docs(SKILL.md): add raw() usage and sql schema reminder

README.md

@@ -5,17 +5,16 @@
   <img src=".github/assets/obelisk-wordmark-l2.svg" alt="Obelisk" width="540">
 </picture>
 
-Every past session, subagent, and workflow — searchable in natural language.
-
 [![stars](https://img.shields.io/github/stars/tommy0103/obelisk?style=flat-square)](https://github.com/tommy0103/obelisk/stargazers)
 [![version](https://img.shields.io/github/v/tag/tommy0103/obelisk?label=version&style=flat-square)](https://github.com/tommy0103/obelisk/releases)
 [![license](https://img.shields.io/badge/license-MIT-blue.svg?style=flat-square)](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">
@@ -24,18 +23,37 @@ Every past session, subagent, and workflow — searchable in natural language.
   <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 上次那个 auth 的 bug 我怎么修的
+/obelisk 上次 auth bug 最后到底改了哪些文件，为什么这么改
-/obelisk 哪些文件这周被反复修改
+/obelisk 这个文件最近在哪些 sessions 里被反复修改
-/obelisk 最近 workflow 跑出来什么结果
+/obelisk 找出最近失败的 tool calls，它们分别发生在哪些任务里
-/obelisk 我让 subagent 做过哪些代码 review
+/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 — is indexed and searchable. Ask in your own words.
+Anything Claude Code has done before -- sessions, tool calls, subagents, workflows -- becomes structured, queryable memory. Ask in your own words.
 
 ## Install
 
@@ -58,19 +76,6 @@ First run builds the index (~5 seconds for 100 sessions). After that it rebuilds
 - Node.js 22+ (uses built-in node:sqlite with FTS5)
 - Claude Code with skills support.
 
-## 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 all message text across every layer.
-
 ## How it works
 
 ```
@@ -83,7 +88,11 @@ Runs it via node runtime.mjs --query <script>
 Reads the JSON result, answers you in natural language
 ```
 
-The core idea: **don't design a query DSL** — let the agent write code. An agent that can write workflow scripts can also write query scripts. Same sandbox, same mental model.
+**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 has a two-tier API. Most questions only need the simple layer:
 
@@ -99,6 +108,19 @@ The agent has a two-tier API. Most questions only need the simple layer:
 
 The design is progressive disclosure: the agent doesn't see the full schema until it needs it.
 
+## 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
 
 ```
@@ -110,7 +132,7 @@ The design is progressive disclosure: the agent doesn't see the full schema unti
     └── schema.md          # Full table schema + advanced API + query patterns
 ```
 
-## Design
+## Implementation Notes
 
 The index rebuilds incrementally — only new or modified JSONL files are re-parsed.
 
@@ -124,4 +146,3 @@ Zero npm dependencies. Uses Node 22's built-in node:sqlite with FTS5. The entire
 
 MIT @tommy0103
 
-

SKILL.md

@@ -58,6 +58,8 @@ Latest n sessions (default 10). Returns session rows with title, project, starte
 
 Raw SQL. Use `?` placeholders. Returns array of row objects.
 
+**Before writing your first SQL query, read `references/schema.md` for the full table schema, column names, and relationships.** Don't guess column names — the schema is your source of truth.
+
 Tables: `sessions`, `messages`, `tool_calls`, `tool_results`, `subagents`, `workflows`, `workflow_agents`, `messages_fts`
 
 ### Other APIs
@@ -69,6 +71,26 @@ Tables: `sessions`, `messages`, `tool_calls`, `tool_results`, `subagents`, `work
 - `workflowTree(runId)` -- workflow + its agents + all their messages
 - `fileHistory(filePath)` -- every Edit/Write/Read on a file across sessions
 - `failures(sessionId?)` -- tool calls that returned errors, with surrounding context
+- `raw(uuid, opts?)` -- windowed access to the original JSONL line (bypasses index truncation)
+
+### raw(uuid, opts?)
+
+Some indexed fields (tool call inputs, tool results) are truncated to 10k chars. `raw()` reads the original JSONL line to recover the full content.
+
+Returns: `{ text, totalLength, offset, limit, hasMore }`
+
+opts: `{ offset: 0, limit: 10000 }` — character window into the raw JSONL line.
+
+```js
+// First window
+const r = raw(messageUuid)
+// r.text = first 10k chars of the original JSONL line
+// r.totalLength = full line length
+// r.hasMore = true if more content remains
+
+// Scroll forward
+const r2 = raw(messageUuid, { offset: 10000, limit: 10000 })
+```
 
 ## Examples