Start from the real job
Give the skill the files, repository, or context your work already uses; it begins by inspecting the actual situation.
Release candidate · v0.2.0
Measure and improve the quality of LLM applications with repeatable evaluations.
Measure and improve the quality of LLM applications with repeatable evaluations. Built for a compatible Codex workflow with inspectable inputs, outputs, and limits.
For operators and analysts who need defensible financial work who need to implement comprehensive evaluation strategies for llm applications using automated metrics, human feedback, and benchmarking.
AI Quality Evaluator
$49
one-time advanced kit. Includes the complete buyer package, version 0.2.0, and the update/support terms shown on this page.
Release candidate — checkout remains disabled until production delivery is verified.
The problem
When the work is consequential, a one-off prompt leaves too much to interpretation. AI Quality Evaluator turns implement comprehensive evaluation strategies for llm applications using automated metrics, human feedback, and benchmarking into a documented workflow with boundaries and a reviewable result.
Built for
For operators and analysts who need defensible financial work who need to implement comprehensive evaluation strategies for llm applications using automated metrics, human feedback, and benchmarking.
Campaign angle: AI Quality Evaluator: Measure and improve the quality of LLM applications with repeatable evaluations.
The mechanism
A repeatable path from request to verified result
See the decision path
Follow a documented sequence with explicit checks, boundaries, and a result you can review before acting.
Keep control at the edge
The package states what it cannot know, what remains human-owned, and which external costs or accounts are separate.
Test evidence
What the package has already proved
Passed structural, secret, safety-boundary, package-integrity, and adversarial-case checks as a release candidate.
Verified behaviors
- Handles a representative success case
- Stops when required input is missing
- Detects an incompatible environment
- Codex-native skill
- External tools, accounts, and usage costs are separate
Included
- Codex-native skill
- Attributed domain reference
- Combined installation and quick-start README
- Useful example request
Objection handling
Know the boundary before you buy.
Will the output be traceable?
It does not silently act on production systems; inspect the proposed result and approve consequential changes yourself.
Will it fit my source data?
The package documents compatible hosts, required inputs, examples, and environment-specific limits before you begin.
Can I review the assumptions?
Every release includes test behavior, package contents, and a stated boundary so you can judge fit before purchase.
Limitations and attribution
- External tools, accounts, and usage costs are separate
- Release candidate checkout is disabled
- Environment-specific behavior must be verified
Planned one-person or one-business internal-use license.
Adapted from wshobson/agents under MIT.
Release candidate
Put ai quality evaluator on a repeatable footing.
one-time advanced kit. Includes the complete buyer package, version 0.2.0, and the update/support terms shown on this page.
One-time price
$49
No subscription or product per-run fee. Host usage is separate.
Product FAQ
Know what you are buying
Is checkout available?
Not yet. This release candidate must complete production delivery verification before purchase is enabled.