specsmith: Skill for Claude Code

.agents/skills/vllm-integration/SKILL.md

vllm-integration is a skill for Claude Code, Codex from layer1labs/specsmith. It costs 22 tokens per session (390 once invoked), scanned A, original, MIT.

An integration guide for vLLM, a tool that serves large language models through an API. It covers model deployment, hardware resources, optimization, configuration, monitoring, and governance approvals.

In plain words
What is it for?
It helps configure model paths and GPU or CPU resources, deploy models, set API ports, and monitor performance and usage.
Why use it?
It provides a defined way to run vLLM models while requiring human approval and recording configuration, security, and resource controls.

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 layer1labs/specsmith's own configuration. It tells Claude Code and Codex how to work on specsmith 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 specsmith configures →

Reuse

Borrowing it

Nothing to install: this file belongs to layer1labs/specsmith. 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/layer1labs/specsmith/main/.agents/skills/vllm-integration/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/layer1labs/specsmith

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 vllm-integration

README.md
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Your own site
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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 vllm-integration

Your own site · 80×15
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Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 390 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 original No closer match found 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 $0.00022 $0.00390
Opus 5.5 $0.00009 $0.00156
Sonnet 5.5 $0.00004 $0.00078
Haiku 4.5 $0.00002 $0.00039

Measured 2mo ago against content hash f55cccdfdac9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

vllm-integration 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 2mo 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.

.agents/skills/vllm-integration/SKILL.md · 68 lines

What it actually says

VLLM Platform Integration

This skill enables specsmith projects to integrate with VLLM for large language model serving while maintaining governance compliance.

Requirements Covered

  • REQ-110: VLLM Platform Integration
  • Allows specsmith projects to integrate with VLLM for large language model serving with human approval

Integration Capabilities

Platform Features

  • VLLM model serving and deployment
  • GPU and CPU resource management
  • Model optimization and quantization
  • API endpoint configuration for VLLM services
  • Performance monitoring and tuning

Governance Requirements

  • Human approval required for all VLLM integrations
  • Configuration management with governance controls
  • Security best practices enforcement
  • Resource monitoring and logging

Usage Examples

# Initialize VLLM integration
specsmith skill install vllm-integration

# Configure VLLM platform settings
specsmith vllm configure --platform vllm --model-path /path/to/model --gpu-count 2

# Deploy model via VLLM
specsmith vllm deploy --model my-model --port 8000

Configuration

The skill requires the following configuration in scaffold.yml:

vllm:
  platform: vllm
  model_path: /path/to/models
  gpu_count: 2
  port: 8000
  quantization: "none"

Security Considerations

  • All VLLM integrations require human approval
  • Model access controls must be configured
  • Network security must be enforced
  • Resource usage monitoring is required

Compliance Requirements

  • Follow security best practices for AI platform integrations
  • Maintain audit logs of all VLLM interactions
  • Ensure proper resource management and monitoring
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. 2mo ago First seen · 68 lines · 22 tokens per session scan A f55cccdfdac9

Subscribe to this mod's changes

vllm-integration is a skill published in the GitHub repository layer1labs/specsmith (8 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 390 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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