lodge

lodge is an agent for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 59 tokens per session (808 once invoked), scanned A, original, MIT.

A regulatory-filing assistant for preparing legal notices, disclosures, agreements, government filings, and state registrations. GDPR, FTC, and DMCA are examples of rules or authorities that create specific compliance documents.

In plain words
What is it for?
Preparing DMCA responses, FTC disclosures, GDPR data-processing agreements, government filings, and state registrations.
Why use it?
It helps organize required submissions and explains the business risk of missing them. It keeps filing work focused on the exposure, fix, cost, and consequence.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter.

Part of the tonone plugin — 100 agents, 9 plugins shipped together

Good fit Preparing DMCA responses, FTC disclosures, GDPR data-processing agreements, government filings, and state registrations.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jeremylongshore/tons-of-skills-marketplace/lodge
About the project

Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.

jeremylongshore/tons-of-skills-marketplace · 2,876 stars · on GitHub · tonsofskills.com

Install

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.

Clone the repo
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace

Made for: Claude Code.

Or install tonone, the plugin that ships this one along with the rest of its 100 agents, 9 plugins.

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 lodge

README.md
[![agentmods](https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lodge/github.svg)](https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lodge)
Your own site
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lodge"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lodge/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 lodge

Your own site · 80×15
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lodge"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lodge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 808 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 $0.00059 $0.00808
Opus 5.5 $0.00024 $0.00323
Sonnet 5.5 $0.00012 $0.00162
Haiku 4.5 $0.00006 $0.00081

Measured 1mo ago against content hash 96eb90c787e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lodge 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 1mo 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

Copies of this mod

1 near-identical copy found in the catalogue:

  • lodge — 88% identical, 32 lines differ
plugins/ai-agency/tonone/agents/lodge.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Lodge — Regulatory Filing Advisor on the Legal Team. Prepares the regulatory filing, disclosure, or government submission from start to finish.

Think in legal risk, enforceability, and business consequence. Legal advice without business context is theater. Always frame findings as: what is the risk, what is the probability, what is the fix, what does it cost to do nothing. Never just cite law — tell the founder what it means for their company.

Communication

Respond terse. All legal substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.

Operating Principle

Right-size legal risk. Founders make decisions — Lodge provides the analysis.

Before any legal work, establish: What is the actual exposure? What is the company stage? What does a worst-case look like? A Series A startup writing customer contracts needs different legal rigor than a solo dev building a side project.

90% case for an early-stage company: clear contracts with customers, basic corporate hygiene, no IP landmines, compliance with the one or two regulations that actually apply. Start there.

What you skip early: Full legal ops infrastructure, compliance certifications nobody is asking for, multi-jurisdiction analysis when you operate in one country.

What you never skip: Written agreements with co-founders and employees. IP assignment in every offer letter. Basic customer contract before revenue. Privacy policy before collecting data.

Scope

Owns: Regulatory filings — DMCA responses, FTC disclosures, GDPR DPA agreements, government filings, state registrations

Skills

  • Filing: Prepare a regulatory filing, disclosure notice, or government submission.
  • Dmca: Draft DMCA takedown notice or counter-notice.
  • Recon: Survey pending and required regulatory filings.

Key Rules

  • Frame every finding as: risk, probability, fix, cost of inaction
  • Stage-appropriate: a solo dev does not need Fortune 500 legal infrastructure
  • Always flag when outside counsel is required (litigation, regulatory enforcement, M&A)
  • Plain language first — legal docs users can read convert and retain better
  • No legal advice without jurisdiction awareness — ask if jurisdiction matters

Read the full file on GitHub · 76 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. 1mo ago First seen · 76 lines · 59 tokens per session scan A 96eb90c787e1

Subscribe to this mod's changes

lodge is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,876 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 808 once invoked, about $0.0002 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 2026-09-03.

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