Memory layer is now English-indexed: memories() query terms and remember() summaries must be English. Adds a runtime assertion that rejects CJK text in both paths, guiding the agent to translate non-English user requests before querying or writing memories. Ensures consistent retrieval regardless of conversation language.
293 lines
14 KiB
Markdown
293 lines
14 KiB
Markdown
---
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name: obelisk
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description: >
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Search and query past Claude Code session history.
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Reactive: when the user asks "how did I fix X", "what did we do last time", "find the session where", "上次怎么修的", "之前的session", "历史记录".
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Proactive: when the user references past work you lack context for, when you're about to modify a file with complex edit history, when the user says "继续之前的" or "continue where we left off", or when understanding prior decisions would improve your current response.
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Memory: when the user says "记住这个", "remember this", "写入记忆", "save this conclusion", or when you determine a retrieval result contains a conclusion worth persisting.
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allowed-tools:
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- Read
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- Bash(node:*)
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- Write
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---
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# obelisk
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Search and query Claude Code session history stored in `~/.claude/`.
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Obelisk indexes sessions, messages, tool calls, tool results, summaries,
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subagents, workflows, workflow agents, parent chains, and raw JSONL lines into
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SQLite + FTS5.
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Obelisk is a CodeAct memory layer: write a small JS query, run it locally, read
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the JSON, then answer. Do not turn history into a flat document or browse entire
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sessions by default.
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## Quick Start
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The skill directory is provided as `$SKILL_DIR` at invocation time.
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Fast keyword search:
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```bash
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node $SKILL_DIR/scripts/runtime.mjs --search "keyword"
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```
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Custom query:
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1. Write a bounded JS query to a temp file, for example `/tmp/q.mjs`.
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2. Run:
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```bash
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node $SKILL_DIR/scripts/runtime.mjs --query /tmp/q.mjs
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```
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3. Parse JSON stdout and answer with concise evidence.
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The query file runs inside `(async () => { ... })()`. Use `return` to emit JSON.
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Query scripts are read-only: `remember()` is not available, and `sql()` only
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accepts read-only SELECT/WITH queries.
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## Default First Pass
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Start with helpers, not raw SQL. For the first Obelisk query in a task, normally
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call `overview({ limit: 6 })` unless the user already gave an exact
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`session_id`, message `uuid`, or absolute file path.
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For semantic or synthesis tasks, combine orientation, memory recall, and raw
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session evidence before deciding whether a detail pass is needed:
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```js
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const map = overview({ limit: 6 });
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const project = map.current.project?.project;
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const topic = 'English topic terms translated from the user request';
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return {
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orientation: map.current_project,
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prior_memories: memories({ project, query: topic, limit: 5 }),
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session_evidence: search(topic.replace(/[-_]/g, ' '), { project, limit: 8 }),
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};
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```
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Use `sql()` only as an escalation path for exact joins, aggregations, or schema
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questions that helpers cannot express cleanly. Do not use raw SQL as a generic
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fallback for broad retrieval.
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## Query Routing
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Before writing a query, classify the task. Progressive disclosure is useful, but
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skipping the relevant reference usually costs extra query rounds.
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- Read `references/query-patterns.md` before the first query for broad synthesis, progress summaries, design history, weekly/monthly reviews, or questions that ask what the user did, learned, decided, tried, or abandoned. Start from the first-pass or one-shot synthesis pattern, then run a faceted detail pass if needed.
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- Read `references/retrieval-semantics.md` before multi-step retrieval, scoped project/file/session searches, or synthesis/conclusion/history questions. It defines the query design frame.
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- Read `references/schema.md` before raw `sql()` unless the needed table/column relationship is already explicit here. Do this before running the SQL, not after a missing-column error. Do not start with raw SQL for broad synthesis unless helpers cannot express the needed aggregation or join.
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- Read `references/pitfalls.md` after an error or when helper fields, FTS syntax, aliases, or row shapes are unclear.
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If a helper row shape is unclear, first run a tiny scoped query and return
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`Object.keys(row)` or a compact sample. Do not invent field names.
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## Core API
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### `search(text, opts?)`
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Full-text search across main messages, subagent messages, and workflow-agent
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messages.
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Returns:
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```js
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[{ message: { uuid, text, role, timestamp, model, cwd },
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session: { id, title, project, started_at },
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rank,
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context }]
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```
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`context` here means temporal neighbors: nearby messages in the same session by
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timestamp. It is not the parent chain. Use `context(uuid)` or `trace(uuid)` for
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causal/parent-chain context.
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Opts: `{ limit, sessionId, project, after, before, cwd }`.
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`project` is a SQL `LIKE` filter over `sessions.project`, not an exact project
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identity. Results are already ordered by FTS5 rank; lower rank sorts earlier.
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Prefer returned order over manually interpreting numeric rank unless you are
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deliberately using FTS5 semantics.
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### `context(uuid)`
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Returns the full story around one indexed message:
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```js
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{ message, parentChain, session, subagent, workflow }
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```
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Use this after `search()` finds a promising message. It is the usual way to
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expand vertically from one evidence point without dumping the whole session.
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### `sql(query, ...params)`
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Read-only SQL SELECT/WITH with `?` placeholders. Returns array rows. SQL is an
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escape hatch for exact structured joins and aggregations after the helper-first
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surface is insufficient; it is not the default retrieval entry point.
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Before writing non-trivial SQL, read `references/schema.md`. Common safe joins:
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- `tool_calls` does not have timestamps. Join `messages m ON m.uuid = tc.message_uuid`.
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- `tool_results` does not have timestamps. Join `messages m ON m.uuid = tr.message_uuid`.
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- For project/session filters, join `sessions s ON s.id = <table>.session_id`.
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- Prefer SQL-side `GROUP BY`, `COUNT`, `MAX`, `ORDER BY`, and `LIMIT` over hand-counting in the final answer.
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Tables: `sessions`, `messages`, `tool_calls`, `tool_results`, `summaries`,
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`memories`, `subagents`, `workflows`, `workflow_agents`, `messages_fts`.
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## Structured Helpers
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These helpers are convenience accessors over the same SQLite structure. They do
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not replace `sql()`, but they are the default first-pass surface. Use `sql()`
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when you need an exact aggregation or a join the helper does not expose.
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All list helpers accept a bounded `limit`. Many also accept:
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`{ project, after, before, sessionId, sessions, branch }`. Check the schema or a
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tiny sample before relying on less common filters.
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- `overview(opts?)` -- compact orientation map. Returns current cwd/project if knowable, global project counts, and current-project recent sessions plus memory records. It is a map, not evidence.
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- `sessions(opts?)` -- session rows, newest first. `project` is a SQL `LIKE` pattern.
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- `recent(n?)` -- shorthand for recent sessions.
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- `summaries(opts?)` -- summary rows, newest first: `{ id, session_id, timestamp, source, content, session_title, project }`.
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- `subagents(opts?)` -- subagent metadata plus `messageCount`.
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- `workflows(opts?)` -- workflow runs, newest first.
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- `workflowTree(runId)` -- workflow row plus parsed `result` and `agents`; may include bulky `script` and `result_json`, so project compact fields.
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- `fileHistory(filePath, opts?)` -- Read/Edit/Write tool calls for a file, oldest first; includes many `Read` rows.
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- `failures(opts?)` -- failed tool results with tool/session context, newest first.
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- `trace(uuid)` -- parent chain from root to message.
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- `thread(sessionId)` -- full session messages; last resort only.
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- `raw(uuid, opts?)` -- windowed access to the original JSONL line.
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- `memories(opts?)` -- recall memory layer, newest first. opts: `{ query, project, sessionId, sessions, after, before, branch, limit }`. `query` filters summary/path by English terms. Returns registered memory records (id, path, summary, project, session_id, created_at). Read the file at `path` for full content.
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## Retrieval Contract
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Keep queries scoped, bounded, and structural.
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- Scope First: classify the locator as scope, artifact, or semantic. Use the narrowest structural locator before FTS; empty scoped results are valid unless the user asks to broaden.
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- Orient First: for a new task, normally call `overview({ limit: 6 })` before deeper retrieval unless the user gave an exact session/message/file locator. It is a navigation map; confirm facts with `memories()`, `search()`, helpers, or, only when needed, `sql()`.
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- Helper First: prefer `overview()`, `memories()`, `search()`, `sessions()`, `summaries()`, `fileHistory()`, and other helpers for first-pass retrieval. Escalate to raw `sql()` only when helpers cannot express the needed join, grouping, or exact schema-level check.
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- Plan Before Probe: for conclusion, broad history, failure investigation, or file evolution, write a bounded retrieval script instead of spending turns on intermediate results.
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- Structure Before Text: compute counts, joins, grouping, dedupe, and projection in SQL or JS; keep runtime JSON compact, ideally under 10k-12k chars for synthesis tasks.
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- Evidence Before Conclusion: return compact evidence with stable IDs (`session_id`, `uuid`, `tool_call_id`, `run_id`, `agent_id`) and short snippets, then synthesize in the final answer.
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- Persist Durable Conclusions: after answering, if retrieval produced a durable conclusion that future sessions are likely to reuse and `memories()` does not already cover it, explicitly offer to write a memory. Keep the offer brief. Do not write the markdown file or run `--remember` until the user approves.
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If field, context, ordering, FTS, or helper semantics affect the query, read
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`references/retrieval-semantics.md` before coding. If a query errors, read
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`references/pitfalls.md` before retrying.
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## Memory Layer
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Obelisk has a persistent memory layer alongside raw session data. Every
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retrieval queries both layers: `memories()` for prior conclusions, `search()`
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and helpers for raw session evidence. Use memory as prior notes, not final
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authority. If a memory record influences your answer, say naturally that it was
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previously recorded, and compare it with raw session evidence when correctness
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depends on it. Raw session data is the evidence layer, but one hit is not a
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complete truth; query and cite it compactly.
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The memory layer is English-indexed. Use English terms in `memories({ query })`
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even when the user asks in another language. Write every `remember().summary`
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in English, regardless of the current conversation language. The runtime rejects
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obvious CJK text in memory queries and summaries as a guardrail.
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**Recall:** query `memories({ query: 'English topic terms', project: '...' })`
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to find prior conclusions relevant to the current task. Translate non-English
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user requests into concise English query terms before calling `memories()`. Like
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other list helpers, passing a string is treated as `sessionId`, and passing a
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number is treated as `limit`. Read the file at `path` for full content.
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Good memory candidates include design decisions, project conventions, abandoned
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alternatives, repeated failure causes, workflow patterns, and conclusions
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synthesized across multiple raw evidence points. Do not propose memory for
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one-off lookups, uncertain findings, or conclusions already covered by existing
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memories.
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**Writing memories:** after a retrieval produces a conclusion worth persisting,
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propose writing a memory file. The user must approve. Flow:
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1. Write a markdown file using the `Write` tool (user approves).
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2. Register it via `remember()` in a narrow memory-registration script:
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```js
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return remember({
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path: '.obelisk/memories/design-decision-x.md',
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session_id: 'current-session-id',
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message_start: 'uuid-of-first-relevant-msg',
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message_end: 'uuid-of-last-relevant-msg',
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summary: 'Detailed summary: what was decided, why, what alternatives were considered, and what constraints drove the choice.'
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})
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```
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Run the registration script with:
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```bash
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node $SKILL_DIR/scripts/runtime.mjs --remember /tmp/register-memory.mjs
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```
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`--remember` exposes only `remember()`. It does not expose `search()`, `sql()`,
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`memories()`, or other retrieval helpers. If you need source IDs, find them
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first with a normal `--query` script.
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`remember()` validates that `path` already exists and points to a file. Relative
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paths are resolved against the source session's `project_path` when
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`session_id` is provided, then stored as normalized absolute paths. Prefer
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project-relative paths such as `.obelisk/memories/...` plus `session_id`.
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`summary` must be English and detailed enough that `memories()` results alone
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can judge relevance without reading the file. Include the decision, the
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reasoning, and the key constraints — not just a title.
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The `message_start`/`message_end` range marks where in the conversation this
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conclusion was drawn. Use it later to trace back to the original evidence.
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Memory records survive index rebuilds. They are never auto-deleted.
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## Minimal Patterns
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Search, then expand one promising hit:
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```js
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const hits = search('auth fix', { limit: 5 });
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if (!hits.length) return [];
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return hits.slice(0, 3).map(h => ({
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session_id: h.session.id,
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session_title: h.session.title,
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uuid: h.message.uuid,
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snippet: h.message.text?.slice(0, 240),
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}));
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```
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Check helper fields before assuming names:
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```js
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const rows = summaries({ project: '%quiet-zero%', limit: 1 });
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return rows.length ? Object.keys(rows[0]) : [];
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```
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Fetch message neighbors without a full thread:
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```js
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const hit = search('runtime query', { limit: 1 })[0];
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return sql(
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`SELECT uuid, role, timestamp, substr(text,1,240) AS snippet
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FROM messages
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WHERE session_id=? AND timestamp>=?
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ORDER BY timestamp LIMIT 6`,
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hit.session.id,
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hit.message.timestamp
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);
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```
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See `references/query-patterns.md` for longer recipes.
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## Notes
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- First run builds the index. Later runs update incrementally.
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- DB location: `~/.claude/obelisk.sqlite`.
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- Query scripts run in a sandboxed VM with no filesystem or network access from inside the script.
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- Indexed text and stored tool inputs/results are truncated to 10k chars. Use `raw(uuid, { offset, limit })` for specific JSONL windows.
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