • ✅ 全局总索引 <你的工作区根>/_ACTIVE_PROJECTS.md
  • ✅ 账号级真源 <memory-root>/MEMORY.md

唯一缺口:开局没按协议回灌。失忆 = 潘布达(连续性 Owner)没执行协议。本技能就是把这个协议变成可调用、可复用的动作。

一、开局四步(每次新会话必跑,顺序不可省)

动手做任何实质性任务之前先跑完这四步。耗时 < 1 分钟,省下反复问用户的成本。

Step 1 · 读全局总索引

Read <你的工作区根>/_ACTIVE_PROJECTS.md   # Windows 例:~/.skills/<skill-dir><你的工作区文件夹>/_ACTIVE_PROJECTS.md

拿到:当前活跃项目清单、RACI、各项目阻塞状态、最近交接点。这是「现在手头有哪些事」的总览。

Step 2 · 读账号级真源 MEMORY

Read <memory-root>/MEMORY.md

拿到:已固化、永不再问用户 的终态硬事实。关键段:

  • 🔴「公众号文章 · 取模版与 VI 总入口」——优先来这取模版 + SynomosAI 红 VI 色系 + 三码路径
  • 公众号真实号名 = SynomosAI(CTA 写「关注【SynomosAI】」,禁旧平台紫色)
  • 推送草稿箱 4 大阻塞
  • 发布闸门铁律(平台判可疑 → 不申诉)
  • 密钥投递铁律(DPAPI / key_drop,禁明文)
  • 署名/版权体系

Step 3 · localmem 语义召回(兜底)

用 localmem MCP 工具:recall_memory(已灌 15 条跨工作区种子)或 search_memory。

  • 模型缓存:<你的工作区根>/_localmem_models(必须保留/备份,断网也可搜;模型下载源已 401 不可再拉)
  • 召回取 limit=5~8,文件层已加载的硬事实即使语义分低也能命中
  • 典型问题验证过可命中:品牌色、VI、号名、推送阻塞、项目索引、微信预览坑、发布闸门、SOP

Step 4 · 扫近 14 天项目级 MEMORY

Glob <你的工作区根>/*/memory/MEMORY.md  → 读最近修改的

拿到:各工作区自己沉淀的项目铁律(如本次 2026-09-03 工作区的「三码 base64 内联」「CTA 去旧平台名」「VI 铁律」)。

二、真源层级(避免冲突时听谁的)

  1. 第一真源 = 文件层:_ACTIVE_PROJECTS.md + 账号 MEMORY.md + 项目 MEMORY.md。冲突以文件层为准。
  2. 第二层 = localmem 语义层:仅作兜底召回,不写新事实(写事实走 Step 2 文件层)。
  3. localmem 只负责"我想不起来时兜底",不替代文件层。

三、已灌种子速查(localmem 库 15 条核心)

id 内容 命中查询示例
4 SynomosAI 品牌名 + 红 VI 色系 + 模版路径 「公众号品牌色用什么」
6 推送草稿箱 4 大阻塞 「推草稿箱卡在哪」
9 发布闸门铁律(平台判可疑不申诉) 「发布前平台判可疑怎么办」
10 密钥投递铁律(DPAPI/key_drop) 「密钥怎么投安全」(需 limit≈8)
13 进行中 6 项目指针 「现在哪些项目在做」
14 微信 X5 预览坑 + LAN 通道 「微信里图不显示」
15 内容发布运营团 SOP 「发布流程怎么走」

注:id10 语义分偏低,靠 Step 2 文件层加载双保险;新会话仍先跑 Step 2。

四、Durability 提醒(已踩过的坑)

  • ⚠️ <你的工作区根>/_localmem_models 嵌入模型缓存必须保留并备份——验证时从 HuggingFace 重拉返回 401(cas-server 不可达)。已写入向量永久可搜;但未来想再加新种子必须靠这个本地缓存,删了就写不进新记忆(旧记忆照常能搜)。
  • ⚠️ localmem 是二级召回,主角永远是文件层。别因为有了 localmem 就偷懒不写 _ACTIVE_PROJECTS.md / MEMORY.md。

五、何时补充种子(write 路径)

发现新终态硬事实(用户拍板、不再变)时:

  1. 先写文件层:账号 MEMORY.md 顶部「公众号取模版」段 / 项目 MEMORY.md
  2. 再用 localmem store_memory 写一条语义种子(tags 含 SynomosAI / publish / continuity 等)
  3. 验证 recall_memory 能命中后再算完成

六、DoD(完成标准)

  • Step 1~4 全跑完,未跳过
  • 连续性敏感任务执行前已掌握「号名/VI/QR/阻塞/密钥」等已固化项
  • 未向用户重复询问已定稿事项
  • 若发现新终态事实,已落文件层 + localmem

证据与安全声明

  • 证据:TBD(暂无评测/徽章链接;产生后在此更新实际链接)
  • 版本:1.0.1
  • 安全:未做独立安全扫描(TBD),结论待补;补全前不作推荐背书。