Run-aware token governance for multi-agent systems.
A budget-aware context compiler for coding agents - scan, grade, spark-test for secrets, and pour a hard-budget context pack with a stamped manifest.
Cross-agent skill quality gate for SKILL.md files. Validates frontmatter, scores description discoverability, checks file references, enforces three-tier token budgets, and flags compatibility issues across Claude Code, VS Code/Copilot, Codex, and Cursor.
Code intelligence for agents: find the code that matters and keep your context window and tokens lean.
让 Agent 高效又守纪律 — 不止省 token：ZeroToken 压缩无效上下文/推理/输出；尉缭子十原则约束权限边界、单一指令、先谋后动、验证先于结束；附 Unicode 编码规范、搜索规范、六种任务模式。More than token savings: ZeroToken efficiency + AI coding discipline for Reasonix / Codex / OpenCode / Hermes
GenPark AI Agent Skill - Multi-tenant token budget tracker, sliding-window rate limiter, and model pricing ledger.
GenPark AI Agent Skill - Multi-tenant token budget tracker, sliding-window rate limiter, and model pricing ledger.
Self-hosted spend firewall and gateway for LLM ( OpenAI / Anthropic / Gemini ). Hard per-user & per-project budget caps that block runaway costs before the API call, plus cost-per-customer tracking, semantic caching, and failover. One line of code, single Go binary.
Open-source platform for deterministic, token-aware context selection for AI agents and LLMs
Coding agents forget your repo. mcp-brain is the missing memory layer — repo-aware, team-aware, lifecycle-aware. 63% Hit@10, zero LLM cost. Works with any MCP client.
Runtime containment kernel for LLM agents. Enforces budget, step, retry, and circuit-breaker limits before the model call.
Don't go into production without these - 3 auto-triggering Claude Code skills for cost and drift prevention. 6 months of practitioner notes.
A drop-in SKILL that forces AI coding agents (Claude Code, Codex, Cursor, Cline, Roo, Windsurf, Copilot, Augment, Aider, …) to deliver exactly what was asked — minimum diff, zero unsolicited files, terse output by default.
Simulate value-aware token allocation across a task tree, choosing model tiers or preempting tasks within a declared budget.
Embeddable, zero-dependency durable execution for agents and NHEs. Deterministic replay, retries, cycle detection, a token budget, and a multi-agent task board, with no sidecar service.
Open source AI cost tracking. Know exactly what your AI costs — per feature, per user, per project.
Constant token budget for long-form LLM writing. Chapter 1000 costs the same as chapter 10 (61,331 → 4,396 tokens measured). Zero dependencies, runs on Cloudflare Workers.
TypeScript SDK that adds cost limits, token/call budgets, timeouts, and circuit breakers to AI agent/LLM workflows, with adapters for OpenAI, Anthropic, Vercel AI, and observability/reporting support.
Zero-dependency context-window packer for LLM chat: fit a conversation into a token budget (middle-out, drop-oldest, priority, pinning).
Core library: scoring, selection, and caching for the Context Engine
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