slicing-long-contexts
Use when a prompt or corpus is long/dense (multi-docs, logs, codebases) and you want a reproducible map/reduce pipeline. Trigger this skill to slice inputs, run per-slice codex/gemini subcalls, and aggregate re...
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Use when a prompt or corpus is long/dense (multi-docs, logs, codebases) and you want a reproducible map/reduce pipeline. Trigger this skill to slice inputs, run per-slice codex/gemini subcalls, and aggregate re...
General skill authoring and improvement. Use when creating or updating any skill (with or without MCP), selecting structure, generating scaffolds, or packaging resources (scripts/references/assets/templates) th...
Build and run deterministic evaluation suites for agent workflows (single-turn or agentic). Use when you need reproducible eval runs with manifests, graders, metrics, and JSONL logs for capability or regression...
Fast environment briefing for agents and subagents. Use at session start to learn OS/shell, container/WSL/VM status, git repo + upstream + dirty state, Python venv status/locations, markdown folders to read, an...
Bidirectional planning for ambiguous or design-heavy tasks. Use when the user requests help breaking down a problem or formulating a plan, and also when an existing plan has too many gaps or needs refinement; c...
Audit tool integrations for deterministic behavior, error contracts, and logging before agents depend on them. Use when adding or updating tools or MCP servers.
Guide plan → instrument → execute → validate with explicit checkpoints and questions. Use for ambiguous tasks or when enforcing a consistent agent workflow.
Generates optimized prompts for AI professional developers through interactive clarification. Asks targeted questions to refine requirements, saves tokens, and ensures reliable outputs. Use when seeking the bes...
This skill should be used when the user asks to "setup conda environment", "configure Python environment", "activate conda automatically", "set conda environment for workspace", or mentions conda environment ac...
Generate clean C# code, Markdown files, agents, prompts, skills in MacroFlow.
Refine user intent through questions and context gathering in MacroFlow.
Orchestrate MacroFlow as a flow network for dynamic AI orchestration.
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Creates Agent Skills for Claude Code following official standards. Use when the user wants to create a Skill, teach Claude new capabilities, add specialized knowledge, or create reusable instructions. Keywords:...
Ruthless concision for AI prompts and context - "Not One Word Wasted"
Design, discover, and refactor multi-command workflows for Claude Code
Multi-disciplinary strategy council with 5 expert personas. Use for strategic analysis, impact assessment, complex decisions requiring diverse expertise. Includes cross-examination to identify contradictions be...
Lean code implementation pair. Claude (Smith) writes code, Gemini (Temper) reviews for bugs, security, and edge cases. ~2x token cost for high-quality code output.
Tree of Thoughts exploration for brainstorming and finding unknown unknowns. Recursively branches hypotheses, ranking by NOVELTY not probability. Use for idea generation, creative unblocking, exploring possibil...
Adversarial research validation using Red Team/Blue Team methodology. Use when researching complex topics, fact-checking claims, or producing research reports. Validates outputs through Gemini 3 Pro critic befo...
Instructions for selecting and configuring Gemini 3 Pro Preview model in Gemini CLI. Use when the user asks about switching models in Gemini CLI, enabling Gemini 3, or configuring Gemini CLI model settings.
3x3 Parallel Debate system for high-confidence research. Spawns 9 agent instances (3 Proposer/Skeptic/Judge cohorts) to argue, critique, and adjudicate claims. Use for complex queries, controversial topics, or...
Map-Reduce system for comprehensive reports and literature reviews. Breaks topic into chapters, researches each in parallel, then weaves into unified document. Use for deep research, reports, and synthesis.
Three-stage code implementation with planning. Gemini (Engineer) plans, Claude (Caster) implements, Gemini (Inspector) verifies. ~3x token cost for complex, multi-file changes.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.