「context-engineering」の検索結果

Comprehensive guide for skill development based on Anthropic's official best practices - use for complex skills requiring detailed structure

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Analyze a GitHub issue and create a detailed technical specification

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Evaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.

日本語の概要は準備中です。原文の説明を表示しています。

Reconcile the project's FPF state with recent repository changes

日本語の概要は準備中です。原文の説明を表示しています。

Manage evidence freshness by identifying stale decisions and providing governance actions

日本語の概要は準備中です。原文の説明を表示しています。

Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation

日本語の概要は準備中です。原文の説明を表示しています。

Implement a task step by step with automated LLM-as-Judge verification at the end of each phase

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Use when found gap or repetative issue, that produced by you or implemenataion agent. Esentially use it each time when you say "You absolutly right, I should have done it differently." -> need create rule for this issue so it not appears again.

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Review what an LLM feature or agent actually puts in its context window — and find what's bloating, missing, or fighting itself. Use when asked to review a system prompt and context assembly, cut token usage without losing quality, debug an agent that ignores instructions, or audit how retrieval results, history, and tool definitions are packed into the window. Produces a context inventory with a keep/cut/restructure verdict per component, ordering and caching fixes, and a token budget. For wording-level prompt tuning use prompt-optimizer.

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项目级上下文工程框架：通过 PROJECT / REQUIREMENTS / ROADMAP / STATE 四层文档 为每个任务建立结构化上下文，控制 token 预算，防止上下文腐烂， 确保跨会话连续性。与 context-lifecycle 的 L0-L3 层互补。

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Audit a repo's agent context — CLAUDE.md files, codebase docs, skills, and tool/MCP designs — against Anthropic's Claude 5 context-engineering guidance ("unhobbling": Anthropic cut ~80% of Claude Code's system prompt with no eval loss). Finds overconstraint, conflicting instructions, redundancy, stale facts, and missing "unknown knowns"; produces a scored findings report with concrete rewrites, then applies approved fixes. Use when someone says "audit my CLAUDE.md", "context audit", "unhobble this repo", "review our agent docs/skills/tools", or after upgrading to Claude 5-generation models.

日本語の概要は準備中です。原文の説明を表示しています。

Manages attention and evidence in long agent sessions. Use for lost instructions, dropped evidence, or large multi-agent contexts.

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Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

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Make technology decisions for every product capability by discovering existing assets, evaluating vendor-aligned options, and categorizing as Reuse/Extend/Build/Buy/Integrate/Research during PRD v0.5 Red Team Review. Handles both greenfield and brownfield contexts. Triggers on "tech stack", "build or buy?", "what technologies?", "technical decisions", "what do we reuse?", "existing stack", "vendor constraint", "IBM-first", "what tools do we need?", "evaluate solutions", "select tech stack". Consumes FEA- (features), SCR- (screens), RISK- (constraints). Outputs TECH- entries with decisions, rationale, and cross-references. Feeds v0.6 Architecture Design.

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Design the changelog as a distribution surface bridging engineering releases (DEP-/FEA-) to marketing channels (GTM-) during PRD v0.8 Deployment & Ops. Triggers on requests to set up a changelog system, publish releases, or when user asks "how should we publish releases?", "changelog as marketing", "release notes", "Stripe-style changelog", "what to do with our release notes", "ship and tell". Outputs MON-CHG-* changelog entries and per-channel formats.

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Connect user journeys to screens, defining the UI structure and navigation paths during PRD v0.4 User Journeys. Triggers on requests to define screens, design screen flows, map UI structure, plan navigation, or when user asks "what screens do we need?", "define screens", "screen flow", "UI structure", "information architecture", "navigation design", "wireframe planning". Consumes UJ- (User Journey Mapping), FEA- (Feature Value Planning), BR- (constraints). Outputs SCR- entries for screens and DES- entries for design system elements. Feeds v0.5 Red Team Review.

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Define how system components connect, establishing boundaries, patterns, and integration approaches during PRD v0.6 Architecture. Triggers on requests to design architecture, create system design, define component relationships, or when user asks "design architecture", "system design", "how do components connect?", "architecture decisions", "technical architecture", "system overview". Consumes TECH- (stack selections), RISK- (constraints), FEA- (features). Outputs ARC- entries documenting architecture decisions with rationale. Feeds v0.6 Technical Specification.

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Surface risks through guided questioning, helping users consider pivots, constraints, and prioritization during PRD v0.5 Red Team Review. Triggers on requests to identify risks, stress-test the idea, perform red team review, or when user asks "what could go wrong?", "identify risks", "red team", "risk assessment", "challenge assumptions", "stress test the idea". Consumes all prior IDs (CFD-, BR-, FEA-, PER-, UJ-, SCR-) as interview context. Outputs RISK- entries with owner decisions and mitigations. Feeds v0.5 Technical Stack Selection.

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Generate visual prototype prompts from SCR- entries for Google Stitch (or equivalent UI generation tool). Triggers on: 'make a prototype', 'visualize screens', 'generate Stitch prompt', 'I need a visual demo', 'prototype the workflow', 'show me what this looks like', 'get this to a demo', 'visual gate'. Consumes SCR- (Screen Flow Definition), PER- (Personas), UJ- (User Journeys), DES- (Design Components). Outputs Stitch prompt blocks per SCR- entry + Feedback Capture Template. No new SoT IDs created — this skill makes existing SCR- entries visual and routes feedback back to them.

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Install the PRD-Driven Context Engineering methodology into a fresh OR existing repository — the subscription-native alternative to forking the whole repo. Runs an interactive wizard that seeds the framework (.claude/ hooks, skills, agents, rules, scripts) without clobbering product content. Triggers on "install the methodology", "adopt this into my repo", "self-install", "set up PRD lifecycle here", "onboard existing project". Outputs an installed framework + a verification report.

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Validates gate criteria before PRD lifecycle advancement by delegating to the readiness scoring pipeline (scripts/readiness.py). Returns a graduated PASS / WARN / BLOCK verdict with top blockers and their causal chain. Triggers before advancing from v0.X to v0.Y or explicit `/ghm-gate-check`.

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Map user missions from trigger to value moment, organizing features into coherent paths during PRD v0.4 User Journeys. Triggers on requests to map user journeys, define user flows, describe how users accomplish goals, or when user asks "map user journeys", "define user flows", "user missions", "how do users accomplish X?", "journey mapping", "what steps do users take?", "pain to value flow". Consumes PER- (Persona Definition), FEA- (Feature Value Planning), KPI- (Outcome Definition). Outputs UJ- entries with step flows, pain points, and value moments. Feeds v0.4 Screen Flow Definition.

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Establish channels and processes for capturing and processing post-launch feedback during PRD v0.9 Go-to-Market. Triggers on requests to set up feedback systems, capture user input, or when user asks "how do we collect feedback?", "feedback loop", "user research", "post-launch feedback", "customer feedback", "NPS", "voice of customer". Outputs CFD- entries specialized for post-launch feedback capture.

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Build customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference account", "case study interview", "before/after story", "social proof page", "logo wall". Outputs CFD-CASE-* evidence entries, GTM-CASE-* marketing assets, and updates ADO-REF-* with story status.

日本語の概要は準備中です。原文の説明を表示しています。