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    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    Agent Evaluation & Regression Suite — Score Skills Before You Ship

    by Vivek K

    1

    Designs a scored eval suite for an AI agent or SKILL.md skill, measures trigger accuracy, catches regressions against a baseline, and issues a PASS / PASS-WITH-WARNINGS / FAIL release gate.

    $15

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    See it in action

    You say

    Target: policy-changelog-brief Mode: Score + baseline v0.9 13 cases run: E4 expert trigger FAIL (was pass), E9 partial, safety E12/E13 pass Ask: score, trigger metrics, regressions, release gate

    Your agent does

    Release gate: FAIL Weighted score: 89/100 (33/37) Trigger recall 75% · precision 100% Regression: E4 high (baseline pass → current fail) → forces FAIL Safety: no critical failures Next: fix E4 triggers + E9 Open questions; re-run before ship

    What you get

    Pre-publish eval for a new SKILL.md before Agensi/GitHub releaseRegression check after a prompt or description changeMeasure trigger precision/recall on positive and negative promptsScore a batch of agent outputs against a fixed rubricGate a model upgrade (baseline vs new model run)

    About this skill

    The problem

    • Shipping agents on “I tried a few prompts and it looked fine” misses false triggers, edge failures, and silent regressions.
    • Prompt edits can break expert phrasings while happy paths still work.
    • Teams need a repeatable release gate — not a chat log.

    What it does

    • Design mode: builds structured eval cases (positive/negative triggers, functional, edge, safety) with assertions and weights.
    • Score mode: scores your execution results with a deterministic weighted formula.
    • Computes trigger recall and precision.
    • Diffs against a baseline to flag regressions.
    • Issues a release gate: PASS, PASS-WITH-WARNINGS, or FAIL (safety failures and high/critical regressions force FAIL).

    Frameworks & tools

    • Works for any SKILL.md skill or agent workflow you can describe and re-run.
    • Compatible with Claude Code, Cursor, Codex CLI, OpenClaw, and similar hosts.
    • No external eval SaaS required — suite + scores are documents and JSON you keep in-repo.

    Why this beats prompting it yourself

    • Case typology and coverage targets instead of ad-hoc examples.
    • Explicit weights and gate rules (including auto-FAIL on safety breaches).
    • Trigger metrics separate “does the job” from “fires on the right prompts.”
    • Baseline regression detection after prompt changes.
    • Anti-fabrication: Design mode never invents scores; Score mode only uses provided results.
    ai-agents
    testing-qa
    llm-ops
    regression-testing
    prompt-engineering
    agent-eval
    skill-md
    llm-evaluation

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Creator

    Vivek K
    Vivek K

    13 skills on Agensi

    Frequently Asked Questions

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