Results for “skill-evaluation”

Guides users through creating, editing, and optimizing agent skills, including drafting, testing, evaluating, and improving skill performance.

Guides users through creating, refining, and evaluating agent skills, including drafting, testing, and optimizing descriptions for better triggering.

Guides users through creating, editing, and optimizing agent skills, including drafting, testing, evaluating, and improving skill descriptions for better triggering.

Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.

Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Skill Tester

Skill Tester

Validate skill outputs against assertion manifests to detect regressions, enforce quality gates, and bootstrap starter manifests from historical runs.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Analyzes development cycle and quality metrics to identify recurring issues, then generates additive patches to skill instructions to prevent them.

スキル定義（SKILL.md）を静的点検・ドライランで検証するスキル。 `--all` で全スキル一括健全性監査モード（ランキング＋修正案ドラフト生成）。 「スキルを点検して」「スキルをテストして」「スキルのバグ確認」「スキル検証」 「全部のスキルを点検して」「一括点検」または /skill-test を呼び出した時にトリガー。

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Validates, tests, and scores the quality of skills within a claude-skills ecosystem using Python scripts that check structure, syntax, runtime, and multi-dimensional quality metrics.

Algebra Based Estimation Skill

Update or correct an existing skill file based on judge feedback or improved understanding.

Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.

Coordinates quality assurance workflows by routing testing tasks to specialized sub-skills for API testing, performance benchmarking, test analysis, tool evaluation, and process optimization.

Automatically evaluates Claude Code sessions to extract reusable patterns and save them as learned skills.

Guides technical evaluation of code review feedback, emphasizing verification before implementation and reasoned pushback over performative agreement.

Use this skill when selecting a TPR-registered Training Provider for behind-the-wheel ELDT training. Covers the registry, evaluation criteria, and common pitfalls.

Use when assessing new ideas, technologies, or approaches before committing resources to them. This skill provides a framework for evaluating innovation opportunities systematically, separating genuine breakthroughs from hype.

Use this skill when selecting or replacing an ELD provider. Covers the FMCSA Registered ELD list, evaluation criteria, common provider removals from the registered list, and the 60-day transition rule.

Use this skill when referring a driver to SAP after a positive test or refusal. Covers SAP selection, the evaluation/treatment cycle, return-to-duty test, and follow-up testing schedule.

Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"

Legal-specific Argument Ranking Engine. Hodnotí právní argumenty 17-sloupcovým scoringem (síla, bezpečnost, dopad, riziko + 10 legal-specific kritérií: Compliance s novelou 2026, Evidence backing, Time-sensitivity, per-document mapping, R-static/R-reversal split, Tom-weight bonus, C-XX/M-XX/N-XX/D-XX integrace). Output: priorizovaný seznam argumentů s kategoriemi CORE/SUPPORT/CONTEXT/EXCLUDED/SUMMARY a per-document bundles (PR/§909/40_06/195). Použití: pre-prioritizace argumentů před F11.x review, Phase 2 Verify input, DÁVKA 3, výživné L04, AT podání. VŽDY použij tento skill, když Tom (nebo legal/strat) zmíní: /lare, lare, argument ranking, ARE matrix, score arguments, prioritize arguments, argument bundle, CORE/SUPPORT/CONTEXT/EXCLUDED, ARE_F11, LARE_F11, legal argument evaluation, argument scoring, compliance scoring, Tom-weight.

Score an unbuilt business idea on desirability, viability, feasibility, distribution wedge, why-now, founder-market-fit, market size, alternatives, defensibility, capital intensity, and regulatory/ethical risk — and return a GO / ITERATE / KILL verdict with kill criteria and a next kill test. Load when the user asks to evaluate a business idea, score a startup idea, screen an idea, decide whether to pursue this venture, do an idea review, or says "is this a good business idea", "should I build this", "evaluate this startup", "screen this idea", "go/no-go on this idea", "kill or pursue". Sub-skill of `venture-exploration`. Calls `fermi` for sizing, `assumption-mapping` for hidden beliefs, optional `pre-mortem` / `adversarial-hat` for high-stakes ideas. Does NOT evaluate built products — for that use `reality-check`.

Generate 5–10 business idea candidates from a blank page or a founder's domain context — using pain mining, jobs-to-be-done, trend × capability mapping, constraint relaxation, adjacency search, and founder-market-fit prompts. Each candidate is a structured idea card (segment, JTBD, current alternative, why-now, distribution wedge, monetisation, "feels like"). Load when the user asks to generate business ideas, brainstorm startup ideas, find ideas to work on, says "what business should I start", "give me startup ideas", "I don't know what to build", "ideate ventures", "blank-page idea generation", "find me a startup idea", "explore business opportunities". Sub-skill of `venture-exploration`. Hard-bans "Uber for X" / "AI for X" with no specific JTBD, "everyone" segments, and idea cards missing any of the 7 required fields. Does NOT design or evaluate ideas generated — for that use `idea-evaluation`.