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ccsniff

v1.1.24

Published

Watch Claude Code JSONL output files and emit structured events as a Node.js EventEmitter

Readme

ccsniff

Watch Claude Code JSONL output files and emit structured events as a Node.js EventEmitter.

Install

npm install ccsniff

Usage

import { watch } from 'ccsniff';

const watcher = watch()
  .on('conversation_created', ({ conversation }) => {
    console.log('New session:', conversation.title);
  })
  .on('streaming_progress', ({ block, role }) => {
    if (block.type === 'text') process.stdout.write(block.text);
  })
  .on('streaming_complete', ({ conversationId }) => {
    console.log('Done:', conversationId);
  });

process.on('SIGINT', () => watcher.stop());

CommonJS:

const { watch, JsonlWatcher } = require('ccsniff');

Mountable Express router (/v1/history/*)

ccsniff ships a mountable router that hosts all the read-only history endpoints used by AgentGUI's live client (/v1/history/snapshot, /sessions, /sessions/:sid/events, /search, /stream SSE, and POST /reindex). It reads ~/.claude/projects by default; override with the CLAUDE_PROJECTS_DIR env var. express is an optional peer dependency — install it in the host app.

import express from 'express';
import { createHistoryRouter } from 'ccsniff';

const app = express();
app.use(await createHistoryRouter({ projectsDir: process.env.CLAUDE_PROJECTS_DIR }));
app.listen(3000);

CLI

npx ccsniff --since 24h --grep "rs-exec" --limit 50
npx ccsniff --since 7d --role user --json
npx ccsniff -f                     # tail new events live
npx ccsniff --rollup out.ndjson --since 7d
npx ccsniff --unsloth train.jsonl --since 7d --no-subagents
npx ccsniff --unsloth train.jsonl --unsloth-format sharegpt --since 7d

Unsloth training export

--unsloth <out> writes one JSONL line per Claude Code session, ready for Unsloth / TRL conversational fine-tuning. All filter flags (--since, --project, --session, --no-subagents, ...) apply.

Two formats are supported via --unsloth-format:

  • messages (default) — OpenAI / ChatML shape with native tool calling:
    {"session_id":"...","messages":[
      {"role":"user","content":"find foobar"},
      {"role":"assistant","content":null,"tool_calls":[{"id":"tu1","type":"function","function":{"name":"Grep","arguments":"{\"pattern\":\"foobar\"}"}}]},
      {"role":"tool","tool_call_id":"tu1","content":"hit at line 3"},
      {"role":"assistant","content":"done"}
    ]}
  • sharegpt{conversations:[{from:human|gpt|tool, value}]}, compatible with standardize_sharegpt. Tool calls are inlined into the gpt turn as <tool_call>name(json-args)</tool_call>.

Sessions with no user/assistant turn pair are skipped (no training value).

GUI (Observatory)

A turnkey, zero-dep browser observatory ships with the package. It indexes every session in ~/.claude/projects and exposes sessions, projects, tools, timeline, errors, subagent tree, live stream, and BM25 full-text search.

npx ccsniff gui --open          # auto-open in default browser
npx ccsniff gui --port 4791     # custom port (default 4791)

Endpoints under /api/*: snapshot, sessions, projects, tools, timeline, stats, errors, subagents, events, search, stream (SSE).

API

watch(projectsDir?)JsonlWatcher

Creates and starts a watcher. projectsDir defaults to ~/.claude/projects.

new JsonlWatcher(projectsDir?)

Class constructor. Call .start() manually after attaching listeners.

watcher.start()this

Scans for existing .jsonl files and begins watching. Chainable.

watcher.stop()

Closes file descriptors and directory watcher.

Events

| Event | Payload | |---|---| | conversation_created | { conversation: { id, title, cwd }, timestamp } | | streaming_start | { conversationId, conversation, timestamp } | | streaming_progress | { conversationId, conversation, block, role, seq, timestamp } | | streaming_complete | { conversationId, conversation, seq, timestamp } | | streaming_error | { conversationId, error, recoverable, timestamp } | | error | Error |

block.type values: text, tool_use, tool_result, system, result, etc.

Requirements

Node >= 18. Zero external dependencies.

License

MIT