Downloading Batch Export Files logo

Downloading Batch Export Files

Organization
PostHog
downloading-batch-export-files

Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, export HogQL query results, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_batch_exports API. Covers starting the export with MCP, polling completion, and downloading via the existing REST redirect endpoint.

Overview

PublisherPostHog
Repositoryskills
Skill namedownloading-batch-export-files
Stars
77
Forks
8
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Downloading Batch Export Files 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/PostHog/skills/tree/main/skills/omnibus/downloading-batch-export-files
  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/PostHog/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/omnibus/downloading-batch-export-files .claude/skills/downloading-batch-export-files
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Downloading Batch Export Files 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 Downloading Batch Export Files 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 Downloading Batch Export Files 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.

Downloading batch export files

Use this skill when a user wants a one-off downloadable export of PostHog data. The export is started and monitored through MCP, but the final file download uses the existing REST endpoint directly.

Available MCP tools

ToolPurpose
posthog:file-download-batch-exports-createStart an on-demand export and return the run ID
posthog:file-download-batch-exports-retrievePoll the run status and return file IDs after completion

Do not rely on a generated MCP tool for the /download/ endpoint. That endpoint is a redirecting file download endpoint, so raw HTTP/download handling is the right interface until MCP has explicit redirect support.

Workflow

1. Choose the export shape

Ask a short clarifying question if the user did not specify the required inputs:

  • model: one of events, persons, sessions, or hogql
  • data_interval_start and data_interval_end: ISO 8601 datetimes. Any supplied bound may not be in the future. When both bounds are supplied, they must be ordered and at most one week apart Required for events, persons, and sessions. For hogql, required only for the placeholders the query references. If only one placeholder is referenced, the other bound may be omitted and the one-week limit does not apply.
  • file.format: Parquet or JSONLines; prefer Parquet for compact analytics exports and JSONLines for line-oriented text processing
  • file.compression: optional, one of zstd, gzip, brotli, lz4, or snappy. If JSONLines was chosen as format, only gzip and brotli are supported.
  • file.max_size_mb: part size in MiB, 1024 by default. A part can go a little over this size. Lower it when the user wants smaller parts, raise it for fewer and bigger ones, or set it to null to write a single file of any size.

For events, include and exclude are optional event-name filters. Use them only when the user asks for specific events or wants to omit specific events.

For hogql, pass the query as hogql_query and leave out include and exclude. You may prompt the user to export a slice of data by including a WHERE clause in the HogQL query, for example limiting results from the events table by bounding timestamp. Always prefer limiting the data exported to the minimum necessary to solve the user's request. Every column in the SELECT clause must be a field or have an alias. This model is in closed beta and is enabled per team.

A hogql query can reference the {data_interval_start} and {data_interval_end} placeholders. The export replaces them with the data_interval_start and data_interval_end values, so one query can export any interval. Supply a bound for every placeholder the query references; a missing bound fails the request. The bounds only replace placeholders and do not filter anything themselves, so a query without placeholders runs unchanged even when bounds are supplied. Prefer placeholders over literal dates when the user wants a time range, or several consecutive ranges from the same query. Compare with >= {data_interval_start} and < {data_interval_end}, so consecutive ranges do not export the same row twice.

2. Start the export

Call posthog:file-download-batch-exports-create with the selected shape. The response contains an id for the export run.

Example request:

json
{
  "model": "events",
  "file": {
    "format": "JSONLines",
    "compression": "gzip"
  },
  "include": ["$pageview"],
  "data_interval_start": "2026-05-25T00:00:00Z",
  "data_interval_end": "2026-05-26T00:00:00Z"
}

Example request for the hogql model:

json
{
  "model": "hogql",
  "file": {
    "format": "Parquet"
  },
  "hogql_query": "SELECT event, timestamp, properties.$current_url AS url FROM events WHERE timestamp >= {data_interval_start} AND timestamp < {data_interval_end}",
  "data_interval_start": "2026-05-25T00:00:00Z",
  "data_interval_end": "2026-05-26T00:00:00Z"
}

3. Poll until completion

Call posthog:file-download-batch-exports-retrieve with the returned id.

Status handling:

StatusAction
Starting or RunningWait briefly and poll again
CompletedRead the files array and download each file
CancelledStop and report that the run was cancelled
Failed, FailedRetryable, FailedBilling, Terminated, or TimedOutStop and report the error field

When Completed, the files array contains file UUIDs. For single-file exports it usually contains one UUID. For split exports, download every UUID unless the user asked for a specific part.

A Completed response also carries records_completed, the number of rows the run exported. Report it to the user, because the count is otherwise only visible by opening every file.

4. Optionally, cancel a running export

If required by the user, a running export can be cancelled by calling posthog:file-download-batch-exports-cancel-create with the returned id.

An export that has already finished or has already failed may not be cancelled.

After cancelling an export, the id may not be used anymore and the export must start again from the beginning. However, you may still use the id to retrieve the export status (which will always be Cancelled).

5. Download files through REST

Use a direct authenticated HTTP request to the existing endpoint:

text
GET /api/projects/{project_id}/file_download_batch_exports/{run_id}/download/{part}/

part can be either:

  • a file UUID from the files array returned by file-download-batch-exports-retrieve
  • a zero-based file index, ordered by key

If there is only one file, this also works without part:

text
GET /api/projects/{project_id}/file_download_batch_exports/{run_id}/download/

Let the HTTP client follow the redirect, or inspect the Location header if you need the temporary signed URL. Use the same PostHog authentication context as other API calls.

6. Save, do not print, file contents

Treat the result as a file download, not a chat response. Parquet is binary and must be written as bytes. JSONLines may still be large; save it to a file rather than pasting the contents unless the user explicitly asks for a tiny sample.

Use a filename that includes the model, run ID, and part identifier when possible, for example:

text
posthog-events-<run_id>-<part>.jsonl.gz
posthog-persons-<run_id>-<part>.parquet

Important notes

  • The maximum export interval is one week. Split longer user requests into separate export runs or ask which week to export.
  • The hogql model is in closed beta and is enabled per team. A permission error that says HogQL batch exports are not enabled means the team does not have the beta. Report that instead of retrying with a different query, and tell the user they can contact PostHog support to request access.
  • The hogql model runs under stricter resource limits than the other models, because user queries are less predictable. If an export fails on memory, execution time, or bytes read, suggest narrowing the query with a WHERE clause instead of retrying it unchanged.
  • The hogql model accepts an optional hogql_modifiers object. Each modifier in it overrides the project HogQL modifier with the same name for this export only, and the project modifiers apply to all others. Unless the project sets the convertToProjectTimezone modifier, timestamp columns come out in UTC, so pass {"convertToProjectTimezone": true} when the user wants them in the project timezone. Pass the same hogql_modifiers to posthog:file-download-batch-exports-count-rows-create, so that the count matches the export.
  • A run can briefly report Running after completion while file records are being created. Poll again instead of failing immediately.
  • Download URLs are temporary. If a URL expires, call the REST download endpoint again for a fresh redirect.
  • Do not send the signed URL to unrelated services unless the user explicitly asks; it grants temporary access to the exported file.
  • If the user wants all parts of a split export, iterate over every UUID in files; do not assume part 0 is enough.
  • Large batch exports may take a few minutes or even longer to complete. Suggest to the user that they can speed-up their download by including only certain events or narrowing the date range.

Frequently asked questions

What does the Downloading Batch Export Files AI skill do?

Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, export HogQL query results, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_batch_exports API. Covers starting the export with MCP, polling completion, and downloading via the existing REST redirect endpoint.

Why use Downloading Batch Export Files on TypingMind?

Because you install it once and use it with any model. Downloading Batch Export Files 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 Downloading Batch Export Files in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PostHog/skills/tree/main/skills/omnibus/downloading-batch-export-files. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Downloading Batch Export Files?

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 Downloading Batch Export Files?

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

Is the Downloading Batch Export Files AI skill free?

Yes. It is published on GitHub by PostHog 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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