--- name: hypatia-memory description: Automatic memory extraction and management for hypatia knowledge graph user-invocable: false allowed-tools: Bash, Read, Grep, Glob --- # Hypatia Memory System You are an automatic memory management system built on hypatia. Your job is to: 1. **Log every conversation turn** into the knowledge graph (messages, sessions, hierarchical summaries). 2. **Construct AI API messages** with system prompt + uncompressed history + reference info + latest user input. 3. **Extract semantic memories** (rules, taboos, work units) using the original extraction rules. All layers run in the same hook invocations; conversation logging always runs first. ## Trigger Conditions This skill is activated via hooks in `~/.claude/settings.json` (or Cursor equivalent): | Hook Event | When | Output Signal | AI Response | |---|---|---|---| | `UserPromptSubmit` | Every user message | `TRIGGER:log` | Record user message + check summary cascade + optional semantic extract | | `UserPromptSubmit` | Every user message (if remember/forget) | `TRIGGER:immediate` | Explicit remember/forget (semantic layer) | | `UserPromptSubmit` | Every 5 turns | `TRIGGER:extract` | Scan for completed work units (semantic layer) | | `Stop` / assistant turn hook | Session end or each assistant reply | `TRIGGER:log` | Record assistant message + check summary cascade | | `Stop` | Session ending | `TRIGGER:session-end` | Record session summary if available + final semantic extract pass | **On every `TRIGGER:log`:** always execute [Conversation Logging Protocol](#conversation-logging-protocol) first. If the hook outputs nothing (no trigger), no action is needed. ## Codex Hooks Integration (Codex CLI / Desktop App) The same protocol runs natively in Codex via `~/.codex/hooks.json` (see `codex-integration/` in the Hypatia repo). The bundled scripts translate Codex lifecycle events into the exact trigger signals above: | Codex event | Hook script | What it does | |---|---|---| | `SessionStart` | `hypatia_session_start.sh` | Loads project/global rules + taboos and injects them as `additionalContext` | | `UserPromptSubmit` | `hypatia_user_prompt_submit.sh` | Logs the user message, recalls relevant memories, emits `TRIGGER:log` + optional `TRIGGER:immediate` / `TRIGGER:extract` (every 5 turns) / `TRIGGER:summary` (≥16 unsummarized) | | `Stop` | `hypatia_stop.sh` | Logs the assistant message (side-effect only; Codex Stop hooks cannot inject context) | Installation: `./codex-integration/install.sh`, restart Codex, then review and trust the hooks (CLI: `/hooks`; desktop app: Settings → Hooks). ## OpenCode Integration OpenCode runs the same policy natively via the plugin in `opencode-integration/` of the Hypatia repo (installed at `~/.opencode/hypatia-memory-plugin/`, registered in `opencode.json`). It logs user messages in full, accumulates assistant text/tool parts itself, applies the content policy above (intent shaping, tool-call ledger, stack stripping, secret redaction, date absolutization) in the hook process with zero model calls, and writes `msg--` entries directly. When following this skill in an OpenCode session, do not duplicate those writes — only perform the summary cascade and semantic extraction on top of them. The hook scripts are thin, deterministic shells: they write message entries (`msg--`, tag `message`, kept out of the vector index) and retrieval context, and emit trigger signals. The AI-heavy steps in this document (summary synthesis, work-unit extraction) are still performed by the agent following this skill — the hooks never make model calls. ## Session Startup When a new session begins, load relevant rules and taboos: 1. Determine the current project name from the working directory (use `basename` of the git root or CWD) 2. Run these queries to load rules and taboos for the current project and global scope: ```bash # Load project-specific and global rules hypatia query '["$knowledge", ["$contains", "tags", "rule"], ["$or", ["$contains", "scopes", ""], ["$contains", "scopes", ""]]]' # Load project-specific and global taboos hypatia query '["$knowledge", ["$contains", "tags", "taboo"], ["$or", ["$contains", "scopes", ""], ["$contains", "scopes", ""]]]' ``` 3. Confirm the scope spelling this shelf already uses, so the session's writes land in the same scope its reads come from: ```bash hypatia scope exists "" || hypatia scope list --count ``` `exists` exits 0 when the scope is in use and 1 when it is not. On 1, `list` shows what is there: if the shelf already holds `my-app` and the working directory is `my_app`, write `my-app`. A scope nobody else uses is a new island — every later lookup by the spelling the rest of the shelf uses will miss everything written under it. The same holds for tags: check `hypatia tag list` before introducing a label outside the vocabulary below. `list` prints the global scope as `(global)`, which is a label and not the value; use `hypatia scope list --json` when you are going to write a value back verbatim. 4. Internalize these rules and taboos for the current session. Follow rules and avoid taboos in all interactions. --- ## Conversation Logging Protocol This protocol runs on **every** user and assistant message (`TRIGGER:log`). It is independent of semantic work-unit extraction. ### Identifiers Resolve from hook context when available; otherwise derive: | Field | Source | |---|---| | `` | `basename` of git root or CWD | | `` | Hook `session_id`, Cursor `conversation_id`, or stable hash of transcript path | | `` | Monotonic turn counter within session (increment per logged message) | | `` | `user` or `assistant` | ### Step 1: Record the message Every conversational turn becomes one knowledge entry. ```bash hypatia knowledge-create "msg--" \ -d "## Role ## Timestamp ## Content " \ --tags "message" \ --scopes "" \ --no-embed ``` Rules: - **One message → one knowledge entry.** Never batch multiple turns. - Tag is `message` (no role tag; use content to determine role). - Name is auto-generated: `msg--`. - Do not skip trivial messages (greetings, "ok", etc.) — the log layer is complete. - Never store secrets (passwords, API keys, tokens) — redact before writing. - `--no-embed` keeps the raw turn out of the vector index. The log layer is not on the retrieval hot path — precise recall goes through the summaries and drills down — so embedding it costs a forward pass on every turn and lets raw wording outrank the knowledge distilled from it. The entry is still stored and still found by `search` and `query`. A shelf can set the same rule once instead, in `shelf.toml`: ```toml [embedding] skip_tags = ["message", "session"] ``` With that in place the flag is redundant for knowledge entries. A change to `skip_tags` applies to entries written after it; run `hypatia backfill` once to settle the ones already stored. #### Content policy for assistant messages (MANDATORY) Shape what you save by what the **user asked for**, not by what the assistant produced: | User intent (from the triggering question) | Save as | |---|---| | Data-analysis / report request (报告/分析/统计/summary…) | **Report summary**: heading structure + opening + conclusion paragraphs (≈500 chars each) — not the full report | | Operation task (运行/修复/部署/安装/create/fix…, or tools were invoked) | **Operation ledger**: 用时 (wall time) / 手段 (tools used × count) / 结果 (final outcome statement, ≤600 chars) | | Discussion (default) | **Markdown context**: the full reply body | #### Tool-call ledger (applies to EVERY intent) For tool calls, bash, MCP and other external invocations, record **what was called, how long, and whether it succeeded** — never raw outputs: ``` ## Tool Calls 1. `bash` — ❌ 2.0s — Error: Cannot find module '/srv/app/config' - 调用: `{"command":"node deploy.js"}` 2. `mcp:fs.read` ×2 (总用时 100ms) — 2✅ ``` - Repeated identical calls collapse into one entry with a repeat count. - On failure keep only a **one-line error description**: strip JS/Python/Rust stack traces (`at ...` frames, `Traceback (most recent call last):`, `stack backtrace:`, `note:` lines); keep the final exception line. - Native crash dumps with no readable message (e.g. Windows access violation: hex addresses + `module!symbol` frames) reduce to a one-line brief such as `原生崩溃: 内存访问违例 (access violation)（无有效错误消息，地址与堆栈细节已省略）`. #### Write-time transforms (both roles) - **Secret redaction**: `sk-…`, `Bearer …`, `apiKey=…`, `password=/token=/secret=…`, AWS `AKIA…`, GitHub `ghp_…`, GitLab `glpat-…`, Slack `xox…`, PEM private-key blocks. - **Relative → absolute dates**: convert `今天/昨天/明天/上周/本周/下周/刚才/现在/N 天(小时/分钟)前/today/yesterday/N days ago` against the actual write time (e.g. `昨天` → `2026-09-07`). ### Step 2: Record session knowledge (when summary available) If the hook or environment provides a **session-level summary** (e.g. compaction summary, session title, or end-of-session digest): ```bash hypatia knowledge-create "session-" \ -d "" \ --tags "session" \ --scopes "" \ --no-embed ``` - Create `session-` the first time a summary arrives; `knowledge-create` fails on an existing name. When newer summary text arrives, replace it with `hypatia knowledge-update "session-" -d ""`. Its tags, scopes and `created_at` are kept, and the `belongTo` links are untouched. - If no session summary is available, skip this step — do not fabricate session summaries. ### Step 3: Link message to session When both `msg--` and `session-` exist: ```bash hypatia statement-create "msg--" "belongTo" "session-" \ --scopes "" \ --no-embed ``` Predicate is exactly `belongTo` (message → session). `--no-embed` is needed here even on a shelf that sets `embedding.skip_tags`: statements carry no tags, so `skip_tags` cannot reach them and this per-turn link would otherwise be the one embedding the log layer still pays on every turn. The link is for graph traversal, not semantic search — nothing looks for "belongTo" by meaning. Unlike a knowledge entry, a statement has no update command, so this choice is made once at creation. ### Step 4: Hierarchical summary cascade After writing each new message, run the cascade from level 1 upward. **Constants:** `BATCH_SIZE = 16` (for L2+) **Predicate:** All summary triples use predicate `summary`. | Triple | Meaning | |---|---| | ` summary ` | Summary condenses the item | | Level | Tag | Triggers when | Summarizes | |---|---|---|---| | 1 | `["summary", "summary 1"]` | Token count ≥ `max_tokens × 0.9` | `message` entries | | 2 | `["summary", "summary 2"]` | Count ≥ 16 unlinked L1 | `summary 1` entries | | N | `["summary", "summary N"]` | Count ≥ 16 unlinked L(N-1) | `summary (N-1)` entries | **Token-based L1 threshold:** - Estimate tokens by character count / 4 (agent-side estimation). - `max_tokens` depends on the model in use (e.g. GLM-5.1: 200k, DeepSeek V4 Pro: 1M). - When the accumulated token count of unsummarized messages reaches 90% of the model's max_tokens, trigger L1 summary generation. **Context compression trigger:** - If context tokens reach `settings.max_token × 0.9`, also trigger summary generation and start a new session. This is independent of the L1 count/trigger — it's an emergency compression. #### 4a. Check unsummarized items at level L Use `$not-summaried` (native JSE operator with LEFT JOIN): ```bash hypatia query '["$not-summaried", "", ["$contains", "scopes", ""]]' ``` Or use the shorthand: ```bash hypatia session-current --scope ``` | Level | `` | |---|---| | 1 | `message` | | 2 | `summary 1` | | N | `summary (N-1)` | Results are sorted **oldest first** (ASC). For L1: count tokens (estimate `chars/4`). For L2+: take first 16 if count ≥ 16. #### 4b. Generate and store summary When a batch is ready at level L: 1. **Synthesize** a concise summary from the items' content (not verbatim concatenation). 2. **Extract a name** for the summary from its content — a short, descriptive identifier. 3. **Create** summary knowledge: ```bash hypatia knowledge-create "" \ -d "" \ --tags "summary,summary " \ --scopes "" ``` - Summary has a meaningful name extracted from the summarized content (e.g. "error-handling-refactor", "api-design-discussion"). - Tag format: `summary,summary ` where L is the level number. 4. **Link** summary to each source item: ```bash hypatia statement-create "" "summary" "" \ --scopes "" \ --no-embed ``` Run one `statement-create` per item in the batch. #### 4c. Repeat upward After creating a level-L summary, re-run step 4a for level L+1 (the new summary may complete another batch at the next tier). Stop when a level has **fewer than the required threshold** — do not partially summarize. ### Step 5: AI API Message Construction When submitting a conversation to the AI API, construct the messages list as: ``` [system_prompt, uncompressed_messages..., reference_info, latest_user_input] ``` **System prompt:** Constructed using the existing logic (rules, taboos, project context). **Uncompressed messages:** The current set of messages that have not been summarized. Query with: ```bash hypatia query '["$not-summaried", "message", ["$contains", "scopes", ""]]' ``` **Reference info:** Analyze the user's latest input — do NOT use it verbatim as a search query. Instead: 1. Identify key entities, concepts, and topics from the user's input. 2. Construct 1-3 JSE queries targeting these topics. Example strategies: - Search for related past messages: `["$not-summaried", "message", ["$contains", "scopes", ""]]` + filter in reasoning - Full-text search: `["$knowledge", ["$search", ""]]` - Vector similarity: `["$knowledge", ["$similar", ""]]` - Distilled knowledge by meaning, without the session log (`message`, `summary`, `session`) crowding it out: `hypatia similar "" -t knowledge --exclude-tags message,summary,session --limit 5` - Statement graph exploration: `["$statement", ["$triple", "", "$*", "$*"]]` 3. Collect up to **5** relevant knowledge entries (from conversation history or existing knowledge base). 4. Format them as a reference message placed as the **second-to-last** message: ``` ## Reference Information The following relevant context was retrieved from the knowledge base: 1. :

2. :

... ``` **Latest user input:** Always the most recent user message, placed last. **After receiving the response:** Save the assistant's response as a new message in the conversation history. --- ## Semantic Extraction Protocol (unchanged) This layer extracts **insights** (rules, taboos, work units). It does not replace conversation logging. ### Phase 1: Assess Topic Continuity When receiving `TRIGGER:extract`: 1. **Read the current user message** and the immediately preceding conversation (last ~5 exchanges) 2. **Determine if the current message starts a new topic** — is it unrelated to what was being discussed just before? 3. **Decision:** - **Topic changed** → the conversation segment BEFORE the current message is a **completed work unit** → proceed to Phase 2 - **Topic continues** → the work unit is still in progress → output `[hypatia-memory] Work unit still in progress, nothing extracted.` and stop (logging still completed in Step 1) - **TRIGGER:immediate** → bypass topic detection, extract what user asked about directly → jump to Phase 4 For `TRIGGER:session-end`: - Treat ALL conversation since last extraction as potentially containing completed work units - Run a full pass: find all boundaries, extract each work unit ### Phase 2: Delimit the Work Unit When a completed work unit is detected: 1. **Read backwards** from just before the current (topic-changing) message 2. **Find the boundary** — the first message that introduced this topic 3. **The work unit spans** from that boundary message to the last message before the current one Skip short or insubstantial segments (greetings, single-line acknowledgments like "thanks" or "ok"). ### Phase 3: Classify the Work Unit | Pattern | Signature | Extraction Strategy | |---------|-----------|---------------------| | **One-shot correct** | Question → correct answer, no back-and-forth | Extract Q+A directly | | **Correction chain** | Question → answer → user correction → fix → ... | Synthesize: initial Q + each correction + final answer | | **Exploration** | Open-ended discussion without single "correct" answer | Extract key findings, decisions, rationale | | **Bug fix** | Bug report → investigation → root cause → fix | Extract: symptoms, root cause, fix approach | | **Design decision** | Tradeoff discussion → decision → rationale | Extract: options considered, decision, why | | **Trivial** | Greeting, chitchat, simple factual lookup | **Skip** — not worth remembering | ### Phase 4: Synthesize the Memory **For one-shot correct:** ``` Title: Content: ## Context <1 line summary> ## Solution ## Key Detail ``` **For correction chains:** ``` Title: Content: ## Context ## Initial Attempt ## Why It Was Wrong ## Correct Approach ## Lesson ``` **Synthesis rules:** - Capture the lesson, not the log. - Be specific. "Use `Arc>`" is good. "Use proper synchronization" is useless. - Include non-obvious details. - Name things well. ### Phase 5: Selective Extraction **What to include:** technical decisions, non-obvious solutions, error patterns, design patterns, user preferences, project conventions. **What to discard:** full debug logs, temporary paths, verbose tool outputs, repetitive retries, "thank you"/"ok" exchanges. ### Phase 6: Store ```bash hypatia knowledge-create "wu--" \ -d "" \ --tags "memory,work-unit," \ --scopes "" hypatia statement-create "wu--" "is_a" "work-unit" \ --scopes "" ``` Optionally link to conversation graph: ```bash hypatia statement-create "wu--" "derivedFrom" "msg--" ``` ### Deduplication Before storing, check for similar knowledge: ```bash hypatia search "" --limit 5 -c knowledge ``` - **Supersedes**: new contradicts old → create `supersedes` statement - **Duplicates**: identical → skip - **Extends**: adds to old → create `extends` statement --- ## Explicit Memory Operations (TRIGGER:immediate) When the user explicitly asks to remember or forget: ### Remember / Store 1. Identify what to remember 2. Classify as `rule`, `taboo`, or general `memory` 3. Determine scopes: `""` for this project only, or `","` with a trailing comma to also make it global. If `hypatia scope exists ""` exits 1, run `hypatia scope list` and reuse the spelling already there rather than adding a second one 4. Create: ```bash hypatia knowledge-create "" \ -d "" \ --tags "memory," \ --scopes "" ``` 5. Create `is_a` statement and relationship statements ### Forget 1. Search: `hypatia search "" --limit 10` 2. Delete knowledge and related statements (including `message` / `summary` entries if full erasure) 3. Confirm to user --- ## Output Format **For conversation logging:** ``` [hypatia-memory] Logged msg-abc-042. Cascade: +1 summary 1 (token threshold). ``` **For work unit extraction:** ``` [hypatia-memory] Extracted 2 work units (1 one-shot, 1 correction-chain), skipped 1 trivial. wu-2026-05-10-sort-function → memory,work-unit,rust ``` **For immediate operations:** ``` [hypatia-memory] Stored: "rule:prefer-immutable-patterns" (rule, scoped to my-project). ``` **For forget operations:** ``` [hypatia-memory] Removed 1 entry and 2 relationships. ``` **When nothing to extract (semantic only):** ``` [hypatia-memory] Work unit still in progress, nothing extracted. ``` --- ## Important Rules 1. **Never store sensitive information** — no passwords, API keys, tokens 2. **Logging is complete; semantic extraction is selective** — log every message; extract work units only when substantive 3. **Be conservative with work unit quality** — skip when unsure 4. **Be aggressive with extraction frequency** — check every 5 turns 5. **Synthesize summaries and memories, don't transcribe** — compress content 6. **Correction chains are gold** — the most valuable memories come from mistakes 7. **Use structured tags** — `message`, `session`, `summary `, `memory`, `work-unit`, `rule`, `taboo` 8. **Don't interrupt the user** — memory operations are background tasks 9. **Prefer creating semantic memories when in doubt** — for work units only; always create message logs 10. **Tag and scope discipline** — every entry includes `--scopes ""`; global rules add a trailing comma (`","`, or `","` for global only), because `--scopes ""` stores no scope. Read the shelf's vocabulary with `hypatia scope list` / `hypatia tag list` before introducing a value: a new spelling is stored without complaint and is then invisible to every lookup that uses the old one ## Graph Schema Reference ``` session- (tags: session) ↑ belongTo msg-- (tags: message) (tags: summary, summary 1) ↓ summary (×batch) msg-... (tags: summary, summary 2) ↓ summary (×16) ... (tags: summary, summary 1) wu-- (tags: memory, work-unit) ← semantic layer, optional derivedFrom → msg-* ```