Results for “job-evaluation”

Identify and analyze 3-5 distinct customer segments with demographics, jobs-to-be-done, pain points, and product fit analysis for market opportunity evaluation.

Analyze customer needs by identifying the 'job' they hire a product to do, covering job statements, forces of progress, and competitive landscapes.

Draft performance reviews, self-assessments, peer reviews, and upward feedback in your own voice using WorkIQ to surface actual contributions and structure them into impact-focused writing.

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.

Reviews resumes for formatting, design, content, and job-specific fit; scores job postings for fit and interview odds; develops rubrics; extracts content from conversations; and audits the resume generation pipeline.

Loop feature-interviews over a brainstorm idea set and consolidate survivors into the roadmap

research-synthesis

Frame jobs, triggers, desired outcomes, anxieties, and product opportunities.

Map user Jobs-to-Be-Done with functional, emotional, and social dimensions plus outcome expectations to reframe product decisions around user motivations.

Runs regression evaluations comparing agent edits against human-approved golden projects, and registers new goldens after human approval.

Assists with job applications: evaluating job postings, tailoring CVs, writing cover letters, and preparing for interviews. Triggers on keywords like: job posting, job application, CV, cover letter, resume, interview prep, job fit, career, application, apply, ansøgning, stilling

Evaluate everything the PA agent manages — tasks, skills, PA network health, billing, calendar connections, and memory quality. Use when: owner asks for an evaluation, wants to know what's working and what isn't, or requests a performance report. Combines supervisor status with quality scoring.

Review designs, products, and features using Steve Jobs' standards of ruthless simplicity, focus, and end-to-end excellence.

基于 Modular RAG MCP Server 项目生成定制化简历项目经历。结合项目技术亮点与用户业务场景，按简历编写原则输出高质量项目描述（中英文）。Use when user says '写简历', 'resume', '简历', 'write resume', '项目经历', 'project experience', '简历项目', or asks to generate resume content based on this project.

基于 Modular RAG MCP Server 项目生成定制化简历项目经历。结合项目技术亮点与用户业务场景，按简历编写原则输出高质量项目描述（中英文）。Use when user says '写简历', 'resume', '简历', 'write resume', '项目经历', 'project experience', '简历项目', or asks to generate resume content based on this project.

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, automated anti-pattern detection, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

Expert technology assessment specialist focused on evaluating, testing, and recommending tools, software, and platforms for business use and productivity optimization

Benchmarks LLM bias by scoring responses to automatically generated open-ended questions across sensitive attributes, producing a composite fitness score from 0 to 5.

Uncover customer jobs, pains, and gains in a structured JTBD format to clarify unmet needs, reposition products, or improve discovery and messaging.

Use when making a forward-looking claim with a checkable outcome (reply within 24h, error rate will drop, this skill will see more use) — record to state/predictions.jsonl with a review horizon so reflection can grade you later. Closes the in-the-moment double-loop.

Eng manager-mode plan review. (gstack)

Produces an evidence-backed inventory of live automations (jobs, hooks, connectors, MCP servers, wrappers) and recommends keep/merge/cut/fix-next actions before rewriting anything.

Validate process decomposition and architecture design quality before execution begins. Load when the setup-evaluator agent fires (automatic for agent-chain tasks), or when user says "evaluate this setup", "check the decomposition", "validate the architecture", "is this plan sound", "review the agent design". Catches structural errors, missing knowledge, unrealistic step ordering, and topology mismatches. Does NOT modify — only evaluates.

Evaluate model quality with task-appropriate metrics and systematic error analysis. Use when: (1) comparing models, (2) analyzing failures, (3) setting go/no-go thresholds. NOT for: production monitoring implementation.

Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing product value propositions. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint.

Design and implement evaluation harnesses for models, agents, and code. Use when creating benchmarks, designing eval metrics, or comparing system outputs.

Synthesize personas and jobs-to-be-done from evidence with confidence levels. Use when: (1) audience segmentation, (2) messaging alignment, (3) feature prioritization inputs. NOT for: stereotype-based profiling.

从思想性、艺术性、观赏性三维度评估影视剧本并打分。适用于剧本开发质量评估、修改方向确定、项目立项前审查

针对 Modular RAG MCP Server 项目的模拟技术面试 Agent。读取用户简历（可选），围绕三个方向进行最多 3 轮深度追问，结束后生成并持久化面试报告（含参考答案、包装识别点评、评分）。Use when user says '模拟面试', '面试练习', '帮我面试', 'mock interview', 'interview practice', '面试', '考我', '开始面试', or wants to practice interviewing about this project.

Create a role interview kit with role outcomes, interview plan, scorecard, evidence prompts, and evaluation criteria.