tommy0103
297ef01eaf
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.
158 lines
5.6 KiB
Markdown
158 lines
5.6 KiB
Markdown
<div align="center">
|
|
|
|
<picture>
|
|
<source media="(prefers-color-scheme: dark)" srcset=".github/assets/obelisk-wordmark-d.svg">
|
|
<img src=".github/assets/obelisk-wordmark-l2.svg" alt="Obelisk" width="540">
|
|
</picture>
|
|
|
|
[](https://github.com/tommy0103/obelisk/stargazers)
|
|
[](https://github.com/tommy0103/obelisk/releases)
|
|
[](LICENSE)
|
|
|
|
Every past session, subagent, and workflow -- queryable by your agent.
|
|
|
|
**Humans should not browse session history. Agents should query it.**
|
|
|
|
</div>
|
|
|
|
<br />
|
|
|
|
<div align="center">
|
|
<img src=".github/assets/demo.png" alt="Obelisk in action" width="540">
|
|
<br />
|
|
<p>Ask in plain language. The agent writes the query, runs it, answers.</p>
|
|
</div>
|
|
|
|
## Not a session browser
|
|
|
|
Most history tools help humans find old chats.
|
|
|
|
Obelisk is built for agents. It exposes past work as structured data: sessions,
|
|
messages, tool calls, subagents, workflows, file history, failures, and parent
|
|
chains. The agent writes the query, runs it locally, and answers in plain language.
|
|
|
|
You don't manage history. You ask questions about past work.
|
|
|
|
## Why Obelisk
|
|
|
|
| Session library | Obelisk |
|
|
|---|---|
|
|
| Find an old chat | Answer a question about past work |
|
|
| Human browses snippets | Agent writes and runs a query |
|
|
| Search result list | Structured context and reasoning |
|
|
| Sessions as documents | Sessions as queryable memory |
|
|
| Good for recall | Good for investigation |
|
|
|
|
## What you can ask
|
|
|
|
```
|
|
/obelisk 上次 auth bug 最后到底改了哪些文件，为什么这么改
|
|
/obelisk 这个文件最近在哪些 sessions 里被反复修改
|
|
/obelisk 找出最近失败的 tool calls，它们分别发生在哪些任务里
|
|
/obelisk 那个 review workflow 的 subagents 各自结论是什么
|
|
/obelisk 我之前有没有试过这个方案，结果为什么放弃了
|
|
```
|
|
|
|
Anything Claude Code has done before -- sessions, tool calls, subagents, workflows -- becomes structured, queryable memory. Ask in your own words.
|
|
|
|
## Install
|
|
|
|
```bash
|
|
npx skills add tommy0103/obelisk
|
|
```
|
|
|
|
Or manually: copy `obelisk/` into your project's `.claude/skills/`.
|
|
|
|
Then in any Claude Code session:
|
|
|
|
```
|
|
/obelisk <your question>
|
|
```
|
|
|
|
First run builds the index (~5 seconds for 100 sessions). After that it rebuilds incrementally.
|
|
|
|
### Requires
|
|
|
|
- Node.js 22+ (uses built-in node:sqlite with FTS5)
|
|
- Claude Code with skills support.
|
|
|
|
## How it works
|
|
|
|
```
|
|
You ask a question
|
|
↓
|
|
Agent writes a JS query against the SQLite index
|
|
↓
|
|
Runs it via node runtime.mjs --query <script>
|
|
↓
|
|
Reads the JSON result, answers you in natural language
|
|
```
|
|
|
|
**The core idea: don't make humans browse, tag, or organize sessions.**
|
|
Don't invent a rigid query DSL either.
|
|
|
|
Agents can write code. So Obelisk gives them a small local query runtime over
|
|
your past work.
|
|
|
|
The agent starts from a small core API, then uses structured shortcuts and
|
|
references only when the question needs them:
|
|
|
|
**Core primitives** — the main CodeAct surface:
|
|
|
|
- `search(text)` — FTS5 full-text search, returns matches with surrounding context
|
|
- `context(uuid)` — full story around a message (parent chain, subagent/workflow metadata)
|
|
- `sql(query, ...params)` — raw SQL for anything else
|
|
|
|
**Structured shortcuts** — session, summary, subagent, workflow, file-history,
|
|
failure, raw-window, and parent-chain helpers over the same SQLite data.
|
|
|
|
**References** — agent reads on demand when the task needs deeper structure:
|
|
|
|
- `references/schema.md` — full SQLite schema and API reference
|
|
- `references/query-patterns.md` — copyable CodeAct recipes for common retrieval tasks
|
|
- `references/pitfalls.md` — scope, FTS, ordering, compact/raw, and field-name traps
|
|
|
|
The design is progressive disclosure with guardrails: the main skill keeps the
|
|
core contract and high-risk pitfalls visible, while longer recipes and the full
|
|
schema stay out of the first prompt until the agent needs them.
|
|
|
|
## What gets indexed
|
|
|
|
| Layer | Source | What's captured |
|
|
|-------|--------|----------------|
|
|
| **Sessions** | `<project>/<sessionId>.jsonl` | Title, project, timestamps, git branch |
|
|
| **Messages** | user + assistant turns | Full text, model, token usage, parent chain |
|
|
| **Tool calls** | every tool invocation | Tool name, input, file paths touched |
|
|
| **Subagents** | `subagents/agent-<id>.jsonl` | Agent type, description, full conversation |
|
|
| **Workflows** | `workflows/wf_<runId>.json` | Script, structured result, agent count |
|
|
| **Workflow agents** | `subagents/workflows/wf_<runId>/` | Per-agent transcripts linked to workflow |
|
|
|
|
Full-text search via FTS5 covers message text across every layer, while the SQLite tables preserve the structure agents need for investigation.
|
|
|
|
## Structure
|
|
|
|
```
|
|
.claude/skills/obelisk/
|
|
├── SKILL.md # Skill definition + simple API + examples
|
|
├── scripts/
|
|
│ └── runtime.mjs # Indexer + query runtime (400 lines, zero deps)
|
|
└── references/
|
|
├── schema.md # Full table schema + advanced API reference
|
|
├── query-patterns.md # Copyable retrieval recipes
|
|
└── pitfalls.md # Scope, FTS, ordering, and compactness traps
|
|
```
|
|
|
|
## Implementation Notes
|
|
|
|
The index rebuilds incrementally — only new or modified JSONL files are re-parsed.
|
|
|
|
Zero npm dependencies. Uses Node 22's built-in node:sqlite with FTS5. The entire runtime is ~400 lines.
|
|
|
|
20K lines of scattered JSONL → something the agent can search() and sql() against in milliseconds.
|
|
|
|
---
|
|
|
|
## License
|
|
|
|
MIT @tommy0103
|