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Agent Tuning

Checked
onesmartguy·vlatest·agents

Refine agent behavior through iterative feedback loops, optimizing performance based on your specified goals and metrics.

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 onesmartguy/next-level-real-estate --skill agent-tuning -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

onesmartguy

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 onesmartguy/next-level-real-estate at b8266e8105.

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

Commit
b8266e8105
Manifest
.claude/skills/agent-tuning/SKILL.md
Scanned
1 file, 589 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

This skill allows you to fine-tune the behavior of AI agents. It provides a mechanism for adjusting agent responses and actions based on specific instructions or examples, improving their performance in targeted scenarios. The goal is to make agents more reliable and aligned with desired outcomes through iterative adjustments.

When to use it

  • Improving response quality: When an agent consistently gives inaccurate or unhelpful answers.
  • Refining task execution: If an agent struggles to complete a specific task correctly, tuning can guide its actions.
  • Adjusting tone and style: To modify the way an agent communicates (e.g., more formal, friendly, concise).
  • Correcting biases or errors: When an agent exhibits undesirable behavior or makes systematic mistakes.

Key capabilities

  • Response adjustment based on provided examples
  • Action refinement through iterative feedback loops
  • Tone and style modification
  • Error correction and bias mitigation

Example prompts

  • "Tune the agent to respond with more concise answers."
  • "Provide an example of a good response for this query: [user query]"
  • "Correct the agent's tendency to hallucinate information when asked about [topic]."

Tips & gotchas

The effectiveness of agent tuning depends on providing clear and specific feedback. Start with small adjustments and carefully monitor the results to avoid unintended consequences.