← ClaudeAtlas

context-engineeringlisted

Workflow for context packets, context audits, compaction, handoffs, session memory, and deciding what AI-agent context to load, retrieve, trim, summarize, refresh, or omit. Use for context rot, context flooding, stale or missing context, task switching, and long-running agent sessions. Do not use when prompt wording, repo file discovery for a story card, or AGENTS.md authoring is the main artifact.
n-n-code/n-n-code-skills · ★ 4 · AI & Automation · score 75
Install: claude install-skill n-n-code/n-n-code-skills
# Context Engineering Treat context as a finite working set. Load the smallest high-signal set of information that can produce the desired behavior, then refresh it as the task evolves. ## When To Use - prepare a focused context packet before an agent starts work - audit why an agent is hallucinating APIs, ignoring conventions, repeating mistakes, or losing the thread - decide what repo files, docs, examples, tool outputs, conversation history, or external references should be loaded now versus retrieved later - compact or hand off a long-running task without losing decisions, constraints, failures, or next actions - switch between major tasks and remove stale or irrelevant context ## Not For - rewriting a system prompt, developer prompt, few-shot examples, or structured output contract as the main artifact; use `prompt-engineering` - finding likely implementation files for a story card; use `story-repo-scout` - creating or revising repo-wide agent instructions; use `agents-md-generator` - broad approach comparison or product framing where context quality is not the main problem; use `thinking` - persistent project-document systems unless the user explicitly asks for one ## Core Workflow 1. **State the job.** Name the task, desired output, success signal, executor, available tools, risk level, and what failure would look like if context is wrong. 2. **Inventory candidate context.** List likely sources: user request, repo instructions, specs, source f