Skip to main content

Local Codex plugin for iterative Agent tuning with guided Skills, reusable runner templates, versioned results, and static validation.

Project description

Agent Tune Kit

English | 简体中文

PyPI

Agent Tune Kit is a local Codex plugin for evaluating and tuning your own local Agent.

If you already have a working Agent but do not know where it fails, why it fails, or what to change next, Agent Tune Kit helps you run the full loop: batch test the Agent, find failure cases, generate a report, let Codex tune the Agent, and verify the next run.

Architecture

Agent Tune Kit architecture

Who It Is For

Use it if you have:

  • A local Agent, chatbot, tool-using Agent, or RAG Agent.
  • A small evaluation dataset, preferably CSV; 5 to 20 rows are enough to start.
  • Inputs, expected answers, or human-checkable results.
  • A desire to let Codex help locate weak spots and tune prompts, code, parameters, or tool configuration.

Prerequisites

You need:

  • A local Agent project that Codex can inspect and edit.
  • An evaluation dataset, preferably in CSV format. Column names do not need to follow a strict schema; Codex will infer inputs and expected results where possible.

Install

One-command install:

uvx --from agent-tune-kit atk install

To keep the atk command available:

uv tool install agent-tune-kit
atk install

Or use pipx:

pipx install agent-tune-kit
atk install

After installation, open the plugin list in Codex:

/plugins

Select and enable Agent Tune Kit. If $atk-status and other completions do not appear immediately after enabling, restart Codex or reopen the current project session.

Minimal Tuning Loop

Run these commands in your Agent project, not in this repository.

1. Initialize

Tell Codex where your Agent starts and where the evaluation data lives:

$atk-init My Agent entrypoint is scripts/agent.py and the evaluation dataset is data/eval.csv

Codex generates:

.atk/runner/eval_runner.py

2. Run Evaluation

$atk-run

Results are written to:

.atk/results/v1/eval_results.csv

3. Find Failures

Let Codex judge which rows failed:

$atk-find-failures

If you already have a clear rule, create the rule script first and then apply it:

$atk-init-failure-rule rule: mark a row as failed when expected differs from agent_output
$atk-find-failures-by-rule

Failure cases are written to:

.atk/results/v1/failure_cases.csv

4. Generate Report

$atk-report

The report is written to:

.atk/results/v1/report.md

It summarizes results, failure cases, likely causes, and recommended tuning priorities.

5. Optional: Browse Failures

$atk-visualize-failures

This creates a local HTML page:

.atk/results/v1/failure_cases.html

Use it to search, filter, and manually review failure cases.

6. Let Codex Tune the Agent

$atk-tune

Codex edits your Agent based on the report and records the tuning plan:

.atk/results/v1/tuning_plan.md

Verify Improvement

After tuning, run another loop:

$atk-run --only-failures
$atk-find-failures
$atk-report

New results are written to .atk/results/v2/. --only-failures maps the prior failure_cases.csv back to .atk/datasets/original.csv by atk_id and reruns only those rows. Starting with the second loop, the report compares against the previous tuning_plan.md and tells you whether the target issues were resolved, partially resolved, unresolved, or impossible to judge.

Output Structure

.atk/
├── datasets/
│   └── original.csv        # ATK runnable dataset with atk_id
├── runner/
│   ├── eval_runner.py
│   └── failure_rule.py
└── results/
    ├── v1/
    │   ├── eval_results.csv
    │   ├── failure_cases.csv
    │   ├── failure_cases.html
    │   ├── report.md
    │   └── tuning_plan.md
    └── v2/
        └── ...

Common output files:

  • eval_results.csv: actual Agent output for each row.
  • failure_cases.csv: rows selected as failures.
  • failure_cases.html: optional failure review page.
  • report.md: analysis and tuning recommendations.
  • tuning_plan.md: what Codex changed and why.

Common Skills

  • $atk-status: inspect progress and suggest the next step.
  • $atk-init: generate the test runner.
  • $atk-run: run evaluation and create a new result version.
  • $atk-find-failures: let Codex identify failure cases.
  • $atk-init-failure-rule: create or update the failure rule.
  • $atk-find-failures-by-rule: apply the rule to identify failures.
  • $atk-report: generate analysis and cross-loop validation.
  • $atk-visualize-failures: generate the failure review HTML page.
  • $atk-tune: tune the Agent based on the report.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agent_tune_kit-0.3.9.tar.gz (3.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agent_tune_kit-0.3.9-py3-none-any.whl (3.1 MB view details)

Uploaded Python 3

File details

Details for the file agent_tune_kit-0.3.9.tar.gz.

File metadata

  • Download URL: agent_tune_kit-0.3.9.tar.gz
  • Upload date:
  • Size: 3.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.16 {"installer":{"name":"uv","version":"0.11.16","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for agent_tune_kit-0.3.9.tar.gz
Algorithm Hash digest
SHA256 5a16d987f1979e4a023bc680d625927d2bf502a7c5545c20dbdcfec8f0b0140b
MD5 15a60520f6c02c0944dd137a42b146b6
BLAKE2b-256 8a8d2baeacf1ccc979da5edf9313650a794e43e07d745f730016e4a212089516

See more details on using hashes here.

File details

Details for the file agent_tune_kit-0.3.9-py3-none-any.whl.

File metadata

  • Download URL: agent_tune_kit-0.3.9-py3-none-any.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.16 {"installer":{"name":"uv","version":"0.11.16","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for agent_tune_kit-0.3.9-py3-none-any.whl
Algorithm Hash digest
SHA256 4926b7e24a8fbb265143018831354ae7c09b6b5ec9cc3150e30d188b3de821b1
MD5 0ef40d3bc95a71e9bfa3beef97a71168
BLAKE2b-256 1aef30ee529a33c537385fcae1975014a16c1b2ee6ffae85a4f8cee6ce5c69fa

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page