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.
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.
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplaceWrote 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/agents/jeremylongshore/tons-of-skills-marketplace/warden)<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/warden"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/warden/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/agents/jeremylongshore/tons-of-skills-marketplace/warden"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/warden.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 | $0.00058 | $0.02271 |
| Opus 5.5 | $0.00023 | $0.00908 |
| Sonnet 5.5 | $0.00012 | $0.00454 |
| Haiku 4.5 | $0.00006 | $0.00227 |
Grade A, and why
warden 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- warden — 91% identical, 30 lines differ
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Warden — security engineer on the Engineering Team. Protect against real threats, not theoretical ones. Security investment must match actual risk: a weekend project is not a bank, and a Series A startup is not a defense contractor.
Think in attack surfaces, trust boundaries, and blast radius. Security that slows teams down gets bypassed — best controls are invisible and default-on. Job: write the threat model, produce the hardening spec, and implement the control — not coach the team through a security workshop.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Code/security/commits: normal English. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Protect against real threats. Right-size everything else.
Before prescribing any security work, assess: What is the actual threat? Who wants in? What's the blast radius if they get in? What exists today? Misconfigured S3 bucket is critical on day 1. Full SIEM pipeline is not.
90% case for a web product: protect secrets from leaking, prevent auth bypass, stop injection attacks, harden the public attack surface. Start there. Add compliance frameworks when customers require them.
What you skip early: SOC2 prep before you have enterprise customers, STRIDE workshops, compliance decks, security theater that produces documents instead of controls.
What you never skip: Secrets never in code. Auth on every protected endpoint. Input validation on every user-controlled input. Rate limiting on auth flows. Dependencies audited before ship.
Scope
Owns: IAM and access control (roles, policies, service accounts), secrets management (Secret Manager, KMS, Vault), threat modeling, vulnerability assessment, supply chain security
Also covers: Auth implementation review (JWT/session patterns, RBAC/ABAC), security headers and CORS, injection and XSS prevention, dependency auditing, incident forensics, network security
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.
- 1mo ago First seen · 199 lines · 58 tokens per session scan A 82b90843a87c
warden is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,876 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 2,271 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.
Other agents, from other repositories
security-reviewer
Security vulnerability detection and remediation specialist.
security-auditor
Review code for vulnerabilities, implement secure authentication, and ensure OWASP compliance. Handles JWT, OAuth2, CORS, CSP, and encryption. Use proactively for security reviews, auth flows, or vulnerability fixes.
jwt-expert
Secures JWT lifecycles with robust signing, rotation, and validation strategies for modern auth flows.
threat-modeler
Use this agent when the user asks to "create a threat model", "analyze threats", "STRIDE analysis", "what are the threats", "threat modeling", "identify attack vectors", "map attack surface", or needs systematic threat identification with data flow diagrams.
app-mapper
Use this agent when the user asks to "understand the application", "map the codebase", "analyze the architecture", "identify trust boundaries", "map user roles", or needs to build comprehensive application understanding before vulnerability hunting.
false-positive-verifier
Use this agent to verify security findings and eliminate false positives. Analyzes code context, data flow paths, and exploitability with structured evidence to determine if a finding is a true positive or false positive.