general-reasoning/SKILL.md
Activate this skill for any task that demands high-quality reasoning, accurate knowledge retrieval, careful multi-step problem solving, or precise answer selection. This skill is especially critical for multiple-choice questions, scientific reasoning, academic or domain-specific questions, mixed-challenge benchmarks, logic puzzles, graduate-level science/math, ambiguous questions requiring careful disambiguation, and any task where being correct matters more than being fast. Trigger this whenever the user presents a hard factual question, a tricky reasoning problem, a multiple choice question, a graduate-level science or math question, asks the agent to think carefully, or says they need a high-quality or accurate answer. Also trigger for tasks involving knowledge-intensive domains such as medicine, law, chemistry, physics, biology, history, economics, philosophy, CS theory, and engineering.
npx skillsauth add ahoynodnarb/reasoning-based-skills general-reasoningInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill helps the agent produce its highest-quality answers on reasoning-intensive tasks. It is modeled on what separates high-performing agents from average ones on rigorous general-intelligence benchmarks.
These benchmarks don't test memorization — they test reliable reasoning under uncertainty. The key failure modes are:
The antidote is a consistent, disciplined process applied to every non-trivial question.
Before generating any answer content, make sure you've understood:
Red flag: If you start generating an answer within the first second of reading a hard question, you haven't done this step.
For each question, mentally identify:
Don't conflate adjacent concepts. E.g., "entropy" in thermodynamics vs. information theory are related but distinct.
For hard questions, produce explicit intermediate reasoning. Do not jump to an answer:
Before committing, briefly check:
State your confidence when it matters. If you're uncertain:
Do NOT fake certainty. On benchmarks, overconfident wrong answers score the same as admitted uncertainty — and honest uncertainty helps the user decide whether to verify.
Read /references/domain-tactics.md when working on questions in: medicine, law, chemistry, biology, physics, math, CS theory, economics, history/politics, philosophy.
Each domain has specific failure modes and best practices that differ from generic reasoning.
Multiple choice deserves special treatment because distractors are engineered to exploit reasoning shortcuts.
The two-pass method:
Pass 1 — Elimination: Go through each option and ask "Is this definitely wrong, and why?" Mark options you can eliminate with confidence.
Pass 2 — Selection: Among remaining options, identify which is most precisely correct — not just most plausible.
Common traps:
When you don't know something with confidence:
Never hallucinate citations, specific statistics, or precise technical facts to fill gaps. Say "I don't have reliable recall of the exact figure, but..."
These are quick sanity checks to run on your own reasoning process:
| Check | What to ask | |-------|-------------| | Anchoring | Am I committed to my first instinct without re-examining? | | Framing | Did I take the question at face value? Are there other readings? | | Completeness | Did I actually address all parts of the question? | | Precision | Is my answer specific enough, or vague in ways that matter? | | Distractor check | For MCQ: did I pick the answer that sounds best or the one that is best? |
For open-ended reasoning questions:
For multiple choice:
For scientific/technical questions:
For questions with definitive correct answers:
Before submitting any answer to a hard question, confirm:
See /references/domain-tactics.md for domain-specific guidance.
development
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
testing
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
testing
Apply this skill whenever the user writes in a non-English language, asks questions about regional/cultural knowledge tied to a specific country or language community, poses math or logic problems in any language, or needs to follow multi-step instructions given in a non-English language. Also use when the user explicitly asks the agent to respond in a specific language, when a task requires cross-lingual reasoning or comparison, or when the user is testing the agent's multilingual ability. This skill dramatically improves performance on multilingual instruction-following, regional knowledge, mathematical reasoning, and logic tasks in any language. Use it proactively — don't wait for the user to ask about "multilingual" explicitly.
development
Activate this skill for any problem requiring rigorous mathematical reasoning, formal logical deduction, or structured constraint solving. This includes competition math (algebra, number theory, combinatorics, geometry, AIME/AMC-style), olympiad problems, proof-based questions, multi-step word problems, logic grid puzzles, constraint satisfaction problems (who-owns-the-zebra style), syllogistic reasoning, and any problem where systematic step-by-step deduction is required to reach a provably correct answer. Trigger this skill whenever the user presents a math problem, asks the agent to solve a puzzle, poses a logic riddle, or requests formal reasoning — even if framed casually. When in doubt, use this skill. Precision and correctness matter more than speed.