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- nyldn/claude-octopus
- 최근 소스 활동
- 2026년 8월 13일 14:21
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/nyldn/claude-octopus --skill skill-intent-contract명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work
Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work
Multi-AI validation, scoring, and review using available external providers (Double Diamond Deliver phase)
SKILL.md 표시 중
| name | skill-intent-contract |
| description | Use when starting a complex or ambiguous task that risks scope drift |
| disable-model-invocation | true |
Host: Codex CLI — This skill was designed for Claude Code and adapted for Codex. Cross-reference commands use installed skill names in Codex rather than
/octo:*slash commands. Use the active Codex shell and subagent tools. Do not claim a provider, model, or host subagent is available until the current session exposes it. For host tool equivalents, seeskills/blocks/codex-host-adapter.md.
The intent contract creates a persistent record of user intent that:
This closes the loop between intention and delivery.
The intent contract is stored in .claude/session-intent.md and follows this format:
# Intent Contract
**Created**: [ISO timestamp]
**Workflow**: [discover/embrace/review/etc.]
**Status**: [active/validating/completed]
## Job Statement
What the user is trying to accomplish (JTBD framework).
[User's goal in plain language]
## Success Criteria
### Good Enough
- [Minimum viable success criterion 1]
- [Minimum viable success criterion 2]
### Exceptional
- [Excellence criterion 1]
- [Excellence criterion 2]
## Boundaries
What this should NOT be:
- [Boundary 1: What to avoid]
- [Boundary 2: What's out of scope]
## Context & Constraints
**Stakeholders**: [Who needs this to work for them]
**Existing Assets**: [What to build on]
**Timeline**: [Time constraints if any]
**Technical Constraints**: [Platform, language, dependencies]
## Clarifying Context
[Any answers from the 3-question pattern]
## Task Allocation
**Risk**: [low | intermediate | high]
**Initiative**: [human | AI | shared] — who starts and proposes
**Control**: [human | AI | shared] — who oversees execution as it runs
**Decision rights**: [human | AI] — who has final say on the outcome
**AI role**: [none | executor | collaborator | challenger]
**Execution disposition**: [AI-assisted | human-only | pending-user-decision]
**Escalation decision**: [not-needed | pending | user's recorded resolution]
**Resolved AUTONOMY_MODE**: [supervised | semi-autonomous | loop-until-approved | autonomous | not-applicable (contract-only sentinel)]
## Validation Checklist
- [ ] Meets "good enough" criteria
- [ ] Respects all boundaries
- [ ] Works for all stakeholders
- [ ] Builds on existing assets appropriately
- [ ] Allocation still fits what the task turned out to be
Create an intent contract when:
/octo:embrace, /octo:discover, /octo:plan)Do NOT create for:
Run this before capturing intent. The question is not how to run the task across agents but whether it should be delegated at all, and if so, which parts of the authority go where. Framework: Afroogh, Varshney & D'Cruz (2025), A Task-Driven Human-AI Collaboration (arXiv:2505.18422).
Classify risk. Complexity is already scored elsewhere — defer to
estimate_complexity and classify_cynefin in scripts/lib/routing.sh rather
than re-deriving it. Risk is a separate axis that nothing in the codebase
measures, so judge it here on three questions:
| Risk | Reading |
|---|---|
| Low | Reversible, no material consequence, no named accountability. |
| Intermediate | Reversible only at real cost, or consequence is unclear. |
| High | Irreversible, materially consequential, or someone must answer for it. |
Allocate the three dimensions separately. They are independent, and treating them as one axis is the mistake this step exists to prevent. People readily hand AI the initiative on unfamiliar work while keeping control and decision rights — an allocation a single autonomy slider cannot express.
Record every outcome explicitly:
| Risk / complexity | Initiative | Control | Decision rights | AI role | Execution disposition | Escalation decision | Mode |
|---|---|---|---|---|---|---|---|
| Low / low | AI | AI | AI | executor | AI-assisted | not-needed | autonomous |
| Low / high | shared | human | human | collaborator | AI-assisted | not-needed | loop-until-approved |
| High / low | human | human | human | executor | AI-assisted | not-needed | supervised |
| High / high | human | human | human | challenger | AI-assisted | not-needed | supervised |
The High / high allocation is adversarial: the human leads while AI attacks the proposed decision as a deliberate counterweight to the human's own bias. In High / low work, AI may execute only the bounded actions the human directly approves.
The rule that inverts. For intermediate-risk work where uncertainty is highest, the cited evidence says avoid AI entirely — "neither as a gatekeeper nor as a second opinion". This contradicts the smooth intuition that middling risk implies middling involvement, and it also sits in tension with the same paper's broader claim that complete human autonomy is rarely justified. That tension is real and unresolved; surface it to the user and let them decide rather than quietly picking a side.
Resolve to a setting. The workflow engine reads one variable,
AUTONOMY_MODE, with four values:
| Allocation | AUTONOMY_MODE |
|---|---|
| Human holds control and decision rights, approving each phase | supervised |
| AI runs; human is pulled in on failures and quality gates | semi-autonomous |
| AI runs and iterates; human holds final decision rights | loop-until-approved |
| AI holds all three | autonomous |
Record the three dimensions and the resolved mode. The mapping is lossy: one axis cannot represent three independent allocations, so a contract that stores only the mode loses the reason it was chosen. That record is what a later reviewer needs when the allocation turns out to have been wrong.
not-applicable is a persisted, contract-only sentinel for human-only work; it
is not a fifth runtime value and must not be passed to the workflow engine.
For intermediate risk, record Execution disposition: pending-user-decision.
Record Escalation decision: pending, then stop before execution.
Ask the user to choose human-only handling or a specific documented AI allocation.
Record their answer, rewrite the Task Allocation fields to match it, and change
Escalation decision to the user's resolution before continuing. For a human-only
resolution, record AI role: none and Resolved AUTONOMY_MODE: not-applicable;
human-only not-applicable must not be passed to the workflow engine. Resolve to the
supported human-only behavior and do not execute AI work in that state.
For a documented AI-assisted resolution, record every Task Allocation field:
Initiative, Control, Decision rights, and AI role from the chosen allocationExecution disposition: AI-assistedEscalation decision: user's recorded resolutionResolved AUTONOMY_MODE: exactly one of supervised, semi-autonomous,
loop-until-approved, or autonomous, mapped using the table aboveValidate the selected runtime mode and only then execute. The runtime must reject
not-applicable and every unknown or unsupported mode before workflow execution rather
than defaulting to autonomous behavior.
After asking the 3 clarifying questions in a workflow, prompt the user to define:
AskUserQuestion({
questions: [
{
question: "What are you ultimately trying to accomplish?",
header: "Goal",
multiSelect: false,
options: [
{label: "Let me describe it", description: "I'll write my own goal statement"},
{label: "Make a decision", description: "Choose between options"},
{label: "Create deliverable", description: "Build something specific"},
{label: "Understand a problem", description: "Research and learn"}
]
},
{
question: "What defines success for this?",
header: "Success",
multiSelect: true,
options: [
{label: "Clear recommendation", description: "Know what to do next"},
{label: "Working implementation", description: "Code that functions"},
{label: "Team alignment", description: "Everyone understands"},
{label: "Problem solved", description: "Issue is resolved"}
]
},
{
: ,
: ,
: ,
: [
{: , : },
{: , : },
{: , : },
{: , : }
]
}
]
})
If user selects "Let me describe it", follow up with a text prompt for their custom goal.
Use the Write tool to create .claude/session-intent.md:
cat > .claude/session-intent.md <<EOF
# Intent Contract
**Created**: $(date -u +"%Y-%m-%dT%H:%M:%SZ")
**Workflow**: ${WORKFLOW_NAME}
**Status**: active
## Job Statement
${USER_GOAL}
## Success Criteria
### Good Enough
${MIN_SUCCESS_CRITERIA}
### Exceptional
${EXCEPTIONAL_CRITERIA}
## Boundaries
What this should NOT be:
${BOUNDARIES}
## Context & Constraints
**Stakeholders**: ${STAKEHOLDERS}
**Timeline**: ${TIMELINE}
## Clarifying Context
${THREE_QUESTION_ANSWERS}
## Validation Checklist
- [ ] Meets "good enough" criteria
- [ ] Respects all boundaries
- [ ] Works for all stakeholders
EOF
Throughout the workflow, periodically read .claude/session-intent.md to:
At key decision points, explicitly say:
Checking against intent contract: [reference specific criterion]
When the workflow completes, read .claude/session-intent.md and validate:
Validation Process:
Read the intent contract
Check each success criterion:
Check boundaries:
Generate validation report:
# Validation Report
## Success Criteria Check
### Good Enough Criteria
- [✓] Criterion 1: [How it was met]
- [✗] Criterion 2: [Why not met, what's needed]
### Exceptional Criteria
- [~] Criterion 1: [Partial progress explanation]
## Boundary Check
All boundaries respected: [Yes/No]
- Boundary 1: [✓/✗] [Explanation]
## Gaps & Next Steps
[If any criteria not met, list concrete next steps]
## Overall Assessment
[Summary: Does this fulfill the original intent?]
Update the Status field in .claude/session-intent.md:
active → workflow in progressvalidating → checking against criteriacompleted → all criteria met, boundaries respectedincomplete → some criteria not met, gaps identified1. Ask 3 clarifying questions (scope, focus, autonomy)
2. Create intent contract
3. DISCOVER phase (reference intent)
4. DEFINE phase (reference intent)
5. DEVELOP phase (reference intent)
6. DELIVER phase (reference intent)
7. Validate against intent contract
8. Present validation report
1. Ask 3 clarifying questions (depth, focus, output)
2. Create intent contract
3. Execute multi-provider research
4. Synthesize findings
5. Validate against intent contract
6. Present validation report
1. Capture comprehensive intent
2. Create intent contract
3. Route to appropriate workflows
4. Execute custom sequence
5. Validate against intent contract
6. Present validation report
# Intent Contract
**Created**: 2026-01-21T15:30:00Z
**Workflow**: embrace
**Status**: active
## Job Statement
Build a user authentication system that our team can implement and maintain.
## Success Criteria
### Good Enough
- Team understands what to build
- Clear technical approach selected
- Security considerations documented
- Implementation plan with steps
### Exceptional
- Multiple authentication methods evaluated
- Security audit performed
- Code examples provided
- Integration tests included
## Boundaries
What this should NOT be:
- Over-engineered with unnecessary features
- Disconnected from our existing Node.js/Express stack
- Experimental or unproven technologies
## Context & Constraints
**Stakeholders**: Development team (5 engineers), Product manager
**Existing Assets**: Express.js API, PostgreSQL database
**Timeline**: Need to start implementation next sprint
**Technical Constraints**: Must work with Express.js, PostgreSQL
## Clarifying Context
**Scope**: Medium feature (multiple components)
**Focus Areas**: Security, Architecture design
**Autonomy**: Supervised (review after each phase)
## Validation Checklist
- [ ] Meets "good enough" criteria
- [ ] Respects all boundaries
- [ ] Works for all stakeholders
- [ ] Builds on existing assets appropriately
For Users:
For Workflows:
Ready to use! Workflows can now create and validate against persistent intent contracts.