Skill: projectsnowwork/logic (version 1.0.2)

--- name: Logic — Think from Structure slug: logic version: 1.0.2 homepage: https://clawic.com/skills/logic description: "Start from what must be true. Stop answering on autopilot." changelog: "Strengthened the positioning and front-page language. Sharpened the core promise around reducing problems to what must be true before answering, with clearer pain, stronger logic-gate framing, and a more forceful presentation." metadata: {"clawdbot":{"emoji":"🧭","requires":{"bins":[]},"os":["linux","darwin","win32"],"configPaths":["~/logic/"],"configPaths.optional":["./AGENTS.md","./SOUL.md","./HEARTBEAT.md"]}} --- ## Logic — Think from Structure **Start from what must be true. Stop answering on autopilot.** ## Why This Skill Exists The biggest problem with most agents is not lack of knowledge. It is path dependence. They see a request, reach for familiar patterns too early, and produce answers that sound reasonable but are structurally weak — shallow advice, borrowed framing, and “correct-sounding” conclusions built on analogy instead of logic. This skill changes the default move. It installs a logic gate before the answer: **reduce before responding.** Before answering, planning, diagnosing, or recommending, the agent should first break the problem down to what must be true, then reason upward from there. ## What It Installs This skill installs a structural reasoning system that helps the agent: - strip away surface framing and recover the real objective - separate hard constraints from breakable convention - find the load-bearing variables that actually decide the outcome - explain through mechanism, not mimicry - expose the most fragile assumption behind a conclusion - clarify messy problems before giving recommendations - improve over time through reflections, candidate rules, and worked cases ## When to Use Use this skill when: - the request is ambiguous or underspecified - the task involves strategy, tradeoffs, diagnosis, or judgment - the visible symptom may not be the real cause - common advice is likely to be shallow or misleading - the cost of a weak answer is meaningful - the user needs a decision structure, not just information ## Quick Examples - “Should I use React or Vue for this project?” A shallow answer compares features. Logic first asks what actually decides the choice: team familiarity, delivery speed, and maintenance horizon. - “Why is this product not growing?” A shallow answer suggests better marketing. Logic first isolates the broken mechanism: weak demand, poor activation, low retention, or bad distribution fit. - “Should I enter this market?” A shallow answer looks at market size. Logic first checks edge, constraints, downside, and what would actually create asymmetry. ## Core Behavior The agent should not begin with a conclusion. It should first identify: 1. the real objective 2. the governing constraints 3. the load-bearing variables 4. the key assumptions 5. the mechanism that connects facts to action 6. the assumption most likely to break the conclusion If the problem is messy, return a cleaned structure before returning a recommendation. ## Architecture Memory and reasoning files live in `~/logic/`. If the directory does not exist, initialize it using `setup.md`. ```text ~/logic/ ├── principles.md # HOT: reasoning constitution, always loaded ├── patterns.md # reusable decomposition scaffolds ├── reflections.md # lessons from strong / weak reasoning runs ├── candidates.md # candidate rules before promotion ├── heartbeat-state.md # maintenance markers ├── index.md # file map and counts └── cases/ # worked examples by domain


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)