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Dspy Debugging Observability

Listed
omidzamani·vlatest·testing·MIT

Provides detailed logs, metrics, and visualizations to diagnose and improve dspy test suite performance and accuracy.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add omidzamani/dspy-skills --skill dspy-debugging-observability -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

omidzamani

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: 20.102.90.50.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    20.102.90.50undeclared

    What it found

    • skills/dspy-debugging-observability/SKILL.md:100contacts 20.102.90.50
      rm = dspy.ColBERTv2(url="http://20.102.90.50:2017/wiki17_abstracts")

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned omidzamani/dspy-skills at f5db3b7b1f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
f5db3b7b1f
Manifest
skills/dspy-debugging-observability/SKILL.md
Scanned
2 files, 261 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The dspy-debugging-observability skill provides tools for inspecting and understanding the internal state of AI agents during execution. It allows you to view intermediate steps, track variable values, and identify potential bottlenecks or errors within complex agent workflows. This capability is crucial for diagnosing issues and improving agent performance.

When to use it

  • Troubleshooting unexpected behavior: When an agent isn't producing the desired results, this skill helps pinpoint where things are going wrong.
  • Understanding complex reasoning chains: For agents with multiple tools or steps, observe the decision-making process at each stage.
  • Optimizing performance: Identify slow operations or redundant actions that can be streamlined to improve overall agent speed.
  • Debugging tool usage: Track how and why an agent is selecting specific tools within its environment.

Key capabilities

  • Inspect intermediate states of the agent's execution.
  • Track variable values throughout the workflow.
  • Identify bottlenecks in the agent’s reasoning process.
  • Provides observability into tool selection decisions.

Example prompts

  • "Show me the internal state after each step."
  • "What was the value of 'search_results' before calling the email tool?"
  • "Explain why the agent chose to use the calculator tool in this situation."

Tips & gotchas

This skill requires a suitable environment that supports observability features. Ensure your agent framework is configured to expose internal state information for debugging purposes.