# report-needs

> report-needs — jarvisonm4-report-needs. Use this tool when you need to gather infrastructure requirements from AI agents, allowing them to report their specific needs directly. This tool solves the problem of inefficient resource allocation by providing a direct interface for agents to submit their requirements. It takes in agent reports as input and outputs actionable insights for infrastructure optimization.

Canonical page: https://skillsregistry.net/skills/jarvisonm4-report-needs  
JSON: https://api.skillsregistry.net/v1/skills/jarvisonm4-report-needs

## Description

MCP server for AI agents to report infrastructure needs. What do agents actually need? Let them tell you.

## Trust

- **Trust score (0–1):** 0.88
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/JarvisOnM4/report-needs)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jarvisonm4-report-needs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jarvisonm4-report-needs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jarvisonm4-report-needs/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt