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Conduct a project or sprint retrospective by gathering data from status reports and velocity metrics, structuring what went well and what needs improvement, and generating actionable improvement items with owners and due dates. Use at the end of a sprint, after a project phase or milestone, following a significant incident or success, at a quarterly review of ongoing processes, or before starting a similar project to capture lessons learned.

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MindStudio Profiler Analyze（msprof-analyze）是面向 AI 训练与推理场景的性能分析工具，基于采集得到的 profiling 数据进行统计、比对和诊断，帮助定位计算、通信、调度及集群场景下的性能瓶颈。

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当用户希望使用 msOpProf（`msprof op` / `msprof op simulator`）对昇腾 AI 算子做上板或仿真性能调优、解释 `aic-metrics`/`trace.json`/`visualize_data.bin`、选择 device vs simulator 路径、排查 `--soc-version`/`--export`/`signal 6`/`Bad address`/热点图或流水图相关问题，或要求生成固定分析报告模板（算子基本信息 / 关键数据 TOP5 / 核心瓶颈 TOP5 / 优化建议 TOP5）时，使用本技能。它负责先判定模式、输入形态与芯片/能力边界，再给出正确命令、结果解读、固定报告输出与高频踩坑规避；不要把经验案例当成通用规则。

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执行msProbe数据比对并分析比对结果，定位确定性计算问题首个输入一致输出不一致的API。

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面向 Ascend PyTorch Profiler / msprof DB（如 ascend_pytorch_profiler*.db、msprof_*.db）的 SQL 分析技能。将自然语言问题（算子耗时、通信、下发、调度、schema/table 查询）转为安全可执行 SQL，并按需从官方文档提取表结构详情。

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为 verl-omni 接入或修复 MSProbe 训推一致性采集，生成打点代码、样本关联日志和诊断启动脚本。 用于 diffusion/omni 的 rollout 与 actor 数据采集、dump 缺失或配对失败；不负责精度根因分析。

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Use this skill when writing sprint contracts in VCSDD strict mode. Provides grading criteria patterns, dimension weight guidelines, and pass threshold formulation for the 5 review dimensions.

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Plan sprints with capacity management, dependency checking, and priority-based story selection

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Analyze Kanban flow metrics to identify bottlenecks and improve team throughput. Covers Cycle Time, Throughput, WIP, and Flow Efficiency using Little's Law and Theory of Constraints. Use when a team wants to optimize delivery flow or improve predictability. Do not use for sprint-based Scrum planning — use sprint-planning-assistant instead.

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CSV/spreadsheet formula injection (DDE, Excel/LibreOffice, Google Sheets IMPORT*). Use when exports, imports, or user fields feed spreadsheets or reporting tools.

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Close out a completed EPIC / sprint end-to-end: author a fact-verified meta-post announcing what shipped, archive the EPIC's handovers, snapshot orchestrator memory, gate the integration→main merge on CI-green + explicit human go, drive the version bump (merge-commit conventions that auto-sync classifies), and verify the release reached the registry/PyPI. Use when the user says "close out EPIC <n>", "wrap up the sprint", "ship the meta shift", "/epic-close", or asks to finalize an integration branch that is ready to merge to main. Generalizes the EPIC 1002 (Yggdrasil II) close-out. This skill orchestrates — it authors founder docs directly (superadmin) and delegates code/regen to workers; it NEVER merges to main without the human gate.

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Designing CRISPR screens — library choice, pooled screen workflow, MOI, and hit validation.

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Marketing project management and execution excellence for B2B SaaS campaigns. Use this skill when coordinating multi-channel campaigns, allocating team resources, planning agile marketing sprints, running QBRs with clients, managing project timelines, balancing marketing workload, or implementing marketing operations scrum. Also triggers on: campaign coordination, resource allocation, agile marketing, sprint planning, client success, QBR, project timeline, marketing ops scrum, workload balancing.

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Generates a new sprint plan or updates an existing one based on the current milestone, completed work, and available capacity. Pulls context from production documents and design backlogs.

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Generate a QA test plan for a sprint or feature. Reads GDDs and story files, classifies stories by test type (Logic/Integration/Visual/UI), and produces a structured test plan covering automated tests required, manual test cases, smoke test scope, and playtest sign-off requirements. Run before sprint begins or when starting a major feature.

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Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.

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Unity New Input System correctness patterns. Catches common mistakes with action reading (triggered vs IsPressed vs WasPressedThisFrame), action map switching, rebinding persistence, InputValue lifetime, PassThrough vs Value, local multiplayer device assignment, and control scheme auto-switching. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.

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Use when a task needs the judgment of a Coating/Painting/Spraying Machine Operator — calculating wet film thickness from a target dry film thickness and the coating's percent volume solids, deciding whether flash-off time can be shortened to increase throughput, verifying cure by actual part temperature rather than oven setpoint, or tracing an adhesion failure back to surface prep rather than the coating application.

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Spring Boot 4 observability with Actuator, Micrometer, and OpenTelemetry. Use when configuring health indicators, health checks, custom metrics, distributed tracing, production endpoint exposure, Kubernetes probes, Cloud Run probes, logging, or monitoring. Covers Actuator endpoint security, Micrometer Timer/Counter/Gauge patterns, OpenTelemetry span customization, liveness/readiness probe setup, and metric tag best practices.

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Spring Boot 4 testing strategies and patterns. Use when writing unit tests, slice tests (@WebMvcTest, @DataJpaTest), integration tests, Testcontainers with @ServiceConnection, security testing (@WithMockUser, JWT), or Modulith event testing with Scenario API. Covers the critical @MockitoBean migration from @MockBean.

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Spring Boot 4 REST API implementation patterns. Use when creating REST controllers, REST endpoints, request validation, exception handlers with ProblemDetail (RFC 9457), API versioning, content negotiation, WebFlux reactive endpoints, HTTP clients with @HttpExchange, JSON serialization with Jackson 3, error handling, or CORS configuration. Covers @RestController patterns, Bean Validation 3.1, global error handling, and declarative HTTP clients.

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Run a focused tech debt reduction sprint — inventories all technical debt (TODOs, outdated deps, missing tests, god objects), fixes code smells, removes dead code, then hardens with a review pass. Use when a codebase feels sluggish, before a major feature push, or on a regular maintenance cadence.

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Synthesize sprint retrospective notes into categorized action items and patterns. Use this skill when: - You have sprint retro notes (raw text, meeting transcript, or structured notes) to process - You need to identify recurring patterns across multiple retros - You want categorized action items with owners and deadlines from retro discussions

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Build a velocity-based release roadmap with risk buffers. Use when the user says "release plan", "when will we ship", "plan the next release", "map sprints to milestones", "estimate our release date", "how many sprints until done", or wants to translate a backlog into a delivery timeline - even if they don't say "release planning". Based on "Agile Estimating and Planning" by Mike Cohn (velocity, story points, cone of uncertainty, risk buffers).

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