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Session Timeline

CommunityPopular
hoangsonww
session-timeline

Render an ordered timeline of one Claude Code session's events (every event type) with per-event durations and tool names, reconstructed from Agent Monitor data. Pairs PreToolUse with PostToolUse to compute tool durations and surfaces gaps, errors, and compaction points. Use when reconstructing what happened in a session step by step.

Overview

Publisherhoangsonww
RepositoryClaude-Code-Agent-Monitor
Skill namesession-timeline
Stars
1.1K
Forks
260
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hoangsonww on GitHub. Read the source before you install it.

Installation

Install the Session Timeline AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-sessions/skills/session-timeline
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git /tmp/Claude-Code-Agent-Monitor
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Agent-Monitor/plugins/ccam-sessions/skills/session-timeline .claude/skills/session-timeline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Session Timeline in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Session Timeline on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Session Timeline is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Session Timeline

Reconstruct the chronological event timeline of a single Claude Code session.

Input

The user provides: $ARGUMENTS

  • A session ID to time-line, or
  • "latest" / "last" for the most recent session.

Data Sources

EndpointReturns
GET /api/sessions/:idsession header: status, model, cwd, started_at, ended_at, cost, metadata (thinking_blocks, turn_count, total_turn_duration_ms) — and nested events
GET /api/events?session_id=Xthe full event stream: event_type (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, Notification, Compaction, APIError, TurnDuration), tool_name, summary, data, timestamp

Report Sections

1. Resolve & header

If "latest", GET /api/sessions?limit=1 to get the id, then GET /api/sessions/:id. Print a one-line header: id, status, model, cwd basename, started_at → ended_at, turn_count, total_turn_duration_ms, cost.

2. Build the ordered timeline

GET /api/events?session_id=X. Sort strictly by timestamp. For each event emit a row with: relative offset from started_at (e.g. +00:03.412), event_type, tool_name (when present), and a one-line summary.

3. Compute durations

Pair each PreToolUse with its matching PostToolUse (same tool_name, next occurrence) and show the tool's wall-clock duration. For TurnDuration events use the recorded duration directly. Flag any PreToolUse with no matching PostToolUse as unclosed.

4. Annotate notable points

Mark APIError (❌), Compaction (⚠️ context compressed), SubagentStop (subagent finished), Notification (ℹ️), and any timeline gap > 30s between consecutive events as an idle window.

5. Tallies

Event count by type, total tool time vs. session wall time, and the longest single tool call.

Output

A Markdown table — offset | event_type | tool_name | duration | summary — in strict timestamp order, preceded by the header line and followed by the tallies. Durations in ms or mm:ss.mmm; currency as USD to 4 decimal places. Never invent a duration when a PostToolUse is missing — label it unclosed. If the dashboard is unreachable, tell the user to start it with npm start from the repo root.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Session Timeline AI skill do?

Render an ordered timeline of one Claude Code session's events (every event type) with per-event durations and tool names, reconstructed from Agent Monitor data. Pairs PreToolUse with PostToolUse to compute tool durations and surfaces gaps, errors, and compaction points. Use when reconstructing what happened in a session step by step.

Why use Session Timeline on TypingMind?

Because you install it once and use it with any model. Session Timeline is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Session Timeline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-sessions/skills/session-timeline. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Session Timeline?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Session Timeline?

As many as you like. As long as a model supports skills, you can use Session Timeline with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Session Timeline AI skill free?

Yes. It is published on GitHub by hoangsonww under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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