Files
obelisk/SKILL.md
T
tommy0103 297ef01eaf refactor(docs): restructure SKILL.md into progressive-disclosure layers
Split the monolithic skill prompt into three tiers:
  - Core API (search/context/sql) stays in the first prompt
  - Structured helpers listed as one-liners with filter signatures
  - Detailed patterns and pitfalls extracted to references/

  Add references/query-patterns.md (copyable CodeAct recipes) and
  references/pitfalls.md (scope, FTS, ordering, compactness traps).
  Clarify project scope semantics (slug vs path vs cwd) throughout.
  Add ORDER BY timestamp DESC to failures() for newest-first default.
2026-06-07 16:42:41 +08:00

200 lines
8.6 KiB
Markdown

---
name: obelisk
description: >
Search and query past Claude Code session history.
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".
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.
allowed-tools:
- Read
- Bash(node:*)
- Write
---
# obelisk
Search and query Claude Code session history stored in `~/.claude/`.
Obelisk indexes sessions, messages, tool calls, tool results, summaries,
subagents, workflows, workflow agents, parent chains, and raw JSONL lines into
SQLite + FTS5.
Obelisk is a CodeAct memory layer: write a small JS query, run it locally, read
the JSON, then answer. Do not turn history into a flat document or browse entire
sessions by default.
## Quick Start
The skill directory is provided as `$SKILL_DIR` at invocation time.
Fast keyword search:
```bash
node $SKILL_DIR/scripts/runtime.mjs --search "keyword"
```
Custom query:
1. Write a bounded JS query to a temp file, for example `/tmp/q.mjs`.
2. Run:
```bash
node $SKILL_DIR/scripts/runtime.mjs --query /tmp/q.mjs
```
3. Parse JSON stdout and answer with concise evidence.
The query file runs inside `(async () => { ... })()`. Use `return` to emit JSON.
## Reference Triggers
Use progressive disclosure, but do not guess.
- Read `references/schema.md` before raw `sql()` unless the needed table/column relationship is already explicit here.
- Read `references/query-patterns.md` for workflow trees, failed tool counts or failure groups, broad development-history synthesis, file history synthesis, summary neighbors, subagent recall, raw windows, and empty-result handling.
- Read `references/pitfalls.md` when a scoped result is empty or tiny, when a query may over-fetch, when a term is hyphenated, when project scope is ambiguous, or when helper row fields are unclear.
If a helper row shape is unclear, first run a tiny scoped query and return
`Object.keys(row)` or a compact sample. Do not invent field names.
## Core API
### `search(text, opts?)`
Full-text search across main messages, subagent messages, and workflow-agent
messages.
Returns:
```js
[{ message: { uuid, text, role, timestamp, model, cwd },
session: { id, title, project, started_at },
rank,
context }]
```
`context` here means temporal neighbors: nearby messages in the same session by
timestamp. It is not the parent chain. Use `context(uuid)` or `trace(uuid)` for
causal/parent-chain context.
Opts: `{ limit, sessionId, project, after, before, cwd }`.
`project` is a SQL `LIKE` filter over `sessions.project`, not an exact project
identity. Results are already ordered by FTS5 rank; lower rank sorts earlier.
Prefer returned order over manually interpreting numeric rank unless you are
deliberately using FTS5 semantics.
### `context(uuid)`
Returns the full story around one indexed message:
```js
{ message, parentChain, session, subagent, workflow }
```
Use this after `search()` finds a promising message. It is the usual way to
expand vertically from one evidence point without dumping the whole session.
### `sql(query, ...params)`
Raw SQL with `?` placeholders. Returns array rows.
Before writing non-trivial SQL, read `references/schema.md`. Common safe joins:
- `tool_calls` does not have timestamps. Join `messages m ON m.uuid = tc.message_uuid`.
- `tool_results` does not have timestamps. Join `messages m ON m.uuid = tr.message_uuid`.
- For project/session filters, join `sessions s ON s.id = <table>.session_id`.
- Prefer SQL-side `GROUP BY`, `COUNT`, `MAX`, `ORDER BY`, and `LIMIT` over hand-counting in the final answer.
Tables: `sessions`, `messages`, `tool_calls`, `tool_results`, `summaries`,
`subagents`, `workflows`, `workflow_agents`, `messages_fts`.
## Structured Helpers
These helpers are convenience accessors over the same SQLite structure. They do
not replace `sql()`; use `sql()` when you need an exact aggregation or a join
the helper does not expose.
All list helpers accept a bounded `limit`. Many also accept:
`{ project, after, before, sessionId, sessions, branch }`. Check the schema or a
tiny sample before relying on less common filters.
- `sessions(opts?)` -- session rows, newest first. `project` is a SQL `LIKE` pattern.
- `recent(n?)` -- shorthand for recent sessions.
- `summaries(opts?)` -- summary rows, newest first: `{ id, session_id, timestamp, source, content, session_title, project }`.
- `subagents(opts?)` -- subagent metadata plus `messageCount`.
- `workflows(opts?)` -- workflow runs, newest first.
- `workflowTree(runId)` -- workflow row plus parsed `result` and `agents`; may include bulky `script` and `result_json`, so project compact fields.
- `fileHistory(filePath, opts?)` -- Read/Edit/Write tool calls for a file, oldest first; includes many `Read` rows.
- `failures(opts?)` -- failed tool results with tool/session context, newest first.
- `trace(uuid)` -- parent chain from root to message.
- `thread(sessionId)` -- full session messages; last resort only.
- `raw(uuid, opts?)` -- windowed access to the original JSONL line.
## Retrieval Contract
Keep queries scoped, bounded, and structural.
- Preserve explicit project/session/file/time scopes. Empty or tiny scoped results are real results; do not broaden unless the user asks.
- Treat project scope as three distinct semantics: exact `sessions.project` slug, exact `sessions.project_path`, or fuzzy `LIKE` search. Use `sql()` for exact slug/path membership; helper `project` means fuzzy `LIKE`.
- Start with cheap locators: `sessions()`, `summaries()`, `search()`, or a small SQL query.
- Expand incrementally with `context()`, `trace()`, neighbor SQL, or `raw()` windows.
- Return compact evidence with stable IDs (`session_id`, `uuid`, `tool_call_id`, `run_id`, `agent_id`) and short snippets.
- Avoid `thread()` unless the user explicitly asks for a full transcript or all smaller probes are insufficient.
- Keep runtime JSON small. Do not return all sessions, all summaries, all tool calls, complete workflow trees, full raw messages, or whole tool results.
- When counting or aggregating, compute counts in SQL or in the query script and return those counts. Do not hand-count from long rows in prose.
- For recent failures or "which tasks failed" questions, aggregate by session/task and return counts plus sparse examples. Do not return raw failure rows.
- For broad "how did X evolve / what did we do / what problems happened" history synthesis, use a bounded facet sweep from `references/query-patterns.md`. For concept recall, session lookup, or exact term recall, keep compact `search()` first.
High-frequency field contracts:
- `summaries()` uses `source` and `content`, not `summary_type` or `text`.
- `search().context` is temporal neighbor context, not causal or parent-chain context.
- `fileHistory()` includes `Read`; filter to `Edit`/`Write` for causal change history.
- `workflowTree()` may expose raw `script` and `result_json`; omit them unless the user asks for raw workflow details.
- `fileHistory()` is ordered oldest first. For recent file changes, use SQL with `ORDER BY m.timestamp DESC`.
- FTS5 tokenizes hyphens and treats `search(text)` as raw `MATCH` syntax. For `workflow-script`, search the quoted tokenized phrase such as `"workflow script"` or use SQL `LIKE` for exact hyphen matching.
## Minimal Patterns
Search, then expand one promising hit:
```js
const hits = search('auth fix', { limit: 5 });
if (!hits.length) return [];
return hits.slice(0, 3).map(h => ({
session_id: h.session.id,
session_title: h.session.title,
uuid: h.message.uuid,
snippet: h.message.text?.slice(0, 240),
}));
```
Check helper fields before assuming names:
```js
const rows = summaries({ project: '%quiet-zero%', limit: 1 });
return rows.length ? Object.keys(rows[0]) : [];
```
Fetch message neighbors without a full thread:
```js
const hit = search('runtime query', { limit: 1 })[0];
return sql(
`SELECT uuid, role, timestamp, substr(text,1,240) AS snippet
FROM messages
WHERE session_id=? AND timestamp>=?
ORDER BY timestamp LIMIT 6`,
hit.session.id,
hit.message.timestamp
);
```
See `references/query-patterns.md` for longer recipes.
## Notes
- First run builds the index. Later runs update incrementally.
- DB location: `~/.claude/obelisk.sqlite`.
- Query scripts run in a sandboxed VM with no filesystem or network access from inside the script.
- Indexed text and stored tool inputs/results are truncated to 10k chars. Use `raw(uuid, { offset, limit })` for specific JSONL windows.