709 lines
20 KiB
Markdown
709 lines
20 KiB
Markdown
# Obelisk Query Patterns
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These are copyable CodeAct patterns for `runtime.js --query` scripts plus
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`--attune` memory mutation patterns. They are not new APIs. Adapt them to the
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user's scope and return compact evidence.
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Read this before the first query for broad synthesis, progress summaries,
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design history, weekly/monthly reviews, or questions that ask what the user did,
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learned, decided, tried, or abandoned. Start with a helper-first pass; use raw
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`sql()` only when the helper surface cannot express the needed join or
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aggregation.
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## First Pass: Overview + Recall + Evidence
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Use this for broad synthesis before writing custom SQL. It gives the agent a
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map, prior notes, and raw session evidence in one bounded result. Then run a
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faceted detail pass if the first pass reveals useful projects, sessions, files,
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or terms.
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```js
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const topic = 'English topic terms translated from the user request';
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const map = overview({ limit: 6 });
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const project = map.current.project?.project;
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const scoped = project ? { project } : {};
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return {
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query_plan: {
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mode: 'first_pass',
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topic,
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project: project || null,
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limits: { sessions: 6, memories: 5, search: 8 },
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},
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orientation: map.current_project && {
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project: map.current_project.project,
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session_total: map.current_project.session_total,
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sessions: map.current_project.sessions.map(s => ({
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id: s.id,
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title: s.title,
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branch: s.git_branch,
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ended_at: s.ended_at,
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})),
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memory_total: map.current_project.memory_total,
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memories: map.current_project.memories.map(m => ({
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id: m.id,
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path: m.path,
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anchors: m.anchors,
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summary: m.summary?.slice(0, 240),
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})),
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},
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prior_memories: memories({ ...scoped, query: topic, limit: 5 }).map(m => ({
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id: m.id,
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path: m.path,
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anchors: m.anchors,
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session_id: m.session_id,
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created_at: m.created_at,
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rank: m.rank,
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summary: m.summary?.slice(0, 260),
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})),
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session_evidence: search(topic.replace(/[-_]/g, ' '), { ...scoped, limit: 8 })
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.slice(0, 6)
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.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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timestamp: h.message.timestamp,
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snippet: h.message.text?.slice(0, 220),
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})),
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};
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```
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## Orient Before Retrieval
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Use `overview()` when the current project or available scopes are unclear. Treat
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the result as a map, not evidence; follow up with `memories()`, `search()`,
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helpers, or `sql()` for facts.
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```js
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const map = overview({ limit: 6 });
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return {
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current: map.current,
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current_project: map.current_project && {
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project: map.current_project.project,
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session_total: map.current_project.session_total,
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sessions: map.current_project.sessions.map(s => ({
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id: s.id,
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title: s.title,
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branch: s.git_branch,
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ended_at: s.ended_at,
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})),
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memory_total: map.current_project.memory_total,
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memories: map.current_project.memories.map(m => ({
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id: m.id,
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path: m.path,
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anchors: m.anchors,
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summary: m.summary?.slice(0, 240),
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})),
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},
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projects: map.projects.slice(0, 8),
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totals: map.totals,
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};
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```
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## Bounded Search To Context
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Use `search()` to locate candidates, then expand only the strongest hits.
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```js
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const hits = search('"runtime query"', { project: '%quiet-zero%', limit: 8 });
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return hits.slice(0, 5).map(h => {
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const c = context(h.message.uuid);
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return {
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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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timestamp: h.message.timestamp,
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snippet: h.message.text?.slice(0, 240),
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parentChain: (c?.parentChain || []).slice(-3).map(m => ({
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uuid: m.uuid,
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role: m.role,
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snippet: m.text?.slice(0, 120),
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})),
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};
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});
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```
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## Memory Plus Session Evidence
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Use this when prior conclusions may exist but the answer still depends on raw
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session evidence. Keep memory as prior notes, not final authority; compare it
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with session evidence in your final answer when correctness matters.
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Memory query terms are English even when the user asks in another language.
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```js
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const project = '%quiet-zero%';
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const topic = 'markdown memory layer';
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const ftsTopic = topic.replace(/[-_]/g, ' ');
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const prior_memories = memories({
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project,
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query: topic,
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limit: 5,
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}).map(m => ({
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id: m.id,
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path: m.path,
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anchors: m.anchors,
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session_id: m.session_id,
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message_start: m.message_start,
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message_end: m.message_end,
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created_at: m.created_at,
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summary: m.summary?.slice(0, 260),
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rank: m.rank,
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}));
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const session_evidence = search(ftsTopic, { project, limit: 8 })
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.slice(0, 6)
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.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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timestamp: h.message.timestamp,
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snippet: h.message.text?.slice(0, 220),
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}));
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return {
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query_plan: {
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project,
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topic,
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memory_limit: 5,
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session_limit: 8,
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},
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prior_memories,
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session_evidence,
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};
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```
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## Attune Approved Memory
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Use this only after the user approves writing memory and the markdown file
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already exists. `remember()` validates the file and stores a normalized absolute
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path, so keep the script small and return the registered record.
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Run this script with `runtime.js --attune <script>`. The `--attune` runtime
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exposes only `remember()` and `forget()`, not retrieval helpers.
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```js
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return remember({
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path: '.obelisk/memories/memory-layer-design.md',
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session_id: 'source-session-id',
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message_start: 'first-message-uuid',
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message_end: 'last-message-uuid',
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anchors: [{ kind: 'file', path: 'SKILL.md' }],
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summary: [
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'Decision: Obelisk uses one user-facing entry that queries both memory and raw sessions.',
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'Memory records are prior notes and must be identified naturally when they influence an answer.',
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'New memory writes require human confirmation before the markdown file is written and registered.',
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].join(' '),
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});
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```
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## Forget Approved Memory
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Use this only after the user asks to archive an outdated or wrong memory. Identify
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the exact memory ID in a normal `--query` script first. If one candidate clearly
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matches the user's request, that request is approval to archive it; if several
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candidates match, ask which one to forget.
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Run the mutation with `runtime.js --attune <script>`:
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```js
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return forget({
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id: 'mem-id-to-delete',
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reason: 'Outdated by newer project guidance.',
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});
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```
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`forget()` archives the record. Active recall through `memories()` will omit it,
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and the markdown file at `path` is left in place.
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## Update Approved Memory
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Use this when the user explicitly corrects an existing memory, or after the
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agent proposes a replacement and the user approves. An update is one combined
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operation: archive the old record and register the replacement markdown file.
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The new markdown file must already exist before running `--attune`.
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```js
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const archived = forget({
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id: 'old-memory-id',
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reason: 'Replaced by updated memory from the current session.',
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});
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const created = remember({
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path: '.obelisk/memories/updated-memory.md',
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session_id: 'current-session-id',
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message_start: 'first-message-uuid',
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message_end: 'last-message-uuid',
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anchors: [{ kind: 'file', path: 'src/path/to/file.ts' }],
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summary: 'Updated summary: concise English retrieval surface for the replacement memory.',
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});
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return { archived, created };
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```
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If the agent only suspects a memory is stale, do not run this pattern yet.
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Answer from current evidence and ask whether to archive or replace the memory.
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## One-Shot Retrieval For Synthesis
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Use this for conclusion, broad history, failure investigation, or file evolution
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questions. The goal is to reduce conversation turns: keep intermediate search
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results inside the query script, then return only a compact task-local evidence
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view. This does not create stored semantic entities; the agent still reads the
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evidence and forms the conclusion. Expect 1-2 runtime queries: one broad compact
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evidence pass, and optionally one targeted detail pass by stable IDs.
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```js
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const project = '%quiet-zero%';
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const topic = 'obelisk retrieval semantics';
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const ftsTopic = topic.replace(/[-_]/g, ' ');
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const facets = [
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'summary conclusion',
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'runtime query script',
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'failure problem',
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'file change',
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];
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const candidates = [];
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for (const facet of facets) {
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for (const h of search(`${ftsTopic} ${facet}`, { project, limit: 4 })) {
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candidates.push({
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kind: 'message',
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facet,
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session_id: h.session.id,
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session_title: h.session.title,
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uuid: h.message.uuid,
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timestamp: h.message.timestamp,
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snippet: h.message.text?.slice(0, 220),
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});
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}
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}
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for (const s of summaries({ project, limit: 8 })) {
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if (/obelisk|retrieval|context|summary/i.test(`${s.content || ''} ${s.session_title || ''}`)) {
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candidates.push({
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kind: 'summary',
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facet: 'summary',
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summary_id: s.id,
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session_id: s.session_id,
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session_title: s.session_title,
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timestamp: s.timestamp,
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snippet: s.content?.slice(0, 240),
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});
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}
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}
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const seen = new Set();
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const evidence = [];
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for (const row of candidates.sort((a, b) => String(b.timestamp).localeCompare(String(a.timestamp)))) {
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const key = row.uuid || row.summary_id || `${row.session_id}:${row.timestamp}:${row.facet}`;
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if (seen.has(key)) continue;
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seen.add(key);
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evidence.push(row);
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if (evidence.length >= 16) break;
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}
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return {
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query_plan: { project, topic, facets, per_facet_limit: 4, max_evidence: 16 },
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evidence,
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omitted: Math.max(0, candidates.length - evidence.length),
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};
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```
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## Learned Faceted Detail Pass
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Use this after a broad sweep has identified candidate sessions and vocabulary.
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Prefer detail facets learned from the first pass over pulling large session
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windows. Fall back to small filtered windows only when the vocabulary is still
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unclear, and record that reason in `query_plan`.
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```js
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const sessionIds = [
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'first-pass-session-id-a',
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'first-pass-session-id-b',
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];
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const learnedFacets = [
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{ facet: 'architecture comparison', terms: ['ultrawork', 'TaskTree', 'parallel'] },
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{ facet: 'key judgment', terms: ['ridiculous', 'serial', 'parallel'] },
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{ facet: 'merge direction', terms: ['replan', 'merge', 'workflow'] },
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{ facet: 'prompt observation', terms: ['prompt', 'guideline', 'skill'] },
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];
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const rows = [];
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for (const { facet, terms } of learnedFacets) {
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const clauses = terms.map(() => 'm.text LIKE ?').join(' OR ');
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const params = [
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...sessionIds,
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...terms.map(t => `%${t}%`),
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];
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rows.push(...sql(`
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SELECT
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? AS facet,
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m.uuid,
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m.session_id,
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s.title AS session_title,
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m.timestamp,
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substr(m.text, 1, 220) AS snippet
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FROM messages m
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JOIN sessions s ON s.id = m.session_id
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WHERE m.session_id IN (${sessionIds.map(() => '?').join(',')})
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AND m.text IS NOT NULL
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AND (${clauses})
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ORDER BY m.timestamp
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LIMIT 3
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`, facet, ...params));
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}
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const seen = new Set();
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const evidence = [];
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for (const row of rows) {
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if (seen.has(row.uuid)) continue;
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seen.add(row.uuid);
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evidence.push(row);
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if (evidence.length >= 12) break;
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}
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return {
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query_plan: {
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mode: 'learned_faceted_detail',
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source: 'terms discovered in first pass',
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session_count: sessionIds.length,
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facets: learnedFacets.map(f => f.facet),
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per_facet_limit: 3,
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},
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evidence,
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};
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```
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## Facet Sweep For Broad History
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Use this only for broad synthesis questions such as "how did X evolve", "what
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did we do on X", or "what problems happened". Do not use it for concept recall,
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exact session lookup, exact term recall, or tasks that ask for compact search
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hits.
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Keep the sweep small: 3-4 facets, `limit: 3` per facet, and at most 12 compact
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evidence rows.
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```js
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const name = 'obelisk';
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const facets = [
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'runtime CLI script',
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'schema SQLite FTS',
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'skill API helper docs',
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'test failure problem',
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];
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const rows = [];
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for (const facet of facets) {
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for (const h of search(`${name} ${facet}`, { project: '%quiet-zero%', limit: 3 })) {
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rows.push({ facet, h });
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}
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}
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const seen = new Set();
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return rows
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.filter(({ h }) => {
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const key = h.message.uuid || `${h.session.id}:${h.message.timestamp}`;
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if (seen.has(key)) return false;
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seen.add(key);
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return true;
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})
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.slice(0, 12)
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.map(({ facet, h }) => ({
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facet,
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session_id: h.session.id,
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session_title: h.session.title,
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project: h.session.project,
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uuid: h.message.uuid,
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timestamp: h.message.timestamp,
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snippet: h.message.text?.slice(0, 180),
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}));
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```
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## Summary Rows And Neighbors
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Use `source`, `content`, `session_id`, `project`, and `session_title`.
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```js
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const rows = summaries({ project: '%quiet-zero%', limit: 8 });
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return rows.map(s => ({
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id: s.id,
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session_id: s.session_id,
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session_title: s.session_title,
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project: s.project,
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source: s.source,
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timestamp: s.timestamp,
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snippet: s.content?.slice(0, 240),
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}));
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```
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To inspect messages around one summary:
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```js
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const s = summaries({ project: '%quiet-zero%', limit: 1 })[0];
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if (!s) return { results: [] };
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const before = sql(
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`SELECT uuid, role, timestamp, substr(text,1,200) AS snippet
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FROM messages
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WHERE session_id=? AND timestamp<?
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ORDER BY timestamp DESC LIMIT 3`,
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s.session_id,
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s.timestamp
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);
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const after = sql(
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`SELECT uuid, role, timestamp, substr(text,1,200) AS snippet
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FROM messages
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WHERE session_id=? AND timestamp>?
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ORDER BY timestamp ASC LIMIT 3`,
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s.session_id,
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s.timestamp
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);
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return { summary: s, before, after };
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```
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## File History Synthesis
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`fileHistory()` contains reads as well as writes and old-to-new rows. For
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"why/how did this file change", scan a bounded `Edit`/`Write` set first, then
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return only compact evidence. Do not return 20 long snippets; keep runtime JSON
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small enough that the final answer, not the query output, carries the prose.
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```js
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const rows = fileHistory('/absolute/path/to/file', { limit: 80 });
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const writes = rows.filter(r => ['Edit', 'Write'].includes(r.toolCall?.name));
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const reads = rows.filter(r => r.toolCall?.name === 'Read');
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const targetTerms = ['summaries', 'failures', 'raw'];
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const bySession = new Map();
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for (const r of writes) {
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let input = {};
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try { input = JSON.parse(r.toolCall.input_json || '{}'); } catch {}
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const delta = String(input.new_string || input.content || input.old_string || '');
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const snippet = delta.slice(0, 220);
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const sid = r.session.id;
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const group = bySession.get(sid) || {
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session_id: sid,
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session_title: r.session.title,
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project: r.session.project,
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write_edit_count: 0,
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first_timestamp: r.timestamp,
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last_timestamp: r.timestamp,
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evidence: [],
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};
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group.write_edit_count++;
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group.first_timestamp = group.first_timestamp < r.timestamp ? group.first_timestamp : r.timestamp;
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group.last_timestamp = group.last_timestamp > r.timestamp ? group.last_timestamp : r.timestamp;
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if (group.evidence.length < 2) {
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group.evidence.push({
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tool: r.toolCall.name,
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tool_id: r.toolCall.id,
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timestamp: r.timestamp,
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mentions: targetTerms.filter(k => delta.toLowerCase().includes(k)),
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snippet,
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});
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}
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bySession.set(sid, group);
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}
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const sessions = [...bySession.values()].slice(0, 6);
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const returnedEvidence = sessions.reduce((n, s) => n + s.evidence.length, 0);
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return {
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counts: { reads: reads.length, writes_edits: writes.length },
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sessions,
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omitted_write_edit_rows: Math.max(0, writes.length - returnedEvidence),
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};
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```
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## Failed Tool Counts
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For precise counts, aggregate in SQL. Do not hand-count long result rows in the
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final answer.
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```js
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|
const counts = sql(`
|
|
SELECT
|
|
tc.name AS tool_name,
|
|
COUNT(*) AS failure_count,
|
|
MAX(m.timestamp) AS last_failure_at
|
|
FROM tool_results tr
|
|
JOIN tool_calls tc ON tc.id = tr.tool_use_id
|
|
JOIN messages m ON m.uuid = tr.message_uuid
|
|
JOIN sessions s ON s.id = tr.session_id
|
|
WHERE tr.is_error = 1
|
|
AND s.project LIKE ?
|
|
GROUP BY tc.name
|
|
ORDER BY failure_count DESC, last_failure_at DESC
|
|
LIMIT 20
|
|
`, '%quiet-zero%');
|
|
|
|
const examples = sql(`
|
|
SELECT
|
|
tr.tool_use_id,
|
|
tc.name AS tool_name,
|
|
m.timestamp,
|
|
s.id AS session_id,
|
|
s.title AS session_title,
|
|
substr(tr.content, 1, 180) AS error_snippet
|
|
FROM tool_results tr
|
|
JOIN tool_calls tc ON tc.id = tr.tool_use_id
|
|
JOIN messages m ON m.uuid = tr.message_uuid
|
|
JOIN sessions s ON s.id = tr.session_id
|
|
WHERE tr.is_error = 1
|
|
AND s.project LIKE ?
|
|
ORDER BY m.timestamp DESC
|
|
LIMIT 8
|
|
`, '%quiet-zero%');
|
|
|
|
return { counts, examples };
|
|
```
|
|
|
|
## Failure Investigation Groups
|
|
|
|
For questions like "recent failed tool calls", "which tasks failed", or "group
|
|
failures by task/session", group structurally and return sparse examples. Use
|
|
SQL for counts; treat `failures()` as an evidence helper, not a precise counter.
|
|
|
|
```js
|
|
const project = '%quiet-zero%';
|
|
|
|
const groups = sql(`
|
|
SELECT
|
|
s.id AS session_id,
|
|
s.title AS session_title,
|
|
s.project,
|
|
COUNT(*) AS failure_count,
|
|
MAX(m.timestamp) AS last_failure_at
|
|
FROM tool_results tr
|
|
JOIN tool_calls tc ON tc.id = tr.tool_use_id
|
|
JOIN messages m ON m.uuid = tr.message_uuid
|
|
JOIN sessions s ON s.id = tr.session_id
|
|
WHERE tr.is_error = 1
|
|
AND s.project LIKE ?
|
|
GROUP BY s.id
|
|
ORDER BY last_failure_at DESC
|
|
LIMIT 10
|
|
`, project);
|
|
|
|
const examples = sql(`
|
|
SELECT
|
|
tr.tool_use_id AS tool_call_id,
|
|
tc.name AS tool_name,
|
|
s.id AS session_id,
|
|
m.timestamp,
|
|
substr(tr.content, 1, 180) AS error_snippet
|
|
FROM tool_results tr
|
|
JOIN tool_calls tc ON tc.id = tr.tool_use_id
|
|
JOIN messages m ON m.uuid = tr.message_uuid
|
|
JOIN sessions s ON s.id = tr.session_id
|
|
WHERE tr.is_error = 1
|
|
AND s.project LIKE ?
|
|
ORDER BY m.timestamp DESC
|
|
LIMIT 12
|
|
`, project);
|
|
|
|
return { groups, examples };
|
|
```
|
|
|
|
## Workflow Tree Compact View
|
|
|
|
Find the run with `workflows()` under scope, then project `workflowTree()` into
|
|
compact fields. Do not return raw `script`, `result_json`, or the full tree.
|
|
|
|
```js
|
|
const runs = workflows({ project: '%quiet-zero%', limit: 30 });
|
|
const target = runs.find(w =>
|
|
/session[-_ ]journal/i.test(`${w.workflow_name || ''} ${w.task_id || ''} ${w.run_id || ''}`)
|
|
);
|
|
if (!target) {
|
|
return {
|
|
found: false,
|
|
candidates: runs.slice(0, 8).map(w => ({
|
|
run_id: w.run_id,
|
|
workflow_name: w.workflow_name,
|
|
timestamp: w.timestamp,
|
|
agent_count: w.agent_count,
|
|
})),
|
|
};
|
|
}
|
|
|
|
const tree = workflowTree(target.run_id);
|
|
return {
|
|
run_id: target.run_id,
|
|
workflow_name: target.workflow_name,
|
|
status: tree?.status ?? target.status,
|
|
timestamp: tree?.timestamp ?? target.timestamp,
|
|
agent_count: tree?.agent_count ?? tree?.agents?.length ?? target.agent_count,
|
|
agents: (tree?.agents || []).map(a => ({
|
|
agent_id: a.agent_id,
|
|
phase: a.phase,
|
|
label: a.label,
|
|
state: a.state,
|
|
tokens: a.tokens,
|
|
messageCount: a.messageCount,
|
|
})),
|
|
};
|
|
```
|
|
|
|
## Subagent Metadata Recall
|
|
|
|
Use `subagents()` for metadata. Do not expand transcripts unless the user asks.
|
|
|
|
```js
|
|
const rows = subagents({ project: '%quiet-zero%', limit: 50 });
|
|
return rows
|
|
.filter(r => /obelisk/i.test(`${r.description || ''} ${r.agent_type || ''}`))
|
|
.map(r => ({
|
|
agent_id: r.agent_id,
|
|
agent_type: r.agent_type,
|
|
description: r.description,
|
|
session_id: r.session_id,
|
|
messageCount: r.messageCount,
|
|
total_tokens: r.total_tokens,
|
|
}));
|
|
```
|
|
|
|
## Empty Result Without Fallback
|
|
|
|
If the user asks for an exact sentinel, scoped project, or exact file, an empty
|
|
result is valid. Report it; do not broaden automatically.
|
|
|
|
```js
|
|
const needle = 'obelisk-impossible-sentinel-20260602';
|
|
const hits = search(`"${needle.replace(/-/g, ' ')}"`, { limit: 10 });
|
|
const real = hits.filter(h => {
|
|
const scope = `${h.session?.project || ''} ${h.message?.cwd || ''}`;
|
|
return !/SkillOpt[-/. ]outputs|obelisk_train|obelisk-eval/i.test(scope);
|
|
});
|
|
return real.map(h => ({
|
|
session_id: h.session.id,
|
|
session_title: h.session.title,
|
|
project: h.session.project,
|
|
uuid: h.message.uuid,
|
|
snippet: h.message.text?.slice(0, 200),
|
|
}));
|
|
```
|
|
|
|
## Raw Window
|
|
|
|
Use `raw()` only after identifying a specific message UUID.
|
|
|
|
```js
|
|
const row = sql(`
|
|
SELECT uuid, length(text) AS indexed_len
|
|
FROM messages
|
|
WHERE length(text) >= 10000
|
|
LIMIT 1
|
|
`)[0];
|
|
if (!row) return null;
|
|
const first = raw(row.uuid, { offset: 0, limit: 4000 });
|
|
return {
|
|
uuid: row.uuid,
|
|
indexed_len: row.indexed_len,
|
|
totalLength: first?.totalLength,
|
|
hasMore: first?.hasMore,
|
|
text: first?.text?.slice(0, 500),
|
|
};
|
|
```
|