Results for “backlog-prioritization”

Rank a backlog of feature ideas by impact, effort, risk, and strategic alignment to identify the top 5 to pursue.

Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.

Prioritize product work with explicit criteria, scoring, tradeoffs, and decision rationale.

Identify, categorize, and prioritize technical debt into a ranked, defensible backlog that ties each remediation to impact and effort — a register, not a wish list.

Turns vague features, bug clusters, roadmap items, or launch work into an execution-ready planning packet by choosing the right packet type, separating discovery from delivery, and making blockers, dependencies, and the next move explicit.

Use this skill for queues, retries, idempotency, cron, dead-letter queues, background processing. Trigger when the task involves programming work related to Background Jobs Queues, implementation, audits, debugging, strategy, or validation.

Optimize MSBuild build parallelism by configuring /maxcpucount, graph build mode, project references, and analyzing binlogs to reduce multi-project solution build times.

Create a delivery plan with goals, capacity, scope, risks, and commitments.

Turns a pile of bugs, issues, and error reports into a ranked, actionable plan with reproduction evidence. Ingests GitHub issues via gh, TODO/FIXME scans, error logs, or a pasted list; attempts to reproduce or classify every item; scores by impact, frequency, fix cost, and regression risk; clusters duplicates; and.

You have 5 projects, each with a session. You open each one, paste "continue with next priorities", wait, switch, repeat. You're acting as a human cron job.

Plan backend domains, services, jobs, integrations, and failure handling for a product or major feature. Use when UX and product scope are defined and the team needs a production-minded backend design without defaulting to premature microservices.

Inngest expert for serverless-first background jobs, event-driven

Compress bloated project or global memory while preserving decisions, rationale, revisit triggers, provenance, and active user preferences. Load when memory exceeds budget, global memory is too large, session logs are repetitive, or before appending to an over-budget memory file.

Threat modeling workflow for software systems: scope, data flow diagrams, STRIDE analysis, risk scoring, and turning mitigations into backlog and tests. Use when designing new features, reviewing architecture changes, handling sensitive data, or hardening auth/payment/multi-tenant flows.

Plan a sprint by estimating team capacity, selecting and sequencing stories, and identifying risks.

Use this skill for pricing pages, onboarding, activation flows, plan comparison, product-led growth UX. Trigger when the task involves ui/ux work related to Pricing Onboarding UX, production implementation, audits, debugging, strategy, or validation.

Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications.

研究优先于编码的工作流程。在编写自定义代码之前，搜索现有的工具、库和模式。调用研究员代理。

Create, schedule, and verify database backups with support for full, incremental, and point-in-time recovery strategies. Use when the user requests database backup or provides relevant inputs for this workflow.

Scan, prioritize, and report technical debt. Usage: /tech-debt <scan|prioritize|report> [options]

Use this skill for feature flags, gradual rollout, kill switches, metrics, experiment gates, rollback. Trigger when the task involves programming work related to Feature Flag Rollout, implementation, audits, debugging, strategy, or validation.

Rank a topic's user-flow branches by proof priority (value × risk × frequency) right after user-flow-map, ordering the branches, gating variation breadth, and promoting or pruning flows so state-model and ux-variations grow the tree in proof order — writes only existing flow-tree ordering fields, no schema change.

PR Fleet

Layer 6 of the keyword research pipeline. Organizes the vetted keyword queue into money clusters (from clusters.md), picks each cluster's keystone vs supporting articles, tracks coverage, and PROPOSES new clusters from high-business-value topics or live products not yet covered — so the blog strategy expands as the company grows. Emits cluster-tagged queue + cluster-map.md + cluster-proposals.md.

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

Package a customer escalation for engineering, product, or leadership as a decision-ready handoff — impact, timeline, facts vs. hypotheses, and a specific ask with an owner.

当需要进入并维持高度专注的深度工作状态时

当需要在多个领域积累独特竞争优势，避免单一技能风险时

Rank the top-5 leads worth calling today with tailored, history-grounded talking points and proposed calendar blocks — no auto-send.

Use this when the system needs queue-backed processing design, message handling rules, delivery semantics, dead-letter strategy, or throughput planning. Trigger on requests about queues, brokers, message processing, and consumer coordination.

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Visualize the user journey by creating a hierarchical map of activities, steps, and tasks to build shared understanding and prioritize features.

Optimize a complete candidate context package by deduplicating, filtering, ordering, and allocating its token budget. Use when retrieved or assembled material is noisy or exceeds the useful context budget; use context-ranking for scoring chunks and context-compression for shrinking selected content.