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ngtwolf

Telegram History via LifeQuery

by ngtwolf · GitHub ↗ · v1.0.1
cross-platform ✓ Security Clean
328
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Install in OpenClaw
/install lifequery
Description
Query your Telegram chat history using a LifeQuery instance. Use when the user wants to search past conversations, find shared links, or ask about specific p...
README (SKILL.md)

LifeQuery Telegram History Skill

Query your Telegram chat history using a LifeQuery instance.

When to Use

Use when the user wants to:

  • Search past Telegram conversations
  • Find shared links, photos, or files
  • Ask about specific people, events, or topics from their Telegram messages
  • Retrieve context from old chats

Configuration

Set these environment variables:

  • LIFEQUERY_BASE_URL: Base URL of your LifeQuery instance (e.g., http://localhost:3134/v1 or http://your-server:80/v1)
  • LIFEQUERY_API_KEY: Optional API key if protected

How it Works

The skill runs a Python script that sends search queries to the LifeQuery /chat/completions endpoint and returns semantically relevant answers with citations from the chat history.

Usage Guidance
This skill is coherent: it simply forwards a search query to a configured LifeQuery instance and returns the response. Before installing or using it, ensure the LIFEQUERY_BASE_URL points to a LifeQuery server you control or trust (a remote server could see all queries you send). If you use an API key, keep it secret. Note the skill itself does not access your Telegram app directly—it relies on the LifeQuery server to have imported or indexed your Telegram history. Also be aware of a minor metadata mismatch: SKILL.md and skill.yaml document the LIFEQUERY_* env vars (optional), even though registry metadata listed none.
Capability Analysis
Type: OpenClaw Skill Name: lifequery Version: 1.0.1 The lifequery skill is a legitimate tool designed to interface with a LifeQuery instance for searching Telegram chat history. The Python script (scripts/query_telegram.py) uses standard libraries to perform authenticated API requests to a user-defined endpoint, and the skill configuration (skill.yaml) and instructions (SKILL.md) are consistent with this purpose without any signs of malicious intent, data exfiltration, or prompt injection.
Capability Assessment
Purpose & Capability
The skill name/description, skill.yaml, SKILL.md, and the Python script all align: they call a LifeQuery /chat/completions endpoint to search Telegram history. The only configuration requested (LIFEQUERY_BASE_URL and optional LIFEQUERY_API_KEY) is appropriate. Minor note: registry metadata listed no required env vars while SKILL.md and skill.yaml document these environment variables (they are optional defaults), but this is a minor metadata mismatch rather than a functional inconsistency.
Instruction Scope
The runtime instructions and script are narrowly scoped: they accept a single query argument, read the LifeQuery base URL and optional API key from environment variables, POST a single request to /chat/completions, and print the response. They do not read local Telegram files or other system secrets. Note: the skill will send whatever query (potentially user content) to the configured LifeQuery endpoint, so the trustworthiness of that endpoint determines whether query content or context is exposed.
Install Mechanism
There is no install spec (instruction-only plus an included Python script). Nothing is downloaded or written to disk by an installer; the script runs with the system Python. This is low-risk from an install-mechanism perspective.
Credentials
The only environment settings are LIFEQUERY_BASE_URL and an optional LIFEQUERY_API_KEY, which are directly relevant and proportionate to reaching a LifeQuery service. The skill does not request unrelated credentials or access to other configuration paths.
Persistence & Privilege
The skill is not always-on and is user-invocable; it does not request persistent platform privileges or modify other skills/config. Autonomous invocation remains allowed by platform default but is not combined with broad or unusual privileges here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lifequery
  3. After installation, invoke the skill by name or use /lifequery
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Made backend calling more secure.
v1.0.0
Integrates: https://github.com/nikira-studio/lifequery This skill connects OpenClaw to LifeQuery—a powerful, self-hosted memory engine that ingests your entire Telegram chat history into a local database. By installing this skill, you give your agent the ability to: Search your actual past: Instantly recall old conversations, shared media links, and specific details from your personal Telegram history. Get Grounded Answers: The agent won't hallucinate your past; answers are generated directly from your chat logs and include source citations (e.g., showing which chat and date the info came from). Requirements: Requires configuration of LIFEQUERY_BASE_URL and optional LIFEQUERY_API_KEY.
Metadata
Slug lifequery
Version 1.0.1
License
All-time Installs 1
Active Installs 1
Total Versions 2
Frequently Asked Questions

What is Telegram History via LifeQuery?

Query your Telegram chat history using a LifeQuery instance. Use when the user wants to search past conversations, find shared links, or ask about specific p... It is an AI Agent Skill for Claude Code / OpenClaw, with 328 downloads so far.

How do I install Telegram History via LifeQuery?

Run "/install lifequery" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Telegram History via LifeQuery free?

Yes, Telegram History via LifeQuery is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Telegram History via LifeQuery support?

Telegram History via LifeQuery is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Telegram History via LifeQuery?

It is built and maintained by ngtwolf (@ngtwolf); the current version is v1.0.1.

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