Results for “assessment”

Honestly evaluate AI work quality using a two-axis scoring system with mandatory devil's advocate reasoning and cross-session anti-inflation detection.

Rates an agent's own output on five axes — accuracy, completeness, clarity, actionability, conciseness — producing a structured scorecard with evidence and improvement suggestions.

Performs a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.

Structures immediate next steps into a dependency-ordered plan, gated by the current action_gate mode, with checkpoints and risk flags before execution.

Evaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".

Audits decisions and situations for operating psychological biases using Munger's 25 tendencies framework, producing a structured analysis with countermeasures.

Guides the user through German summary proceedings (Mahnverfahren) under §§ 688 ff. ZPO, checking deadlines, form, jurisdiction, and legal remedies, and providing a deadline and risk assessment with immediate steps.

Identify, test, deploy, and verify software updates across an organization's IT infrastructure using a structured patch management workflow with phased rollouts and automated assessment.

Analyze draft prompts to identify intent, scope, and missing context, then generate an optimized prompt with ECC component recommendations. Advisory only — never executes the task.

Use when designing a course, assessment, or student-feedback workflow and deciding where AI assistance is acceptable, when grading or feedback must stay within academic-integrity and FERPA/KVKK boundaries, or when AI-use rules for students need stating.

Implement bounded remaining work for an issue-driven repository change after an authoritative verifier reports concrete gaps. Use when a workflow supplies an issue brief or assessment plus materialized gate-result and remaining-work evidence, and the existing candidate must be corrected without creating a MoonSpec feature packet.

Propose specific, actionable test cases for a target module — without writing the actual test code. Use this skill whenever the user wants to know "what should I test", "what test cases would catch real bugs in X", "I have a finding from test-assessment, what tests would close that gap", "suggest tests for this file", or wants to think through coverage before writing. Pairs with the test-assessment skill (which finds gaps); writing the test code itself happens as a normal follow-up task once the suggestions are reviewed. This skill stops at suggestions — if the user wants code generated, redirect them. Trigger even on casual phrasings ("what should I test in auth.ts", "give me test ideas for this module").