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The PandaProbe Agent Skill teaches AI coding agents — Claude Code, Cursor, and other tools that support the open Agent Skills standard — how to work with PandaProbe. With it installed, your agent knows how to set up PandaProbe, instrument your app, and drive the pandaprobe CLI without you spelling out the details every time. It’s open source and lives at github.com/chirpz-ai/pandaprobe-skills.

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Why use it

Coding agents produce significantly better results with the skill installed, because it conditions them to follow PandaProbe’s best practices — work doc-first instead of guessing APIs from memory, use the CLI for data access instead of hand-building requests, and never echo API keys into the chat. The skill is self-contained: a SKILL.md entry point plus focused reference docs. 
SKILL.md
references/
  ├── setup.md            # guided onboarding playbook
  ├── instrumentation.md  # SDK tracing across frameworks and providers
  └── cli.md              # the pandaprobe CLI command tree and recipes
It uses a progressive disclosure model to keep context usage low. The agent only sees the skill’s name and description until a task matches; it then reads SKILL.md, and pulls in a specific reference file (setup.md, instrumentation.md, or cli.md) only when that topic comes up.

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What it can do

Onboard a project

Guided, interactive setup that builds and runs a first traced agent example from scratch and verifies the traces landed — ideal for a new or empty project.

Instrument your app

Add PandaProbe tracing via an agent-framework integration, a provider wrapper, or manual decorators — working doc-first against the live documentation.

Read & evaluate data

Use the pandaprobe CLI to inspect traces, sessions, spans, and scores, and to run evaluations.

Look up the docs

Fetch the latest PandaProbe documentation — the source of truth that all instrumentation relies on.

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Install

The skill is distributed through npx skills, the open agent-skills CLI.
The simplest path is to ask your coding agent to install it. Paste a prompt like:
Install the PandaProbe agent skill from the chirpz-ai/pandaprobe-skills GitHub repository.

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Prerequisites

The skill installs the instructions, not the tools. Depending on what you ask it to do, you’ll also need:
  • The pandaprobe CLI — for data and evaluation access. Install with: 
    curl -fsSL https://cli.pandaprobe.com/install.sh | sh
  • A PandaProbe account and API key — sign up at app.pandaprobe.com, then run pandaprobe auth login. Self-hosted deployments can configure an endpoint and key manually instead.
  • Python 3.10+ with pip install pandaprobe — for SDK instrumentation.

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Usage examples

Once installed, the agent picks the skill up automatically for prompts like:
  • “Set up PandaProbe in this project and show me my first traces.”
  • “Add PandaProbe tracing to my LangGraph agent.”
  • “Use pandaprobe to list my failed traces, then drill into the error in trace tr_….”
  • “Run a coherence eval over yesterday’s completed traces.”

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Resources

Skill repository

The open-source pandaprobe-skills repo with the full SKILL.md and references.

CLI reference

Install, authenticate, and use the pandaprobe CLI.

Tracing overview

The three layers of instrumentation the skill uses.

Evaluation

How metrics, scores, and monitors work.