CampusMind-AI: Skill for Claude Code

.agents/skills/tools-resources-prompts/SKILL.md

nitrostack-tools-resources-prompts is a skill for Claude Code, Codex from Maheshdayyala/CampusMind-AI. It costs 48 tokens per session (2,316 once invoked), scanned A, a copy of nitrostack-tools-resources-prompts, MIT.

Development guidance for creating tools, data resources, and reusable prompts in NitroStack, an application framework for MCP servers. It uses Zod, a library for checking that inputs and outputs have the expected shape.

In plain words
What is it for?
Defining MCP tools, specifying and validating their inputs and outputs, adding automatic startup tools, and handling concerns such as caching, rate limits, and file uploads.
Why use it?
It helps keep agent-callable functions consistently named, documented, validated, and safely integrated with the application.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is Maheshdayyala/CampusMind-AI's own configuration. It tells Claude Code and Codex how to work on CampusMind-AI itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything CampusMind-AI configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Maheshdayyala/CampusMind-AI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Maheshdayyala/CampusMind-AI/main/.agents/skills/tools-resources-prompts/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Maheshdayyala/CampusMind-AI

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nitrostack-tools-resources-prompts

README.md
[![agentmods](https://agentmods.dev/badge/skills/maheshdayyala/campusmind-ai/tools-resources-prompts/github.svg)](https://agentmods.dev/skills/maheshdayyala/campusmind-ai/tools-resources-prompts)
Your own site
<a href="https://agentmods.dev/skills/maheshdayyala/campusmind-ai/tools-resources-prompts"><img src="https://agentmods.dev/badge/skills/maheshdayyala/campusmind-ai/tools-resources-prompts/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nitrostack-tools-resources-prompts

Your own site · 80×15
<a href="https://agentmods.dev/skills/maheshdayyala/campusmind-ai/tools-resources-prompts"><img src="https://agentmods.dev/badge/skills/maheshdayyala/campusmind-ai/tools-resources-prompts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,316 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.02316
Opus 5 $0.00024 $0.01158
Sonnet 5 $0.00010 $0.00463
Haiku 4.5 $0.00005 $0.00232

Measured 11d ago against content hash 6afc492e781b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nitrostack-tools-resources-prompts scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to nitrostack-tools-resources-prompts — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/tools-resources-prompts/SKILL.md · 288 lines

How it starts

The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to Use

Use this skill whenever you are defining, editing, or validating tools, resources, or prompts on a NitroStack MCP server.

Defining Tools with @Tool

An MCP tool exposes a function that an AI client can invoke. Decorate a service or controller method with @Tool.

Key Tool Options:

  • name: Kebab-case or snake_case unique identifier.
  • description: Detailed description explaining when and how the client should use it.
  • inputSchema: A Zod object schema for strict validation of inputs.
  • outputSchema (optional): Zod schema validating the output structure.
import { ToolDecorator as Tool, ControllerDecorator as Controller, InitialTool, z, ExecutionContext } from '@nitrostack/core';

@Controller('weather')
export class WeatherService {
  @Tool({
    name: 'get_current_weather',
    description: 'Get the current weather forecast for a specific city.',
    inputSchema: z.object({
      city: z.string().describe('The name of the city, e.g., San Francisco'),
      unit: z.enum(['celsius', 'fahrenheit']).default('celsius'),
    }),
  })
  @InitialTool() // Auto-invoked when the AI client initializes/starts
  async getWeather(
    input: { city: string; unit: 'celsius' | 'fahrenheit' },
    ctx: ExecutionContext
  ) {
    ctx.logger.info(`Fetching weather for ${input.city}`);
    // implementation
    return {
      city: input.city,
      temp: 22,
      condition: 'Sunny',
    };
  }
}

Defining Resources with @Resource

An MCP resource exposes static or dynamic data files/URIs that the AI client can read.

Key Resource Options:

  • uri: URI pattern (e.g., git://{owner}/{repo}/file or static app://config).
  • name: Unique name of the resource.
  • description: Explanation of what data this resource provides.
  • mimeType: Mime type of the response (e.g., text/plain, application/json).
import { Resource, ExecutionContext } from '@nitrostack/core';

export class ConfigResources {
  @Resource({
    uri: 'app://settings',
    name: 'Application Settings',
    description: 'System-wide configuration settings and parameters.',
    mimeType: 'application/json',
  })
  async getSettings(ctx: ExecutionContext) {
    return {
      environment: 'development',
      debugMode: true,
    };
  }
}

Read the full file on GitHub · 288 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 288 lines · 48 tokens per session scan A 6afc492e781b

Subscribe to this mod's changes

nitrostack-tools-resources-prompts is a skill published in the GitHub repository Maheshdayyala/CampusMind-AI (0 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 2,316 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to nitrostack-tools-resources-prompts, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens