Distributed Rate Limiting with Redis Token Bucket
Verified SecureCreated by Upstash•security Workflow
Protect APIs against credential stuffing, brute force, and DoS using Redis rate limiters.
npx askills install rate-limiting-token-bucket-redis
Client Trigger & Invocation Simulator
$rate-limiting-token-bucket-redis <your task>Type `$rate-limiting-token-bucket-redis` in the chat or invoke via natural language. Codex automatically identifies the skill from ~/.agents/skills or project .skills, mounts bundled scripts, and executes inside the workspace sandbox.
$rate-limiting-token-bucket-redis Implement an API rate limiter capping free tier users at 60 requests per minute with Redis.
Overview & Problem Solved
When modern frontier LLMs (like Claude 3.7, GPT-4o, or deep reasoning agents) execute complex domain tasks without standard operating procedures, they frequently suffer from context drift, incorrect CLI arguments, or non-standard file hierarchies. Distributed Rate Limiting with Redis Token Bucket eliminates probabilistic guessing by supplying the Agent with an authoritative, sandboxed execution specification.
By packaging verified workflows into a structured SKILL.md manifest, this skill establishes deterministic boundaries, verifies dependencies, and executes tasks using proven engineering conventions.
Operational Impact: Without Skill vs. With Skill
Raw frontier models possess deep knowledge, but probabilistic prompting lacks rigid engineering guardrails. Packaging Distributed Rate Limiting with Redis Token Bucket into a verified SKILL.md transforms speculative model behavior into reproducible, deterministic delivery.
- Speculative CLI Flags: Model guesses experimental command arguments or deprecated API endpoints.
- Lazy Placeholder Code: Outputs
// TODO: implement error handlingor skips critical verification phases. - Directory Pollution: Generates non-standard file structures that break existing project linters and monorepo roots.
- Extraneous Context Bloat: Wastes thousands of output tokens on narrative pleasantries rather than verified deliverables.
function process() {
// TODO: Connect database here
console.log("Done");
}- Codified Workflow Stages: Follows strict step-by-step algorithms explicitly codified in SKILL.md.
- Zero-Placeholder Delivery: Every deliverable is 100% implemented, with complete error boundaries and types.
- Automatic Pre-Flight Check: Agent inspects environment dependencies (Python/Node/Docker) before modifying files.
- Self-Healing Verification: Runs automated linting, test suites, or syntax parsers before concluding the turn.
export async function execute() {
const validated = schema.parse(input);
return await auditAndPersist(validated);
}Core Capabilities & Guarantees
Follows pre-tested instructions and step-by-step algorithms, avoiding experimental or hallucinated flags.
Runs with identical behavioral fidelity across OpenAI Codex, Claude Code, Cursor IDE, and Windsurf Cascade.
Enforces workspace-scoped file mutations and shields environment secrets against accidental prompt leakage.
Automates test verification, linter checks, and syntax validation before completing any user turn.
Agent Execution Pipeline
Intent Matching & Context Ingestion
The agent scans the user request against the skill's YAML frontmatter triggers and loads the verified instructions into active working memory.
Toolchain & Dependency Validation
The runtime verifies that necessary tools, interpreters, and environment configurations exist within the workspace sandbox before proceeding.
Deterministic Execution & Delivery
The agent executes the codified SOP, runs verification checks, and outputs high-fidelity deliverables without extraneous narration.
Validated Prompt Templates
(Click to copy)“Implement an API rate limiter capping free tier users at 60 requests per minute with Redis.”
“Protect a login endpoint against credential stuffing by limiting attempts to 5 per IP per minute.”
“Return standardized 429 Too Many Requests responses with Retry-After and X-RateLimit headers.”
Automated Security & Audit Report
Workspace Scoped
Cannot escape workspace rootInstruction Only
Zero system subprocessesOffline Sandbox
No internet egressNone Required
Runs fully standaloneEnterprise & Production Use Cases
Frequently Asked Questions
Q: What makes Distributed Rate Limiting with Redis Token Bucket different from a standard MCP server?
MCP (Model Context Protocol) provides external protocol connections to databases or APIs. In contrast, Distributed Rate Limiting with Redis Token Bucket is a high-level operational skill (SKILL.md) that teaches AI Agents procedural intelligence, deterministic step-by-step SOPs, parameter constraints, and self-correction workflows.
Q: Is Distributed Rate Limiting with Redis Token Bucket compatible with frontier models like Claude 3.7 Sonnet, GPT-4o, and DeepSeek-R1?
Yes. The skill is packaged with standard markdown instructions (SKILL.md) and YAML frontmatter, adhering to the universal agent skill standard natively supported across Codex, Claude Code, Cursor, and Windsurf.
Q: What permissions does Distributed Rate Limiting with Redis Token Bucket require in agent mode?
Every listed skill undergoes automated static analysis scoring 98/100. It strictly adheres to workspace-scoped filesystem boundaries and does not execute untrusted remote code.
Q: Can our team customize or extend the rules in this SKILL.md?
Yes. Once installed in your project root (.skills/rate-limiting-token-bucket-redis/SKILL.md or ~/.agents/skills/rate-limiting-token-bucket-redis/), you can customize the instructions to include internal team guidelines, custom linters, or proprietary APIs.
SKILL.md Source Specification
---
name: "rate-limiting-token-bucket-redis"
description: "Protect APIs against credential stuffing, brute force, and DoS using Redis rate limiters."
metadata:
author: "Upstash"
version: "1.0.0"
runtime_compatibility:
- "codex"
- "claude-code"
- "cursor"
- "windsurf"
triggers:
- "implement redis rate limiting"
- "sliding window rate limiter"
- "prevent brute force login"
permissions:
fs_read: true
fs_write: "workspace"
shell_exec: false
net_access: false
---
# Distributed Rate Limiting with Redis Token Bucket
Implements distributed rate limiting algorithms (Token Bucket, Sliding Window Counter) in Redis: tracking request quotas per IP and API token, emitting 429 Too Many Requests, and Retry-After headers.
## When to Invoke
Invoke this skill whenever you need to:
- implement redis rate limiting
- sliding window rate limiter
- prevent brute force login
## Execution SOP & Rules
1. Use atomic Redis multi/exec or Lua scripts to prevent concurrency race conditions.
2. Apply sliding window counter algorithms to prevent burst traffic spikes at window boundaries.
3. Include standard rate limit response headers (X-RateLimit-Limit, X-RateLimit-Remaining).
4. Whitelist trusted internal microservice IP addresses and health check probes.
## Verification Checklist
- Run local linting, syntax validation, and type-checks before reporting completion.
- Ensure all created or modified files adhere to workspace boundaries and avoid uncommitted secrets.
- Verify tests or build commands exit cleanly with return code 0.
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