Results for “team-analysis”

Derives a comprehensive test plan from user stories and acceptance criteria, then writes unit, integration, and end-to-end test cases. Flags issues in prior artifacts and declares UAT readiness.

Derives a comprehensive test plan and writes unit, integration, and end-to-end test cases from user stories and acceptance criteria, flagging issues in prior artifacts and declaring UAT readiness.

Design and evolve engineering team structures for fast flow of change using the Team Topologies framework, including Conway's law, four team types, three interaction modes, and cognitive load management.

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

Plans sprints, breaks user stories into tasks, and estimates story points from BA and TechLead artifacts, producing sprint plan, task breakdown, and story point files.

Reviews all pipeline artifacts from a virtual software team and produces quality, compliance, and sign-off reports with an advisory release verdict.

Performs a comprehensive cross-artifact QA/QC review of a virtual team pipeline, checking completeness, consistency, security, and compliance, then issues an advisory verdict with quality, compliance, and sign-off reports.

Design and apply QA methodology for software teams: test strategy, regression testing, CI failure triage, test automation, quality gates and metrics, risk-based testing, exploratory testing, test design techniques, AI code quality gates (independent verification, acceptance-criteria testability review for agentic Spec-Driven Development), mutation-guided test hardening and review evidence (surviving mutants, weak assertions, diff-aware mutation testing), agentic eval design (dataset test design, judge-as-system-under-test, flaky-eval discipline), QA career levels (Senior/Staff/Principal), and SDET engineering (test infrastructure, gTAA, CI/CD integration). Do not use for root-cause debugging of production incidents, security implementation or threat modeling, or evaluation framework governance and statistical analysis — route those to systematic-debugging, secure-software-engineering, and agent-evals-and-observability respectively.