Analyze prompt cache hit rates, estimate cost savings from cached system prompts and memories, and recommend improvements to caching strategy. Use when checking cache performance, investigating high token costs, optimizing cache hit rates, or diagnosing slow cache warmup.
Manage Serena memories and session context — load, save, refresh, inspect, and clear project knowledge
Initialize Claude Code optimization for a new project — detect stack, create memories, generate constitution, configure settings
Reduce token usage by selecting a planning strategy, loading Serena memories, enforcing symbol-first exploration, and reporting savings. Use when starting a non-trivial task, asking to reduce token costs, requesting efficient execution, or wanting optimized Claude Code workflows.
Search the web for latest Claude API changes, compare findings to existing documentation, and apply targeted updates to keep prompts and configs current. Use when docs are outdated, after a Claude API update, to refresh system prompts, or to validate documentation accuracy.
Close the loop on a skill/prompt/convention library: mine recurring review feedback into rules, fold them back into the generator, and gate every change through a three-tier evaluation (deterministic lint + trigger accuracy + LLM judge) that converges instead of drifting. Use when a correction keeps recurring across skills/PRs, when adding or revising skills warrants a quality gate, or when asked to "harden the skill library", "run the eval", "lint skills", or "close the loop". Composes with your existing execution, memory, and governance layers.
Preserve the OPERATIONAL THREAD across coding sessions with a repo-local, inspectable .continuity/ surface and a resume -> work -> finalize lifecycle. Not another memory store — a thin lifecycle layer over the memory you already have. Use at the START of substantial work on a repo ("resume", "where were we", "pick up") and at the END ("finalize", "hand off", "wrap up") so the next session starts from bounded, evidence-weighted state instead of re-orienting from scratch. Complements (never replaces) Serena/Svod/codebase-memory/auto-memory.
Audit the current project's website for AI-agent readiness using Cloudflare's isitagentready.com scanner (robots.txt, sitemap, llms.txt, Link headers, Content Signals, Markdown-for-Agents, MCP / OAuth / A2A / Agent-Skills discovery, agentic commerce), triage which gaps are actually worth fixing for THIS kind of site, then implement the worthwhile ones in the project's own stack and re-scan to verify. Use when the user wants to check or improve agent readiness, run "is it agent ready", add an llms.txt / MCP card / agent discovery endpoints, or "make my site agent-ready".