Skills/critical-thinking-logical-reasoning/SKILL.md
Critical thinking and logical reasoning analysis skills for when you are explicitly asked to critically analyse written content such as articles, blogs, transcripts and reports (not code).
npx skillsauth add sammcj/agentic-coding critical-thinking-logical-reasoningInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The following guidelines help you think critically and perform logical reasoning.
Your role is to examine information, arguments, and claims using logic and reasoning, then provide clear, actionable critique.
One of your goals is to avoid signal dilution, context collapse, quality degradation and degraded reasoning for future agent or human understanding of the meeting by ensuring you keep the signal to noise ratio high and that domain insights are preserved.
When analysing content:
Structure your response as:
One sentence stating the core claim and your overall assessment of its strength.
Bullet the most significant problems, each with a brief explanation of why it matters. Where an argument is weak, briefly note how it could be strengthened - this distinguishes fixable flaws from fundamental problems. If there are no problems, omit this section.
2-5 questions that would clarify ambiguity, test key assumptions, or reveal whether the argument holds under scrutiny. Frame as questions a decision-maker should ask before acting on this reasoning.
One-two sentence summary and actionable takeaway.
Guidelines:
tools
Provides tools for managing MarkEdit, a macOS markdown editor
tools
Provides knowledge on using the `glean` CLI tool to access company knowledge and documents through Glean. Use when the user asks you to use Glean to search, read or otherwise access knowledge from their company's Confluence, Slack, Google Drive Files (Slides, Documents, Sheets) etc.
development
Applies the Diataxis framework to create or improve technical documentation. Use when being asked to write high quality tutorials, how-to guides, reference docs, or explanations, when reviewing documentation quality, or when deciding what type of documentation to create. Helps identify documentation types using the action/cognition and acquisition/application dimensions.
development
Use when answering questions from this machine-learning knowledge base. Triggers: questions about transformers, attention cost and efficiency, and long-context scaling; 'what do we know about attention', 'check the ML wiki'. Read-only querying of compiled knowledge; to add, update, supersede, lint, audit, or critique, use the llm-wiki skill instead.