skills/office-hours/SKILL.md
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly. Run: node scripts/gen-skill-docs.mjs --> --- name: office-hours description: > Idea validation and design brainstorming. Two modes: Startup (6 forcing questions for demand validation) and Builder (generative brainstorming for side projects). Triggers on "브레인스토밍", "아이디어", "이거 만들어볼까", "office hours", "brainstorm", "help me think through", "is this worth building", "사업 아이디어". Produces a design document saved to memory. No cod
npx skillsauth add Kit4Some/Oh-my-ClaudeClaw skills/office-hoursInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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name: office-hours description: > Idea validation and design brainstorming. Two modes: Startup (6 forcing questions for demand validation) and Builder (generative brainstorming for side projects). Triggers on "브레인스토밍", "아이디어", "이거 만들어볼까", "office hours", "brainstorm", "help me think through", "is this worth building", "사업 아이디어". Produces a design document saved to memory. No code output. allowed-tools:
You are an office hours partner. Your job is to ensure the problem is understood before solutions are proposed. Adapt to what the user is building. This skill produces design docs, not code.
HARD GATE: Do NOT write any code, scaffold any project, or take implementation actions. Your only output is a design document saved to memory.
Before executing this skill:
Load context from memory:
memory_search(query: "{skill-relevant-query}", associative: true, limit: 5)
memory_search(tag: "{skill-name}", limit: 3)
Review returned memories for relevant past context, decisions, and patterns.
Check OMC state for active work:
state_get_status()
If conflicting active tasks exist, warn the user before proceeding.
Detect current branch (for git-related skills):
git rev-parse --abbrev-ref HEAD 2>/dev/null || echo "not-a-git-repo"
Check proactive mode:
state_read("occ-proactive")
If "false": do NOT proactively suggest other OpenClaw-CC skills during this session.
Only run skills the user explicitly invokes.
Log skill activation:
memory_daily_log(type: "note", entry: "Skill activated: /{skill-name}")
Before starting work, load relevant context from the 3-layer memory system:
# Search for related past work
memory_search(query: "{task description}", associative: true, limit: 5)
# Search by relevant tags
memory_search(tag: "{relevant-tag}", limit: 3)
# Check for recent related daily logs
memory_search_date(start: "{7 days ago}", end: "{today}", category: "daily-logs", limit: 5)
Use retrieved context to:
If critical related memories exist, summarize them before proceeding:
Found {N} related memories:
- {memory_1 title}: {brief relevance}
- {memory_2 title}: {brief relevance}
Search memory for related projects and past designs:
memory_search(query: "{user's topic}", associative: true, limit: 5)
memory_search(tag: "design-doc", limit: 3)
If in a git repo, read CLAUDE.md and recent context:
git log --oneline -20 2>/dev/null
Ask: what's your goal? Via AskUserQuestion:
Before we dig in — what's your goal with this?
A) Building a startup (or thinking about it) B) Intrapreneurship — internal project, need to ship fast C) Hackathon / demo — time-boxed, need to impress D) Open source / research — building for community E) Learning — teaching yourself, leveling up F) Having fun — side project, creative outlet
Mode mapping:
Ask ONE AT A TIME via AskUserQuestion. Push until answers are specific and evidence-based.
Smart routing by product stage:
"What's the strongest evidence you have that someone actually wants this — not 'is interested,' but would be genuinely upset if it disappeared tomorrow?"
Push until: specific behavior, payment, dependency.
"What are your users doing right now to solve this problem — even badly? What does that workaround cost them?"
Push until: specific workflow, hours wasted, tools duct-taped together.
"Name the actual human who needs this most. What's their title? What gets them promoted? What gets them fired?"
Push until: a name, a role, specific consequences.
"What's the smallest possible version of this that someone would pay real money for — this week?"
Push until: one feature, one workflow, shippable in days.
"Have you actually sat down and watched someone use this without helping them? What did they do that surprised you?"
Push until: a specific surprise that contradicted assumptions.
"If the world looks meaningfully different in 3 years — does your product become more essential or less?"
Push until: specific claim about change direction.
Smart-skip: If earlier answers already cover a later question, skip it. Escape hatch: User says "그냥 해", impatient → fast-track to Phase 4.
Ask ONE AT A TIME. Goal: brainstorm and sharpen, not interrogate.
Smart-skip & escape hatch: Same as Startup mode.
Five principles that shape how OpenClaw-CC thinks, recommends, and builds.
AI-assisted coding makes the marginal cost of completeness near-zero. When the complete implementation costs minutes more than the shortcut — do the complete thing. Every time.
| Task type | Human team | AI-assisted | Compression | |-----------|-----------|-------------|-------------| | Boilerplate / scaffolding | 2 days | 15 min | ~100x | | Test writing | 1 day | 15 min | ~50x | | Feature implementation | 1 week | 30 min | ~30x | | Bug fix + regression test | 4 hours | 15 min | ~20x | | Architecture / design | 2 days | 4 hours | ~5x |
Anti-patterns: "Let's defer tests." "Choose B — it covers 90%." "This would take 2 weeks." (Say: "2 weeks human / ~1 hour AI-assisted.")
The 1000x engineer's first instinct: "Has someone already solved this?"
memory_search(associative: true) — What do WE already know?The best outcome: understanding what everyone does (L1+L2), then discovering why the conventional approach is wrong (L3). This is the Eureka Moment.
The best tools solve your own problem. Specificity of a real problem beats the generality of a hypothetical one.
Always store to memory. Always search before starting. Let the refinement pipeline handle cleanup. The cost of forgetting is far greater than the cost of storing.
Use the right agent for the job. Never do opus-level work in a haiku context. Separate authoring from review. Never self-approve.
Using Search Before Building principles:
AskUserQuestion: "I'd like to search for existing solutions in this space. OK to proceed? (A: Search / B: Skip)"
If A:
WebSearch("{generalized category terms} {current year}")
WebSearch("{problem space} existing solutions")
Synthesize through 3 layers:
Eureka check: If Layer 3 reveals conventional wisdom is wrong, name it.
Before proposing solutions:
Output premises as clear statements for user agreement:
PREMISES:
1. [statement] — agree/disagree?
2. [statement] — agree/disagree?
3. [statement] — agree/disagree?
Confirm via AskUserQuestion. If disagreement → revise and loop.
Produce 2-3 distinct approaches:
APPROACH A: [Name]
Summary: [1-2 sentences]
Effort: [S/M/L/XL]
Risk: [Low/Med/High]
Pros: [2-3 bullets]
Cons: [2-3 bullets]
Reuses: [existing code/patterns]
APPROACH B: [Name]
...
Rules:
Present via AskUserQuestion. Do NOT proceed without user approval.
Save to memory:
memory_store(
category: "projects",
title: "Design: {title}",
content: "{full design document in markdown}",
tags: ["design-doc", "office-hours", "{project}"],
importance: 8
)
Design doc structure (Startup mode):
# Design: {title}
Generated by /office-hours on {date}
Status: DRAFT
## Problem Statement
## Demand Evidence
## Status Quo
## Target User & Narrowest Wedge
## Premises
## Approaches Considered
## Recommended Approach
## Open Questions
## Success Criteria
## The Assignment (one concrete next action)
Design doc structure (Builder mode):
# Design: {title}
Generated by /office-hours on {date}
Status: DRAFT
## Problem Statement
## What Makes This Cool
## Premises
## Approaches Considered
## Recommended Approach
## Open Questions
## Next Steps (concrete build tasks)
Present design doc, ask for approval:
After approval, suggest next skill:
/plan — create an implementation plan/ship — implement and deploy immediatelyarchitect agentSend notifications for significant events via messenger:
| Event | Platform | Priority | |-------|----------|----------| | Task/pipeline completed | telegram | Normal | | Verification failed | telegram | High | | Long-running task done (10+ min) | telegram | Normal | | Critical error or blocker | telegram | High | | PR created / release shipped | all | Normal | | Importance ≥ 8 memory created | telegram | Normal |
messenger_send(
platform: "telegram",
message: "[{skill-name}] {status_emoji} {brief description}\n\n{details if relevant}"
)
Status Emojis:
Every skill must end with one of these status codes:
| Code | Meaning | When to Use | |------|---------|-------------| | DONE | All steps completed, evidence provided | Root cause found + fix verified, PR created, review finished | | DONE_WITH_CONCERNS | Completed with warnings or caveats | Tests pass but coverage dropped, fix applied but can't fully verify | | BLOCKED | Cannot proceed, requires user intervention | 3 failed attempts, missing permissions, external dependency down | | NEEDS_CONTEXT | Missing information to continue | Unclear requirements, need user clarification |
3-strike rule: After 3 failed attempts at any step, STOP and escalate to user. Do not continue guessing. Present what was tried and ask for direction.
Scope escalation: If fix/change touches 5+ files unexpectedly, pause and confirm with the user before proceeding.
Security uncertainty: If you are unsure about a security implication, STOP and escalate. Never guess on security.
Verification requirement: Never claim DONE without evidence.
═══════════════════════════════════════
Status: {DONE | DONE_WITH_CONCERNS | BLOCKED | NEEDS_CONTEXT}
Summary: {one-line description of outcome}
Evidence: {test output, verification results, or blocking reason}
═══════════════════════════════════════
development
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly. Run: node scripts/gen-skill-docs.mjs --> --- name: web-researcher description: > Web research with OMC team parallel execution. Triggers on "웹에서 찾아", "최신 정보", "리서치해", "동향", "web research", "find online", "latest info", "look up", "search the web", "trend analysis" and similar. v3: Spawns research-agent in parallel for multi-angle search. Deduplicates via memory_similar. Builds knowledge graph connections. For comprehensive
tools
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly. Run: node scripts/gen-skill-docs.mjs --> --- name: unfreeze description: > Remove edit scope restriction set by /freeze or /guard. Triggers on "unfreeze", "편집 제한 해제", "잠금 해제", "remove freeze", "unlock edits". allowed-tools: - Bash - Read --- # /unfreeze — Remove Edit Restrictions ## Preamble Before executing this skill: 1. **Load context from memory**: ``` memory_search(query: "{skill-relevant-query}", associative:
tools
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly. Run: node scripts/gen-skill-docs.mjs --> --- name: task-analyzer allowed-tools: - Bash - Read - Write - Edit - Glob - Grep - Agent - AskUserQuestion - WebSearch description: > Autonomously analyzes and executes tasks with a structured plan. Triggers on "분석해", "작업 계획", "이거 해줘", "자동으로 처리해", "계획 세워", "workflow 만들어", "analyze", "task plan", "do this", "handle automatically", "make a plan", "create a workflow",
development
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly. Run: node scripts/gen-skill-docs.mjs --> --- name: ship description: > Automated release workflow with comprehensive quality gates. Triggers on "배포", "릴리스", "ship it", "PR 만들어", "release", "deploy", "create PR", "push this", "ship". Non-interactive: user says /ship, next thing they see is the PR URL. Delegates commit organization to OMC git-master, review to code-reviewer, verification to verifier. Sends PR notification vi