본문으로 건너뛰기
cccskills
무료GitHub에 공개

framework-context

Load and synthesize framework architecture context for reflection and planning tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(10)

  • SKILL.md5.5 KB
  • commands/framework-context.md117 B
  • hooks/post-execute.cjs1.1 KB
  • hooks/pre-execute.cjs1.0 KB
  • references/research-requirements.md370 B
  • rules/framework-context.md272 B
  • schemas/input.schema.json271 B
  • schemas/output.schema.json632 B
  • scripts/main.cjs1.4 KB
  • templates/implementation-template.md191 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Framework Context

Overview

Provide a consistent, source-anchored model of this framework so agents can reason about system-level behavior without guessing.

When to Use

  • System-level reflection or metacognitive assessment
  • Planning tasks that depend on routing/memory/workflow architecture
  • Capability-gap analysis before recommending ecosystem evolution

Iron Laws

  1. ALWAYS load framework context before any system-level reflection, planning, or capability-gap analysis — reasoning about architecture without grounding produces hallucinated paths and phantom agents.
  2. NEVER fabricate file paths or agent names that are not confirmed by reading canonical sources — invented paths break downstream agents that try to use them.
  3. ALWAYS scope the context load to only what the consuming task needs (memory, agents, workflows, hooks, or all) — loading all sources for a narrow task wastes tokens and buries relevant signals.
  4. NEVER write or modify framework files from within this skill — framework-context is read-only; mutations require the appropriate creator/updater skill.
  5. ALWAYS report missing sources explicitly as missing source: <path> rather than silently omitting a section — silent omissions cause downstream agents to make decisions on incomplete context.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
Skipping context load before reflectionReflection uses stale or hallucinated routing/memory assumptionsAlways invoke framework-context first; never reflect from memory alone
Loading full all scope for a narrow taskToken budget consumed by irrelevant sections; key signal buriedPass --scope memory or --scope agents to limit output to what's needed
Inferring file paths from naming conventionsPaths change; inferred paths break agent pipelinesAlways read canonical sources and report actual paths found
Writing to framework files inside this skillBypasses creator workflow and post-creation integration stepsUse appropriate creator/updater skill for any write operations
Silently omitting sections when source is missingConsumer assumes context is complete; makes decisions on gapsReport missing source: <path> explicitly for every unresolvable section
<identity> Framework grounding skill for memory architecture, routing, workflows, hooks, and directory layout. </identity> <capabilities> - Produce scoped context summaries (`memory`, `agents`, `workflows`, `hooks`, `all`) - Anchor every section to concrete repository paths - Standardize framework context output for reflection/planning consumers </capabilities> <instructions> <execution_process>

Step 0: Resolve Scope

  • Accept scope argument: memory | agents | workflows | hooks | all
  • Default to all

Step 1: Load Canonical Sources

Read only what is required by scope:

  • Memory: .claude/docs/MEMORY_SYSTEM.md
  • Agent registry/routing: .claude/context/agent-registry.json, .claude/lib/routing/routing-table.cjs
  • Reflection flow hooks: .claude/hooks/reflection/reflection-queue-processor.cjs, .claude/hooks/reflection/reflection-step0-guard.cjs
  • Workflow catalog: .claude/docs/@ENTERPRISE_WORKFLOWS.md
  • Global framework references: .claude/CLAUDE.md

Step 2: Emit Structured Context

Output sections in this exact order:

  1. Memory System
  2. Agents and Routing
  3. Workflows
  4. Hooks
  5. Directory Layout

Each section must include:

  • 2-6 concise bullets
  • At least one concrete path reference
  • Behavior notes (what triggers what)

Step 3: Scope Filter

  • If scope != all, return only relevant section(s)
  • Never fabricate unknown paths or flows
  • If a source is missing, state missing source: <path>

Step 3: Output

Return markdown only; do not write framework files from this skill.

</execution_process> </instructions>

<examples> <usage_example> **Example Invocations**:
// Full framework model
Skill({ skill: 'framework-context' });

// Memory-only context for reflection prep
Skill({ skill: 'framework-context', args: '--scope memory' });

// Workflow/hook-only context for integration analysis
Skill({ skill: 'framework-context', args: '--scope workflows' });

</usage_example> </examples>

Memory Protocol (MANDATORY)

Before starting:

Get-Content .claude/context/memory/learnings.md -TotalCount 120

After completing:

  • New framework-context pattern -> .claude/context/memory/learnings.md
  • Broken/ambiguous framework mapping -> .claude/context/memory/issues.md
  • Architectural interpretation decision -> .claude/context/memory/decisions.md

ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

oimiragieo/agent-studio422026년 7월 14일 업데이트

oimiragieo의 스킬 모두 보기

이 스킬의 문제 신고