Results for “bounded-context”

10 skills

Load bounded working context at the start of a coding session. FIRES ON EVERY FIRST USER MESSAGE in a fresh session, regardless of content — including bare greetings ("hi", "hello", "hey"), task-only openers, or "let's start". Also triggers on: "fresh session", "session start", "first message in a new thread", "new chat", "cold start", "begin work in this repo", "starting work", "continue from prior session", "what were we working on", "resume", "what happened last time", "load memory", "recall context", "create a handoff", "prior session context", "latest handoff", "current state", "decision context". Skip ONLY if the user explicitly says "fresh start" or "ignore prior context". Self no-ops if invoked mid-session when context is already loaded.

More results

context-optimization

Extends effective context capacity through strategic compression, masking, caching, and partitioning techniques.

16.9k · bundle

task-handoff-context

Select evidence-bearing context for a downstream consumer after work when claims, artifacts, validation, unresolved decisions, or omissions must cross a boundary.

analyze-context

Breaks down current state, context, user input, and data into a structured assessment before taking action.

context-engineering-advisor

Diagnose whether an AI workflow suffers from context stuffing or benefits from context engineering, and apply structured techniques to improve reliability.

task-context-selection

Selects a minimal, non-redundant set of facts, artifacts, skills, and references for a working decision when context is stale, uncertain, or over budget.

context-compression

Optimizes long-running agent sessions with structured context compression, summarization, and durable handoff summaries that preserve decisions, files, risks, and next actions.

16.9k · bundle

context-engineering

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.

Frames tasks with explicit goals, success evidence, stop conditions, and boundaries before execution, then routes work to the appropriate workflow.