eval-harness
by affaan-mThe eval-harness skill is a formal evaluation framework for Claude Code sessions and eval-driven development. It helps you define pass/fail criteria, build capability and regression evals, and measure agent reliability before shipping prompt or workflow changes.
This skill scores 78/100, which means it is a solid directory candidate with real workflow value for agents doing eval-driven development. Users should be able to trigger it and understand its purpose quickly, though they should expect a mostly documentation-driven skill rather than one backed by helper scripts or bundled references.
- Clear activation use cases for EDD setup, pass/fail criteria, regression evals, and benchmarking
- Substantial operational content with structured eval and grader templates plus multiple workflow sections
- Strong triggerability from the frontmatter and explicit 'When to Activate' guidance, making install intent easy to judge
- No install command, scripts, or support files, so adoption depends on reading and applying the markdown guidance manually
- No references/resources/tests bundled, which limits trust signals for users who want a turnkey evaluation harness
Overview of eval-harness skill
What eval-harness does
The eval-harness skill is a formal evaluation framework for Claude Code sessions and eval-driven development. It helps you define what “good” looks like before you ship, then measure whether an agent, prompt, or workflow actually meets that bar.
Who should use it
Use the eval-harness skill if you need repeatable checks for AI-assisted coding, prompt changes, or agent behavior. It is especially useful for teams comparing model versions, tracking regressions, or turning vague task expectations into pass/fail criteria.
Why it matters
The main value of eval-harness for Model Evaluation is reliability: instead of judging outcomes by feel, you write evals that expose when behavior changes. That makes it easier to debug agent performance, compare runs, and avoid shipping prompt updates that silently degrade quality.
When it is a good fit
It fits best when the task can be expressed as observable success criteria, output structure, or checkpointed behavior. It is less useful for open-ended creative work unless you can still define measurable acceptance conditions.
How to Use eval-harness skill
Install and activate
For eval-harness install, use the repo’s skill install flow in your Claude Code environment, then open the skill file directly. The skill lives at skills/eval-harness/SKILL.md, and that is the first file to read because it defines when to activate the framework and how to structure evals.
Build a prompt the skill can evaluate
For strong eval-harness usage, do not start with “test my agent.” Start with a concrete target, such as: what task the agent must complete, what counts as success, what failure looks like, and whether you are checking capability or regression. A better input looks like: “Evaluate whether the agent can update a React form without breaking validation, and require three explicit success criteria.” That gives the harness something measurable.
Read the right files first
If you are adopting the eval-harness guide approach inside your own workflow, read SKILL.md first, then inspect any repository notes that describe evaluation style, grading logic, or output conventions. In this repo, there are no helper scripts or extra support folders, so the skill file itself is the source of truth.
Use it in a practical workflow
A good workflow is: define the behavior, write one eval for the happy path, add one regression eval for a known failure, then run the harness and refine the criteria. This keeps evals small enough to debug and reduces the chance of writing tests that are too broad to interpret.
eval-harness skill FAQ
Is eval-harness only for Claude Code?
No. The skill is written around Claude Code sessions, but the underlying method is useful anywhere you need structured agent evaluation. If your stack uses different tools, you can still adapt the eval format and grading logic.
Is eval-harness the same as a normal prompt?
No. A normal prompt asks for an answer; eval-harness asks for a repeatable way to judge answers. That distinction matters when you need consistency across versions, not just a single good response.
Is it beginner-friendly?
Yes, if you can describe a task clearly. The harder part is not the syntax; it is writing good success criteria. Beginners usually do well when they start with one simple capability eval instead of trying to model an entire workflow at once.
When should I not use it?
Skip eval-harness if the work is highly subjective, if the output cannot be checked consistently, or if you only need a one-off answer. It is strongest when reliability, regression tracking, or model comparison is the real goal.
How to Improve eval-harness skill
Make criteria observable
The biggest quality gain comes from turning opinions into checks. Replace “make it better” with conditions like “preserve existing API shape,” “return valid JSON,” or “pass all three regression cases.” The more observable the criteria, the easier eval-harness becomes to run and trust.
Separate capability from regression
If you mix new-feature checks with old-behavior checks, failures become hard to interpret. Keep capability evals focused on whether Claude can do something new, and regression evals focused on whether a known baseline still holds.
Give the harness real edge cases
Stronger evals include failure modes, not just happy paths. Add tricky inputs, incomplete context, or ambiguous instructions so the eval-harness skill can reveal whether the agent is robust or merely lucky on clean examples.
Iterate after the first run
Treat the first run as calibration, not proof. If the result is unclear, tighten the success criteria, add a baseline, or split one broad eval into smaller checks. That is usually the fastest way to improve eval-harness usage and get results you can act on.