Test Target Selector with Codex
Select the smallest honest verification set for a change, including targeted tests, manual checks, missing-test recommendations, a broader fallback, and named remaining risk.
- Choose targeted checks for a bugfix without overstating confidence.
- Map a feature or refactor diff to tests, smoke checks, and fallback commands.
- Identify missing tests for security-sensitive or contract-changing work.
Free
One-time purchase
See it in action
A real example of what this skill takes in and produces.
Sample input
This change touched password reset token handling and email link generation. Pick the smallest useful tests and what remains unverified.
Sample output
[Test Target Plan with change summary, change type, affected behavior, targeted checks, tests to add or update, manual smoke checks, broader fallback, unverified risks, confidence, and next instruction.]
Test Target Selector with Codex
Select the smallest honest verification set for a change, including targeted tests, manual checks, missing-test recommendations, a broader fallback, and named remaining risk.
Free
One-time purchase
Included in download
- Downloadable skill package
- Works with diff
- 2 permissions declared
- Instant install
See it in action
A real example of what this skill takes in and produces.
Sample input
This change touched password reset token handling and email link generation. Pick the smallest useful tests and what remains unverified.
Sample output
[Test Target Plan with change summary, change type, affected behavior, targeted checks, tests to add or update, manual smoke checks, broader fallback, unverified risks, confidence, and next instruction.]
About This Skill
What it does
The Test Target Selector provides a precise, honest verification strategy for code changes. Instead of running every test or guessing which ones matter, it analyzes your diff, classifies the change type (bug fix, refactor, API change, etc.), and selects the narrowest, most relevant tests to run first.
Why use this skill
AI agents often suffer from "false confidence," assuming a small fix is safe because a single unrelated test passed. This skill forces a rigorous evaluation of risk. It identifies what behaviors are actually affected, suggests specific manual smoke checks for things like UI or Auth, and—crucially—explicitly lists what remains unverified after the plan is executed. It transitions your agent from "guessing" to "verifying" with developer-grade precision.
Supported tools
This skill is optimized for Codex-driven development and is compatible with any local repository. It works by inspecting your file structure, CI configurations, and test suites (via Terminal and File Read access) to generate executable command patterns tailored to your specific environment.
Output
The output is a structured Test Target Plan. It includes a prioritized table of targeted test commands, recommendations for new tests that should be added, manual verification steps for high-risk flows, and a final confidence rating (Low/Medium/High).
Use Cases
- Choose targeted checks for a bugfix without overstating confidence.
- Map a feature or refactor diff to tests, smoke checks, and fallback commands.
- Identify missing tests for security-sensitive or contract-changing work.
- Create a verification plan before finishing a task.
Known Limitations
- "Does not run or implement tests unless paired with an execution skill and user/runtime permission."
- "Targeted checks cannot prove full-system safety."
- "Command recommendations are estimated when repository context is unavailable."
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/test-target-selector-with-codex | tar xz -C ~/.claude/skills/Free skills install directly. Paid skills require purchase - use the download button above after buying.
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Security Scanned
Passed automated security review
Permissions
File Scopes
This skill produces a verification plan only. It may inspect local repository structure and test command definitions, but it does not modify files, install dependencies, or claim that partial checks prove complete safety.
Optimized for Codex local repositories and CI-aware verification planning. The targeted-test selection method is model-agnostic. Requires enough repository, diff, or change-summary context to make honest recommendations.
Frequently Asked Questions
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