# exploring-llm-traces

Inspect and debug AI agent traces using PostHog MCP tools. It helps trace errors and track token usage from trace links.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 408 installs · ★ 76
- Author: PostHog
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/PostHog/skills/tree/HEAD/skills/omnibus/exploring-llm-traces/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/exploring-llm-traces

## What it does

This skill guides agents through debugging LLM trace trees via PostHog MCP tools. Each trace links high-level `$ai_trace` containers to subagent steps (`$ai_span`) and single model calls (`$ai_generation`). The agent inspects the URL structure, separating single trace paths at `/ai-observability/traces/<trace_id>` from multi-trace sessions under `/ai-observability/sessions/<session_id>`.

Investigation starts with `detail: "summary"` to retrieve event metadata and latencies without clogging context with conversation payloads. When inspecting exact prompts or tool inputs, the agent switches to `detail: "full"` or runs local Python scripts from `scripts/` to parse large JSON files saved on disk.

Querying `events.properties.$ai_input` or `$ai_output_choices` in HogQL yields nothing because PostHog stores raw conversation content exclusively in the `posthog.ai_events` table. You need this dedicated table whenever you craft custom SQL queries.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add PostHog/skills --skill exploring-llm-traces -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/exploring-llm-traces/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/exploring-llm-traces/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add PostHog/skills --skill exploring-llm-traces -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/exploring-llm-traces/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add PostHog/skills --skill exploring-llm-traces -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/exploring-llm-traces/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install PostHog/skills exploring-llm-traces
```

2. **Manually: put the files in place**
- File: `.github/skills/exploring-llm-traces/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add PostHog/skills --skill exploring-llm-traces -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/PostHog/skills --path skills/omnibus/exploring-llm-traces
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/exploring-llm-traces/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add PostHog/skills --skill exploring-llm-traces -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/PostHog/skills/tree/HEAD/skills/omnibus/exploring-llm-traces/SKILL.md

## When to use it
- pinpoint failed tool calls within agent execution traces
- inspect prompt payloads and model outputs for a specific span
- parse large trace trees saved as JSON files using Python
- check latency and token consumption across subagent runs

## Example prompts
- Investigate what failed in trace `/ai-observability/traces/<trace_id>`
- Pull trace summaries for session `/ai-observability/sessions/<session_id>` and list errors
- Inspect full input and output payloads for the tool call in trace `<trace_id>`

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 495a10d38cf5d59f.

BEGIN THIRD-PARTY FILE 495a10d38cf5d59f
````text
---
name: exploring-llm-traces
description: >
  Debug and inspect LLM/AI agent traces using PostHog's MCP tools.
  Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>),
  asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly,
  verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions,
  or analyze token usage and costs. Also use when raw SQL/HogQL against
  `events.properties.$ai_input` / `$ai_output_choices` returns empty — message content lives only
  on the dedicated `posthog.ai_events` table.
---

# Exploring LLM traces with MCP tools

PostHog captures LLM/AI agent activity as traces. Each trace is a tree of events representing
a single AI interaction — from the top-level agent invocation down to individual LLM API calls.

## Available tools

| Tool                            | Purpose                                                       |
| ------------------------------- | ------------------------------------------------------------- |
| `posthog:query-llm-traces-list` | Search and list traces; can return large multi-trace payloads |
| `posthog:query-llm-trace`       | Get a single trace by ID with full event tree                 |
| `posthog:read-data-schema`      | Discover custom event/person properties before filtering      |
| `posthog:execute-sql`           | Ad-hoc SQL for complex trace analysis                         |

## Event hierarchy

See the [event reference](./references/events-and-properties.md) for the full schema.

```text
$ai_trace (top-level container)
  └── $ai_span (logical groupings, e.g. "RAG retrieval", "tool execution")
        ├── $ai_generation (individual LLM API call)
        └── $ai_embedding (embedding creation)
```

Events are linked via `$ai_parent_id` → parent's `$ai_span_id` or `$ai_trace_id`.

## Workflow: debug a trace or session from a URL

### Step 1 — Classify the URL

First inspect the path. Do not treat every UUID-looking value as a trace ID.

- `/ai-observability/traces/<trace_id>` or legacy `/llm-analytics/traces/<trace_id>` / `/llm-observability/traces/<trace_id>` is a single trace. Fetch it with `posthog:query-llm-trace`.
- `/ai-observability/sessions/<session_id>` or legacy `/llm-analytics/sessions/<session_id>` is an AI session, not a trace. Fetch traces with `posthog:query-llm-traces-list` filtered by event property `$ai_session_id`.

Preserve `date_from` / `date_to` query parameters from the URL when present.
````
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