'planner' 검색 결과

dev-graph artifact を正規 path へ atomic 追加・差分更新したいとき、system-dev-planner の exact 13 phase task package を all-or-none 登録したいときに使う。

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大きな自然文構想を feature・architecture・機能間依存へマクロ分解したいとき、ready feature の system-dev-planner package を atomic 登録・binding 別投影したいときに使う。

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Use when the user asks to "keep the launch momentum going after launch week", "plan a changelog / release-notes cadence as GTM", or "is this update worth a relaunch"; produces a T+1→T+30 momentum plan — a launch-moment calendar (milestone / shipped-loop / badge moments only), announcement-tier routing (major = full-channel, medium = targeted, minor = changelog-only), a relaunch legitimacy call, spike-to-owned handoff briefs, and the next Tier-1 moment with launch-stacking spacing. Not for the 30-day content-reuse map or paid amplification execution — use content-amplifier; not for planning the next launch end to end — use launch-tier-planner. 抗第二周断崖/changelog-as-GTM/relaunch/下一发布时刻

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Use when the user asks to "plan an influencer campaign", "build a campaign blueprint", or "launch a product with creators"; produces campaign objectives, platform and influencer-tier strategy, content requirements, a phased timeline, budget allocation, and KPI targets. Not for writing individual creator briefs — use brief-generator; not for the overall product-launch plan (tiering, calendar, press, community day) — use launch-tier-planner, which hands this skill the creator lane. A launch request that does not mention creators routes to the launch discipline, not here. 达人营销策划/种草方案

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Use when the user asks to "launch on Product Hunt / Hacker News", "prepare community or directory launch submissions", or "plan the launch submission waves"; produces per-platform submission packages — a Product Hunt tagline / gallery / first-comment skeleton, a factual Show HN title and text, per-subreddit posts with a self-promotion rules table, tiered directory waves, and a regional channel matrix including Chinese communities — plus a platform red-line check (never solicit votes or organize voting rings) and T-0 submission-status lines for the launch registry. Not for paid amplification — use content-amplifier; not for creator channels — use campaign-planner; not for launch telemetry readouts — use launch-monitor; not for ongoing community presence or pre-launch karma-building outside the launch window — use participation-warmup-planner. 社区发布/PH提交包/Show HN/目录波次/平台红线/中文渠道

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Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.

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planner エージェントによるタスク分解。design.md を基に TaskCreate でネイティブタスクに登録。「タスクに分解して」「タスク分解して」「実装計画を立てて」「何から始める？」で発動。

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Use when: planner mode, planning mode, proposal, scope definition, estimate, timeline, how hard, feasibility, effort, how long, how big, client message, external communication, pricing, delivery confidence, commercial risk, or project delivery planning.

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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types. Use when creating agents in source control, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship'. NOT for Apex-based agent actions (use custom-agent-actions-apex). NOT for UI-based agent creation (use agentforce-agent-creation).

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Build production-grade AI agents from scratch using patterns inspired by production-grade agentic systems like Claude Code. Covers two audiences — (1) workflow builders who need planner+executor pipelines, human-in-the-loop checkpoints, and multi-agent orchestration, and (2) application embedders who need HTTP/SSE APIs, multi-user session management, and React frontend integration. Use when asked to build an AI agent, create a coding assistant, embed an agent in an app, build an API agent, clone Claude Code, build a CLI agent, design an agent architecture, scaffold an agentic system, or automate a multi-step workflow. Triggers on keywords like agent builder, agent blueprint, coding assistant, CLI agent, agentic tool, claude code clone, agent scaffold, agent architecture, workflow automation, multi-agent, planner executor, SSE streaming, agent API.

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Experiment with the policies that govern an AI agent, such as planning, memory, and tool use. Test one policy change per variant in a sandbox, an isolated environment, and promote only candidates with measured improvements.

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• Finding policy changes that improve low evaluation scores
• Exploring initial agent settings for a new domain
• Comparing manual tuning with an evolved baseline

Uses multiple agents with different critical roles to challenge assumptions, complexity, risks, and alternatives. Findings that withstand review go to a dedicated planner, who turns them into sequenced tasks with explicit success criteria.

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• Reviewing assumptions before implementation
• Checking integration risks and edge cases
• Comparing alternative approaches

Plan and build a connected series of lessons around learners’ experience and goals. After the user approves the complete lesson list, it creates lessons in order, checks continuity, and organizes them in one folder.

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• Building a seven-day introductory Python course
• Creating a four-week onboarding program
• Turning book chapters into separate lessons

Design and build an OpenMAIC lesson series using a spiral curriculum: core ideas return with deeper explanations, new representations, and unfamiliar applications. It maps conceptual growth across lessons and checks that revisits add understanding.

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• Designing a Bruner-style spiral curriculum
• Moving from concrete examples to general models across lessons
• Revisiting concepts through unfamiliar applications and counterexamples

Turn an understood task into an ordered implementation plan in Codewhale. Clarify the goal and constraints, identify which steps depend on others, and record verification methods, risks, and open questions before broader implementation begins.

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• Planning implementation for a clearly defined task
• Ordering steps that depend on one another
• Adding verification to risky steps

Turns vague development requests into reviewed plans through planning, architecture, and quality-review agents. It compares alternatives, defines testable acceptance criteria, and records decisions, stopping before implementation unless execution has been explicitly approved.

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• Defining the scope of a vague development request
• Comparing implementation approaches before coding
• Planning migrations or security-sensitive changes

Configure tools and skills for sub-agents before dispatching development tasks. Role presets cover implementation, planning, reviews, testing, and verification, with defined boundaries for what each agent should do and whether it may modify files.

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• Setting tool permissions before spawning a sub-agent
• Separating implementation, planning, and review roles
• Configuring agents for review without file changes

Add Codex as the agent that plans tasks and coordinates tools in NanoClaw. Choose it for individual groups alongside Claude, with conversation history and session resume using a ChatGPT subscription or OpenAI API key.

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• Adding Codex as a NanoClaw agent provider
• Choosing Claude or Codex for each group
• Setting up ChatGPT or API key authentication

Use sales history and current stock to estimate stockout dates, reorder timing, quantities, and costs. Identify cash tied up in slow-moving inventory, and prepare purchase order and supplier email drafts for approval.

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• Deciding what to reorder this month
• Checking whether stock will last until delivery
• Finding cash tied up in slow-moving stock

Turns sales and stock data into a reorder plan with quantities, costs, and estimated stockout dates. Prepares supplier purchase orders, email drafts, and accounting memos for later invoice checks, while flagging slow stock and requiring approval before sending.

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• Estimate stockout dates and reorder quantities
• Prepare purchase orders and supplier email drafts
• Keep accounting memos for future invoice checks

Design interview processes for specific roles and experience levels, with round objectives, timing, suggested questions, and scoring criteria. Help interviewers align their judgments and review potential bias before using the process.

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• Designing interview rounds for a specific role
• Preparing questions for each interview round
• Aligning scoring criteria across interviewers

Plan, review, and retire feature flags, switches that control feature availability. Includes tools to identify aging flags, generate phased release schedules, and check that documentation records ownership and emergency shutdown procedures.

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• Plan a phased release for a new feature
• Identify old flags for cleanup
• Audit emergency shutdown documentation

Scope a Claude Managed Agent through six questions about its job, trigger, inputs, actions, success criteria, and recurrence. Produce a validated build sheet with configuration components, deferred features, and an evaluation plan, without requiring an API key.

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• Turn an agent idea into a concrete build plan
• Define success criteria before implementation
• Separate the initial scope from later integrations

Route internal operations questions to six specialist skills covering workflows, vendors, staffing capacity, communications, procedures, and procurement. Receive a brief summary of findings, recommended actions, and links to the documents or data files produced.

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• Finding bottlenecks in internal workflows
• Reviewing vendor performance and purchasing costs
• Planning staffing capacity for the next quarter