Use when an output makes claims, explanations, interpretations, judgments, recommendations, forecasts, or persuasive conclusions that need explicit warrants, assumptions, countercases, and implications; use analytic-tradecraft for estimative or contested-evidence methods.
Use when an output makes claims, explanations, interpretations, judgments, recommendations, forecasts, or persuasive conclusions that need explicit warrants, assumptions, countercases, and implications; use analytic-tradecraft for estimative or contested-evidence methods.
This is the engine's universal thinking layer. It prevents the engine from merely collecting information and arranging it into plausible prose: every serious output must expose its question, terms, evidence, assumptions, inference chain, countercase, limits, and action implications.
Use When
Use this skill for all forms of writing and reporting that contain a claim or conclusion: academic essays, theses, dissertations, literature reviews, systematic reviews, intelligence products, market analyses, history essays, business reports, proposals, board briefs, due diligence, policy analysis, legal argument, technical recommendations, and executive communication.
Do Not Use When
The task is purely formatting, file movement, or mechanical conversion.
The output contains no claim, recommendation, interpretation, evaluation, forecast, or decision support.
A domain skill already handles a narrow factual extraction and no conclusion is being drawn.
Reasoning Intake Guidance
The user's real question, decision, audience, and output type.
Available sources, data, notes, or draft text.
Known constraints, scope boundaries, definitions, and country or domain context.
Any required confidence, citation, or evidence standard.
Non-negotiable rule
No conclusion ships until it has passed the reasoning protocol in references/reasoning-protocol.md.
For research work, this skill operates after source-evaluation: source quality determines what can be used as evidence; this skill determines whether the evidence supports the conclusion. For intelligence or forward-looking work, run analytic-tradecraft after this skill to add probability language, hypothesis handling, and uncertainty discipline.
Reasoning Method Detail
Frame the real question. Convert the prompt into a precise question the output must answer. If the prompt asks for "a report", infer the decision, controversy, interpretation, or action the report is meant to support.
Define scope and terms. Identify key terms, boundaries, jurisdiction, time period, population, market, method, or discipline. Flag ambiguous or loaded language.
Separate the materials. Distinguish facts, claims, assumptions, values, interpretations, inferences, recommendations, and unknowns.
Map the argument. Build the chain: main conclusion -> intermediate conclusions -> premises/evidence -> warrants/linking assumptions. Use the table in references/reasoning-protocol.md.
Test evidence quality. Apply source-evaluation; then ask whether the available evidence is relevant, sufficient, representative, current, and independent.
Run the countercase. State the strongest plausible objection, alternative explanation, rival hypothesis, or historiographical/market/technical counter-reading.
Audit inference quality. Test causal claims, generalisations, analogies, statistics, definitions, conditionals, necessity/sufficiency, and certainty calibration.
Check coherence and fallacies. Look for contradiction, circular reasoning, equivocation, straw-manning, false alternatives, hasty generalisation, post hoc causation, appeal to authority, appeal to majority, and unsupported value leaps.
Choose the action form. Route the tested reasoning into the right structure and tone using references/audience-action-forms.md.
Run the serious-analysis overlay. Use references/essential-questions-mental-models-strategic-logic.md when the output must show deeper thought, business sense, feasibility, strategic judgment, or problem-solving logic.
Ship with limits. State what the conclusion means, what it does not mean, confidence limits, operational implications, and next actions.
Quality Standards
Every output using this skill must be:
Convincing: the reader can see why the conclusion follows from the evidence.
Authentic: the tone fits the institution, audience, discipline, and stakes; no generic filler or artificial certainty.
Realistic: recommendations name constraints, tradeoffs, risks, time, cost, incentives, and implementation friction.
Actionable: the reader knows what decision, interpretation, next step, or research move follows.
Proportionate: claim strength matches evidence strength; uncertainty is not hidden.
High-stakes research, business analysis, proposals, plans, recommendations, strategy, design thinking, feasibility, and any output that must show serious analysis
references/audience-action-forms.md
Choosing structure, tone, and delivery form for academic, intelligence, market, history, business, policy, legal, technical, or executive outputs
