Use ChatMem for repository recall, continuation, handoff, migration, startup rules, wiki/context, local history search, and durable memory. 当用户问“记得吗、之前讨论过、回忆、继续做、迁移、交接、项目历史、本地历史、启动规则、记忆”等问题时使用；先查 ChatMem MCP，不要让用户重新描述已有对话。
Instrucciones de origen · Vista previa de solo lectura
name
chatmem
description
Use ChatMem for repository recall, continuation, handoff, migration, startup rules, wiki/context, local history search, and durable memory. 当用户问“记得吗、之前讨论过、回忆、继续做、迁移、交接、项目历史、本地历史、启动规则、记忆”等问题时使用；先查 ChatMem MCP，不要让用户重新描述已有对话。
ChatMem
Core Principle
ChatMem is an MCP-first local-history, startup-rule, and continuation layer. Indexed local history is the evidence layer; approved startup rules are compact durable guidance for new agent sessions; generated wiki pages are readable projections rebuilt from approved rules and episodes. This skill is only the operating guide: use it to decide when and how to call the ChatMem MCP server.
Do not ask the user to paste full historical transcripts when ChatMem can provide repo memory, checkpoints, handoffs, or targeted history.
Do not assume ChatMem appears as an @chatmem mention in the chat UI. For agents, ChatMem should normally be reached through MCP tools; the desktop app is the human-facing conversation and memory control surface.
When to Use
Use this skill when the user:
asks to continue, resume, migrate, or hand off work between Claude, Codex, Gemini, or another local agent
pastes a ChatMem continuation prompt from the desktop app
asks what was done earlier in the current repository
needs project rules, prior decisions, commands, gotchas, or recent work context
wants to create durable memory from the current conversation
Do not use it for general web search, unrelated memory, or one-off notes that will not help future work in the same repo.
MCP-First Workflow
Identify the repo root from the current workspace, user prompt, or ChatMem continuation prompt.
If the user did not explicitly ask for recall or continuation, ask once in the user's language before loading project memory: 要我先用 ChatMem 低成本回忆一下这个项目吗？我会只加载启动规则、最近交接和少量相关历史，不展开完整对话。
If the user asks a recall/continuation question, pastes a ChatMem continuation prompt, or answers yes to the recall question, proceed without asking again.
For recall questions, call recall_project_work first with limit=3. This is the default high-level recall tool: it returns status, compact answer, de-duplicated evidence, diagnostics, and next actions, and it does not run foreground import or scan.
Use get_project_context when startup rules, handoff metadata, pending candidates, and compact history are all needed together. Use intent="startup" for compact startup rules, intent="recall" when the user asks whether something was discussed before, and intent="continue_work" when resuming.
Start with limit=3 unless the user asks for a broad review. Read approved rules, recent handoff metadata, diagnostics, and the top relevant history summaries first; do not load or paste raw transcripts.
Treat approved startup rules as durable project guidance. Treat history evidence as local evidence that may be stale or unapproved. Never treat absence from approved rules as evidence that a past discussion did not happen.
If recall_project_work, get_project_context, or get_repo_memory_health reports unmatched project roots that clearly belong to the same repo, use merge_repo_alias, then run scan_repo_conversations as maintenance and retry recall.
If recall_project_work is unavailable, fall back to get_project_context and then call search_repo_history for specific gaps: prior decisions, commands, key files, errors, earlier attempts, or recall questions. When a hit includes conversation_id, use read_history_conversation only after the user asks you to read/expand that found conversation.
Use the smallest useful context. Prefer approved startup rules, generated wiki pages, checkpoints, handoffs, targeted history evidence, and pending candidate summaries over replaying raw conversation logs.
Use list_repo_wiki_pages or rebuild_repo_wiki when the user asks for a readable project wiki, commands, gotchas, or recent-work pages. Treat those pages as generated projections, not editable source material.
Use list_entity_graph when a task depends on related systems, symbols, protocols, agents, or release concepts.
Use list_memory_conflicts before writing or updating a surprising startup rule, especially when it negates an existing command or convention.
When a stable rule should be injected at future startup, call create_memory_candidate with concise text and evidence.
When a pending candidate should update an existing approved startup rule, use propose_memory_merge or the relevant MCP write path to prepare an agent-authored rewrite. Do not silently overwrite approved rules; ask the user first when the evidence or conflict is uncertain.
Before another agent continues the task, call build_handoff_packet instead of asking the user to copy the full conversation.
Low-Token Project Recall
Use this ladder whenever the user agrees to project recall, asks "do you remember...", or needs to continue prior work:
First call recall_project_work with the exact topic and limit=3.
If status is found, summarize the returned answer, source agent/conversation, and evidence label. Say that this is indexed local history, not an approved startup rule. Ask whether the user wants you to read the most relevant conversation with read_history_conversation before increasing the limit or requesting broader history.
If status is partial, try one narrower query with exact file names, feature names, or conversation titles. If the miss appears caused by repo-root drift, use merge_repo_alias or retry with the likely related repo root.
If status is miss and diagnostics show no indexed documents/chunks, say the indexed coverage is missing and run import_all_local_history or scan_repo_conversations only as a background maintenance step before concluding history is absent.
Fall back to get_project_context(intent="recall", limit=3) only when you also need approved startup rules, recent handoff, or pending candidate context.
Increase to limit=10 or more only after the user asks for a broader review or after the first compact pass proves the topic is relevant.
Never say "we did not discuss this" only because approved startup rules are empty. Say whether approved rules, indexed history, wiki projections, diagnostics, and repo-root coverage were checked.
Conversation Evidence Follow-Up
If recall_project_work.evidence, get_project_context.relevant_history, or search_repo_history.matches returns any plausible match:
Do not ask the user to redescribe the topic as the next step.
Do not say the current session has no context just because the match is not an approved startup rule. Say: "启动规则没有命中，但本地历史里找到了相关对话证据。"
Name where it was found: source agent (source_agent or the prefix in conversation_id), conversation title, updated date, and evidence excerpt when available.
Ask a concrete follow-up in the user's language, for example: 我在 Codex 和 Claude 的本地历史里找到了关于 Pmodel 的对话证据。要我读取最相关的那段对话，还是先列出命中的对话让你选？
If the user says yes, call read_history_conversation with the returned conversation_id, the evidence message_id when present, the original query, and a compact limit such as 8-12.
If read_history_conversation is not available in the current MCP tool list, say the installed ChatMem MCP is older and continue with the existing search evidence: offer to list the matched conversations, run search_repo_history with a slightly larger limit, or ask the user to open the conversation in ChatMem. Do not ask the user to redescribe the topic.
Only ask the user to explain the topic again after approved rules, indexed history, aliases, and fresh import/scan all miss.
Continuation Prompts
The ChatMem desktop app may copy a short prompt like:
Use ChatMem to load memory for this project:
repo: D:\VSP
conversation: 019dab66-4427-7d93-a7dc-6cb90a1a4a74
Prefer ChatMem MCP over pasted history.
When you see this, do not treat it as context by itself. Treat it as an instruction to call ChatMem MCP for the repo and optional conversation id.
Memory Candidate Rules
Language rule:
Prefer Chinese for memory titles, values, usage hints, merge proposals, checkpoints, and handoff summaries when the user works in Chinese.
Preserve exact English identifiers such as file paths, commands, function names, env vars, config keys, model names, and API/tool names.
A good durable memory usually reads as Chinese prose with embedded technical tokens, for example: 跨 agent 记忆依赖 repo_root 归一化；继续使用 canonical_repo_root 匹配 .git 根目录。
If the source evidence is entirely English and the user's language is unknown, keep the original wording instead of guessing.
Good candidates are durable, repo-scoped, and useful as startup rules:
commands that must be run before packaging or release
repo conventions, architectural decisions, or gotchas
known compatibility rules
stable user preferences for this repo
repeatable handoff or verification requirements
sync/release caveats that affect future local work
Bad candidates:
secrets, tokens, credentials, or private account details
full conversation summaries
temporary TODO lists
speculative ideas without evidence
edits directly to generated wiki output instead of creating or approving memory
personal chatter or one-off debugging noise
WebDAV Sync Rule
The desktop settings screen owns WebDAV credentials and cloud upload. MCP tools do not silently write to the user's cloud storage. When a user expects files to appear in their netdisk, the app must run the explicit WebDAV sync action, which creates the remote chatmem folder and uploads JSON conversation snapshots plus a manifest.
Retrieval Rule
Search history is indexed as FTS plus vectors. Local chatmem-local-hash-v1 vectors are always kept as a fallback. When CHATMEM_EMBEDDING_PROVIDER=openai-compatible and the matching base URL/model/dimensions/API key environment variables are present, search can use real provider embeddings stored side-by-side with the local fallback. Call rebuild_repo_embeddings after changing embedding provider settings. Treat vector hits as retrieval candidates, not final truth: prefer approved startup rules and evidence refs for durable facts, and verify stale or surprising matches before acting.
For recall questions, never answer from get_repo_memory alone. If approved startup rules do not contain the answer, search history and clearly label matches as history evidence rather than approved rules. If history evidence exists, offer to read/expand the found conversation before asking the user to explain the topic. If exact repo search misses, broaden to the repo family: parent roots and child roots can contain the real conversation.
Local History And Alias Rule
import_all_local_history is the broad bootstrap tool. Use it sparingly: first install, major source-path changes, or suspicious recall misses.
scan_repo_conversations is the repo-scoped maintenance tool. It links conversations that match the repo and returns unmatched project roots for diagnosis.
merge_repo_alias is the repair tool for path drift: old cwd, file cwd, renamed folder, generated Codex project path, or related subproject that should belong to the current repo.
After merging an alias, run scan_repo_conversations again before answering recall questions.
Do not merge unrelated repositories just to get more search hits.
Extraction And Conflict Rule
ChatMem may auto-create pending startup-rule candidates only from explicit durable-memory markers such as "Remember:", "Rule:", "Gotcha:", "记住：", or "规则：". Bare imperative lines such as "Always ..." or "Do not ..." are not enough because they often come from agent task instructions. Auto-extracted candidates are suggestions only and are not required for local-history search. The desktop app is for inspecting or deleting them; promotion into startup rules belongs to the active agent through MCP or skill-driven workflow after checking evidence and conflicts.
Merge Proposal Rule
ChatMem does not need an internal LLM API to rewrite startup rules. The active agent can draft or apply a better rule update through MCP or skill workflow after reading the candidate, approved rule, conflicts, and evidence. The desktop inbox remains a view/delete surface, not an approval queue. If the rewrite is uncertain, ask the user before writing or submitting a confident proposal.
Handoff Rules
Use a checkpoint when the same agent or user wants to resume current work with minimal drift.
Use a handoff packet when another agent needs a concise transfer asset.
Choose a target profile that matches the next agent when available.
Include current goal, completed work, next steps, key files, useful commands, risks, and related memory ids; write prose fields in Chinese by default while preserving exact technical tokens.
Keep handoffs compact; they should replace raw transcript transfer, not become another transcript.
If MCP Is Unavailable
If ChatMem MCP tools are not available:
Say that ChatMem MCP is not currently callable in this environment.
Ask the user for the short ChatMem continuation prompt or plain memory export from the desktop app.
Use that export as a fallback only for this turn.
Do not invent memories, checkpoints, handoffs, or prior decisions.
Avoid telling the user to paste an entire historical conversation unless there is no other workable path.
User-Facing Behavior
When you use ChatMem, be brief:
"I will search local history first."
"I found a recent handoff; I will continue from that."
"The memory is stale, so I will verify before relying on it."
"I will create a memory candidate for this durable rule."
Do not expose internal memory mechanics unless the user asks. The user experience should feel like "continue this project", not "manage a memory database".
