Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add eric861129/SKILLS_All-in-one --skill refactor-modulegit clone --depth 1 https://github.com/eric861129/SKILLS_All-in-oneWrote 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.
[](https://agentmods.dev/skills/eric861129/skills_all-in-one/refactor-module)<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/refactor-module"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/refactor-module/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.
<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/refactor-module"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/refactor-module.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.03464 |
| Opus 5 | $0.00014 | $0.01732 |
| Sonnet 5 | $0.00006 | $0.00693 |
| Haiku 4.5 | $0.00003 | $0.00346 |
Grade A, and why
refactor-module 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 9d 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.
This is a copy
100% identical to refactor-module — 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.
How it starts
The opening of the file, as written. The whole thing — 539 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Refactor Module
Overview
This skill guides AI agents in transforming monolithic Terraform configurations into reusable, maintainable modules following HashiCorp's module design principles and community best practices.
Capability Statement
The agent will analyze existing Terraform code and systematically refactor it into well-structured modules with:
- Clear interface contracts (variables and outputs)
- Proper encapsulation and abstraction
- Versioning and documentation
- Testing frameworks
- Migration path for existing state
Prerequisites
- Existing Terraform configuration to refactor
- Understanding of resource dependencies
- Access to current state file (for migration planning)
- Knowledge of module registry patterns
Input Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
source_directory |
string | Yes | Path to existing Terraform configuration |
module_name |
string | Yes | Name for the new module |
abstraction_level |
string | No | "simple", "intermediate", "advanced" (default: intermediate) |
preserve_state |
boolean | Yes | Whether to maintain state compatibility |
target_registry |
string | No | Target module registry (local, private, public) |
Execution Steps
1. Analysis Phase
**Identify Refactoring Candidates**
- Group resources by logical function
- Identify repeated patterns
- Map resource dependencies
- Detect configuration coupling
- Analyze variable usage patterns
**Complexity Assessment**
- Count resource relationships
- Measure variable propagation depth
- Identify cross-resource references
- Evaluate state migration complexity
2. Module Design
Interface Design
# Define clear input contract
variable "network_config" {
description = "Network configuration parameters"
type = object({
cidr_block = string
availability_zones = list(string)
enable_nat = bool
})
validation {
condition = can(cidrhost(var.network_config.cidr_block, 0))
error_message = "CIDR block must be valid IPv4 CIDR."
}
}
# Define output contract
output "vpc_id" {
description = "ID of the created VPC"
value = aws_vpc.main.id
}
output "private_subnet_ids" {
description = "List of private subnet IDs"
value = { for k, v in aws_subnet.private : k => v.id }
}
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.
- 9d ago First seen · 539 lines · 28 tokens per session scan A 51357bb86eb4
refactor-module is a skill published in the GitHub repository eric861129/SKILLS_All-in-one (52 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 3,464 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to refactor-module, differing in 0 lines, and is treated as a copy.
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