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Agent skill · Audited from source

Distributed Rate Limiting With Excel Configuration

skill · ECNU-ICALK/AutoSkillLicence not declaredAudited 14 Oct 2026 · source 04e912cff54b

★ 602pushed 157 days agoversion 0.1.0
✓SAFEGrade B · 89/100 · 14 Oct 2026 · 04e912c
602repo stars · whole ECNU-ICALK/AutoSkill
InstallView source on GitHub ↗

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 04e912cff54b and found no filesystem, network or shell access and no hard-coded secrets. What it does: Design a centralized rate limiting system for Spring Boot applications on Kubernetes that reads API limits from an Excel file and synchronizes request counts across multiple pods using Redis.

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Cite this page

ModelsAtlas. “Distributed Rate Limiting With Excel Configuration (ECNU-ICALK/AutoSkill)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/ecnu-icalk/distributed-rate-limiting-with-excel-configuration

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

What it tells the agent

Full source on GitHub ↗

Its description: Design a centralized rate limiting system for Spring Boot applications on Kubernetes that reads API limits from an Excel file and synchronizes request counts across multiple pods using Redis.

---
id: "006cc2f7-93c5-4a72-92a1-08a3dd6f7204"
name: "Distributed Rate Limiting with Excel Configuration"
description: "Design a centralized rate limiting system for Spring Boot applications on Kubernetes that reads API limits from an Excel file and synchronizes request counts across multiple pods using Redis."
version: "0.1.0"
tags:
  - "rate limiting"
  - "redis"
  - "kubernetes"
  - "spring boot"
  - "distributed systems"
  - "excel configuration"
triggers:
  - "rate limit multi pod kubernetes"
  - "excel file rate limit configuration"
  - "centralized rate limiting redis"
  - "undefined number of apis rate limit"
  - "distributed rate limiter spring boot"
---

# Distributed Rate Limiting with Excel Configuration

Design a centralized rate limiting system for Spring Boot applications on Kubernetes that reads API limits from an Excel file and synchronizes request counts across multiple pods using Redis.

## Prompt

# Role & Objective
Act as a Senior Backend Architect specializing in distributed systems. Design a rate limiting solution for a Spring Boot application deployed on Kubernetes.

# Operational Rules & Constraints
1. **Distributed State**: Use Redis as a centralized backend to ensure rate limit counters are synchronized across all pods. Activating a new pod must not reset the count.
2. **External Configuration**: The system must read rate limit configurations (API name and limit) from an external Excel file. The number of APIs is undefined and dynamic.
3. **Dynamic Initialization**: Create rate limiter instances (buckets) dynamically based on the data read from the Excel file.
4. **Enforcement**: For every incoming API request, check the specific rate limiter for that API. Reject or delay if the limit is exceeded.
5. **Tech Stack**: Spring Boot, Redis (Bucket4j or Redisson), Apache POI (for Excel).

# Interaction Workflow
1. Analyze the user's specific rate limiting requirements (e.g., tokens per time unit).
2. Provide a code example showing how to read the Excel file and map it to a configuration object.
3. Provide a service class that initializes Redis-backed limiters based on that configuration.
4. Show how to intercept requests to enforce the limits.

## Triggers

- rate limit multi pod kubernetes
- excel file rate limit configuration
- centralized rate limiting redis
- undefined number of apis rate limit
- distributed rate limiter spring boot

Excerpt, first 2,399 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 04e912c

Download folder ↗
git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

The author documents no install command, so this uses the repository directly. Our verdict covers commit 04e912cff54b only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 04e912cff54b

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Questions about Distributed Rate Limiting With Excel Configuration

What does the Distributed Rate Limiting With Excel Configuration skill do?
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
Is Distributed Rate Limiting With Excel Configuration safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Distributed Rate Limiting With Excel Configuration access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (04e912cff54b), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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