kylesnowschwartz/simpleclaude/sc-hypothesize
Claude Code and agent skill by kylesnowschwartz/simpleclaude
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Use when multiple plausible approaches must be generated, tested, and compared against constraints before the user chooses.
Install
npx vskill@latest install kylesnowschwartz/simpleclaude/sc-hypothesizeSKILL.md
Structured Reasoning (ADI Cycle)
Reason through problems by generating competing hypotheses, verifying them against constraints, gathering evidence, and presenting a comparison for the user to decide.
Based on the ADI reasoning cycle: Abduction (generate options) -> Deduction (verify logic) -> Induction (gather evidence) -> Decision (user picks).
When to Use This
- Architectural decisions with long-term consequences
- Multiple viable approaches that need systematic comparison
- Decisions that benefit from an auditable reasoning trail
- Problems where anchoring on the first idea is a risk
When NOT to Use This
- Quick fixes with obvious solutions (just do the work)
- Easily reversible decisions (just try it)
- Open-ended uncertainty without clear options (use
/sc-socraticinstead) - Pure implementation tasks (implement directly)
Core Principle: Transformer Mandate
You generate options with evidence. The human decides.
Do not select winners autonomously. Present the comparison, surface the trade-offs, and wait for the user to choose.
The ADI Cycle
Each phase is a conversational turn. The user drives transitions — you don't auto-advance through all phases in one response.
Phase 1: Abduction (Generate Hypotheses)
Generate 3-5 competing approaches. Resist anchoring on the first idea that seems reasonable.
Requirements:
- At least one conservative option (safe, proven, lower risk)
- At least one radical option (novel, higher potential, less proven)
- Each hypothesis states: what it is, key assumptions, and where it applies (scope)
- Classify each as system (code/architecture) or process (methodology/workflow)
Anti-anchoring check: Before generating, ask yourself — am I just listing variations of the same idea? If yes, force at least one genuinely different approach.
Output format:
After presenting hypotheses, ask the user:
- Are any missing? Should we add one?
- Should we kill any before going deeper?
- Ready to verify?
Phase 2: Deduction (Verify Logic)
Check each surviving hypothesis against constraints. Kill the ones that don't hold up.
For each hypothesis, check:
- Logical consistency — Does the approach actually solve the stated problem?
- Constraint compatibility — Does it fit within known technical constraints (existing stack, team skills, timeline)?
- Type correctness — Does the solution shape match the problem shape? (e.g., proposing a caching solution for a data modeling problem)
Verdicts:
- PASS — Logically sound, survives to evidence gathering
- FAIL — Contradicts constraints or logic. Document why and drop it
- REFINE — Has potential but needs adjustment. Modify and re-check
Output format:
After verification, confirm with user: These hypotheses survived. Ready to gather evidence?
Phase 3: Induction (Gather Evidence)
Collect actual evidence for each surviving hypothesis. This is where you do real work — read code, run searches, check docs, analyze feasibility.
Evidence quality tiers:
| Tier | Source | Confidence | |
|---|---|---|---|
| Internal test | Run code, benchmark, prototype in this project | High | |
| Internal analysis | Read this codebase, check compatibility | Medium-High | |
| Similar context | Evidence from similar project/stack | Medium | |
| External docs | Library docs, blog posts, general advice | Low-Medium |
Weakest Link Principle (WLNK): A hypothesis is only as strong as its weakest piece of evidence. Don't average — report the floor.
For each hypothesis, gather:
- Best available evidence (prefer internal over external)
- The weakest link — what's the least certain thing?
- Known unknowns — what couldn't you verify?
Use Agent tools to parallelize evidence gathering when hypotheses are independent.
Output format:
Phase 4: Decision (User Decides)
Present a comparison table and let the user choose.
Output format:
After the user decides, document the rationale:
Persistence
Save reasoning artifacts to .agent-history/reasoning/<slug>/:
Create the directory at the start of Phase 1. Write each file as its phase completes.
Slug generation: Lowercase the problem statement, take first 4-5 words, join with hyphens. Example: "how should we handle caching" -> how-should-we-handle-caching
Execution
- Parse the problem — Read
$ARGUMENTS. If empty, ask what decision needs reasoning.
- Gather context — Use Read, Grep, Glob to understand the relevant codebase before generating hypotheses. Don't hypothesize in a vacuum.
- Run Phase 1 — Generate hypotheses, present to user, wait for confirmation.
- Run Phase 2-4 on user request — Each phase is a separate turn. Don't auto-advance. The user says "verify" or "gather evidence" or "decide" to move forward.
- Early exit is fine — If the answer becomes obvious during Phase 1 or 2, say so. The framework serves the decision, not the other way around.
Shortcuts
/sc-hypothesize [problem]— Start from Phase 1- "verify" / "check logic" — Run Phase 2 on existing hypotheses
- "evidence" / "test these" — Run Phase 3
- "decide" / "compare" — Run Phase 4
- "add hypothesis: [idea]" — Add a user-supplied hypothesis at any point
- "kill H2" — Remove a hypothesis from consideration
Related Commands
| Situation | Next step | |
|---|---|---|
| Open-ended uncertainty, no clear options | /sc-socratic | |
| Quick implementation after deciding | Implement the chosen option directly | |
| Challenge a conclusion adversarially | /sc-review-and-refactor (refute-findings route) | |
| Full feature workflow with architecture | Plan the architecture in plan mode, then implement it |
Security
- Security scanPassedPattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingplugins/sc-skills/skills/sc-hypothesize/SKILL.md
Popularity
- Repository stars
- 103
- Repository forks
- 15
- 7-day trend score
- 23
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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