Skills from muratcankoylan/Agent-Skills-for-Context-Engineering: 23 agent skills
advanced-evaluation — This skill should be used for advanced LLM evaluation: LLM-as-judge systems, direct scoring, pairwise comparison, rubric calibration.
bdi-mental-states — This skill should be used when modeling agent mental states with BDI concepts: beliefs, desires, intentions, RDF-to-belief transformations.
book-sft-pipeline — This skill should be used for book-to-SFT pipelines: ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training.
comprehensive-research-agent — Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
context-compression — This skill should be used when long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization.
context-degradation — This skill should be used for diagnosing and mitigating context degradation: lost-in-middle failures, context poisoning, context clash, context confusion.
context-engineering-collection — A comprehensive collection of Agent Skills for context engineering, harness engineering, multi-agent architectures, and production agent systems.
context-fundamentals — This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window.
context-optimization — This skill should be used for improving context efficiency: context budgeting, observation masking, prefix or KV-cache strategy, partitioning.
digital-brain — This skill should be used for personal operating-system workflows: content creation, voice consistency, relationship lookup, meeting preparation.
evaluation — This skill should be used when building agent evaluation systems: deterministic checks, regression suites, multi-dimensional rubrics, quality gates.
filesystem-context — This skill should be used when agent work needs file-backed context: durable scratchpads, tool-output offloading, just-in-time discovery.
harness-engineering — This skill should be used when designing autonomous agent harnesses: research loops, evaluation scaffolds, locked and editable surfaces, durable logs.
hosted-agents — This skill should be used when designing hosted or background agent infrastructure: sandboxed execution, remote coding environments, warm pools.
latent-briefing — This skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context".
memory-systems — This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity.
multi-agent-patterns — This skill should be used when designing multi-agent systems that need context isolation, supervisor or swarm coordination, explicit handoffs.
project-development — This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand.
reasoning-trace-optimizer — Debug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task failures.
self-improvement-loops — This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops.
skill-template — Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection.
tool-design — This skill should be used for the tool-interface layer of an agent system specifically: writing tool descriptions agents can route on.