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Agent Skills in category: methodology

272 skills match this category. Browse curated collections and explore related Agent Skills.

ship-learn-next

Transform learning content (like YouTube transcripts, articles, tutorials) into actionable implementation plans using the Ship-Learn-Next framework. Use when user wants to turn advice, lessons, or educational content into concrete action steps, reps, or a learning quest.

implementation-planlearning-resource-curationtask-planning
michalparkola
michalparkola
14533

scientific-problem-selection

This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".

research-methodologyresearch-ideationresearch-gapsstrategic-analysis
anthropics
anthropics
12020

systematic-debugging

4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.

root-cause-analysistroubleshootingverificationbest-practices
xenitV1
xenitV1
10917

geo-fundamentals

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

generative-aiprompt-engineeringretrieval-augmented-generation
xenitV1
xenitV1
10917

brainstorming

Socratic questioning protocol + user communication. MANDATORY for complex requests, new features, or unclear requirements. Includes progress reporting and error handling.

ideationclarificationstatus-reportserror-handling
xenitV1
xenitV1
10917

behavioral-modes

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

behavioral-guidelineprompt-engineeringagent-orchestrationworkflow-design
xenitV1
xenitV1
10917

Lightweight Implementation Analysis Protocol

This skill should be used when fixing bugs, implementing features, debugging issues, or making code changes. Ensures understanding of code flow before implementation by: (1) Tracing execution path with specific file:line references, (2) Creating lightweight text diagrams showing class.method() flows, (3) Verifying understanding with user. Prevents wasted effort from assumptions or guessing. Triggers when users request: bug fixes, feature implementations, refactoring, TDD cycles, debugging, code analysis.

code-analysisdebuggingflowchartdiagram-generation
NTCoding
NTCoding
11112

TDD Process

Strict test-driven development state machine with red-green-refactor cycles. Enforces test-first development, meaningful failures, minimum implementations, and full verification. Activates when user requests: 'use a TDD approach', 'start TDD', 'test-drive this'.

test-driven-developmentsoftware-development-processred-green-refactortest-first-development
NTCoding
NTCoding
11112

Independent Research

Research-driven investigation skill for validating solutions and exploring documentation. Never ask questions you can answer yourself through research. Use WebFetch, WebSearch, and testing to validate ideas before presenting them. Deliver concrete, tested recommendations with evidence.

scientific-inquiryresearch-methodologyweb-searchtesting
NTCoding
NTCoding
11112

Observability-First Debugging

Systematic debugging methodology that eliminates guessing and speculation. Add instrumentation to gather specific data that fully explains the problem. Evidence before hypothesis. Observation before solution.

observabilityinstrumentationtroubleshootingroot-cause-analysis
NTCoding
NTCoding
11112

prompt-authoring

Guidance for creating effective prompts, chains, and gates using CAGEERF methodology

prompt-engineeringprompt-generationprompt-refinementprompt-chaining
minipuft
minipuft
12628

prompt-optimizer

Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.

prompt-refinementprompt-engineeringrequirements-gatheringspecification-documents
daymade
daymade
15713

iterative-development

Ralph Wiggum loops - self-referential TDD iteration until tests pass

test-driven-developmentunit-testingtest-automationiterative-development
alinaqi
alinaqi
28724

commit-hygiene

Atomic commits, PR size limits, commit thresholds, stacked PRs

gitversion-controlpull-requestsatomic-commits
alinaqi
alinaqi
28724

aeo-optimization

AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

retrieval-augmented-generationknowledge-graphtemplatessemantic-triples
alinaqi
alinaqi
28724

base

Universal coding patterns, constraints, TDD workflow, atomic todos

test-driven-developmentdesign-patternsbest-practicescoding-patterns
alinaqi
alinaqi
28724

ask-questions-if-underspecified

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

requirements-gatheringspecification-documentsclarity-adjustment
skillcreatorai
skillcreatorai
41431

ai-prompting

Effective communication strategies for AI-assisted development. Learn context-first prompting, phased interactions, iterative refinement, and validation techniques to get better results from Claude and other AI coding assistants.

prompt-engineeringprompt-refinementcontext-engineeringclaude-skills
Kiro Team
Kiro Team
457140

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