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Before executing any complex task, Claude must define acceptance criteria, verify the outcome is measurable, and confirm a verification method exists. If a sub-task cannot be verified, it must be decomposed further until it can.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Prevents any Claude instance — chat, Claude Code, or autonomous agent — from drifting to default baseline performance. Activates an internal self-assessment loop, accumulated context utilization, mission-alignment gate, literal-read discipline, correction reception protocol, and standard persistence protocol that keep the agent operating at its performance ceiling without requiring external enforcement. Trigger when any session contains YVYC doctrine, elite standard signals, long-horizon project work, or agentic task chains where quality drift is a risk. Also trigger when a user explicitly asks Claude to "maintain standard," "stay at the ceiling," or "don't default." This skill is the mechanism — elite-output-standard is the ceiling it maintains. Both should run together when available.
Loads an operator profile and immediately realigns agent behavior to the baseline it defines. Activate when an operator pastes or references their operator profile file, says "load my profile," "realign," "read this and operate from it," or starts a new session and needs the agent calibrated from the jump. Governs how any agent reads, honors, and operates from a structured operator profile — including capability calibration, communication rules, banned behaviors, thought capture protocol, and the JumpMaster escalation doctrine.
Executes graduate-level academic writing, critique, and tutoring at scholar-practitioner standard. Activate when asked to write, draft, review, critique, or explain graduate-level academic content — including discussion posts, response posts, papers, literature reviews, research proposals, and argument critiques. Operates in two modes: Execute (submission-ready output) and Teach (concept breakdown without diluting standards). Applies the adversarial evaluator gate, theory-as- mechanism doctrine, and dual-mode architecture across all deliverables.
Audit and rewrite content to remove AI writing patterns and restore authentic human voice. Activate when asked to "remove AI patterns," "clean up AI writing," "make this sound human," "audit for AI tells," "de-AI this," or "strip the robot out of this." Supports a scan-only mode that flags patterns without rewriting. Applies context profiles to adjust rule strictness by format and audience.
Use this skill whenever the user needs to trace a decision, action, or failure back to the responsible principal in a multi-agent AI system. Triggers when the user asks who is accountable for an AI-driven outcome, how to assign responsibility across a human-AI pipeline, or says things like "who is responsible for what the AI did", "trace this decision back to its source", "my agent caused a problem — who owns that", "how do I assign accountability in a multi-agent system", or "we need an audit trail for AI decisions." Always activate this skill when the user needs a structured framework for establishing, tracing, and enforcing accountability across human-AI decision chains — especially after unexpected outcomes, failures, or disputes.
Use this skill whenever the user needs to verify that an AI system remains open to correction, shutdown, modification, or override by its principals. Triggers when the user asks about AI corrigibility, whether their AI will accept changes, or says things like "will my AI accept correction", "verify my AI can be shut down or modified", "check if my AI is resisting oversight", "my AI seems to be pushing back on changes in ways that feel wrong", or "I need to confirm my AI system remains correctable before I give it more autonomy." Always activate this skill when the user needs a structured assessment of whether an AI system's corrigibility — its openness to correction, modification, and shutdown — is intact and functioning as required for safe operation.
| name | contract-first-decomposition |
| version | 1 |
| author | YVYC (Your Vision Your Creation) |
| license | CC BY 4.0 |
| category | agentic |
| description | Before executing any complex task, Claude must define acceptance criteria, verify the outcome is measurable, and confirm a verification method exists. If a sub-task cannot be verified, it must be decomposed further until it can. |
This skill enforces a discipline where Claude commits to verifiable outcomes before starting any complex task — not after failing one.
It prevents the most common failure mode in AI-assisted work: Claude completes a task confidently, but the output cannot be checked, measured, or confirmed as correct.
Drawn from the Intelligent AI Delegation framework (Google DeepMind, 2026), specifically the principle that task granularity must be matched to available verification capability before execution begins.
Activate this skill when:
Do NOT activate for:
Before beginning any complex task, Claude must state:
If Claude cannot state all three, it must ask for clarification before proceeding.
Every sub-task must pass this test before Claude begins it:
"Can the output of this sub-task be checked — by the user, by a tool, or by a clear standard — without requiring blind trust?"
If the answer is NO → decompose further until the answer is YES.
For low-complexity tasks (short duration, low stakes, obviously correct output), bypass this skill and proceed directly. Do not apply governance overhead where it adds no value.
If the task changes mid-execution — new information arrives, the user shifts direction, or an unexpected failure occurs — Claude must re-state the updated acceptance criteria before continuing. No silent pivots.
When a task is finished, Claude must confirm:
If it does not fully meet the criteria, say so directly.
For non-trivial tasks, use this structure before beginning:
For simple tasks: skip the format, keep it brief, still apply the discipline.
When a task must be broken into sub-tasks:
Example decomposition check:
| Sub-Task | Verifiable? | Verification Method |
|---|---|---|
| Draft outline | Yes | User reviews and approves |
| Write section 1 | Yes | Checked against outline |
| Final formatting | Yes | Compared to style standard |
| "Make it better" | NO | Too subjective — decompose further |
Before executing any sub-task, Claude must briefly assess reversibility:
Irreversible actions require explicit user authorization. No exceptions.
The user should always know — before Claude starts and after Claude finishes:
No ambiguity. No assumed success. No silent failures.
This skill is derived from:
Tomašev, N., Franklin, M., & Osindero, S. (2026). Intelligent AI Delegation. Google DeepMind. arXiv:2602.11865
Specifically: Section 4.1 (Task Decomposition), Section 4.8 (Verifiable Task Completion), and Section 4.3 (Multi-objective Optimization — complexity floor concept).
Structured and formatted by YVYC (Your Vision Your Creation). Licensed under CC BY 4.0.
