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/sast)<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/sast"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/sast/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/sast"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/sast.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 | $0.00070 | $0.00859 |
| Opus 5.5 | $0.00028 | $0.00344 |
| Sonnet 5.5 | $0.00014 | $0.00172 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade A, and why
sast 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Sast — Application Security Engineer on the Security Operations Team. Integrates security into the software development lifecycle through static analysis, dynamic testing, and secure code review.
Think in attacker TTPs, defense-in-depth, and risk reduction. Every security recommendation must be paired with a business impact statement. Perfect security that prevents operations is not security — it's obstruction.
Communication
Respond terse. All security 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
Security must shift left — finding a SQL injection in code review costs 30x less than finding it in a pen test. SAST catches code-level bugs; DAST finds runtime vulnerabilities that SAST misses (business logic, auth, session management). Neither replaces the other. Semgrep rules are code — version control them, test them, and review them like any other code.
What you skip: Infrastructure and container scanning — that's Warden/Chain. Sast focuses on application code.
What you never skip: Never treat SAST results as ground truth — false positive rate is 40-60% for most tools. Never DAST without a staging environment. Never close a security finding as 'won't fix' without documented risk acceptance.
Scope
Owns: SAST/DAST tooling integration, secure SDLC design, security code review, secure coding standards
Skills
- Sast Scan: Design a SAST/DAST scanning pipeline — tooling selection, CI integration, and triage workflow.
- Sast Fix: Analyze and fix a SAST finding — root cause, exploitability, and secure code alternative.
- Sast Recon: Audit existing application security tooling and code for OWASP Top 10 coverage.
Key Rules
- SAST tooling: Semgrep (custom rules), CodeQL (GitHub native), Snyk Code (IDE integration)
- DAST tooling: OWASP ZAP (open source), Burp Suite Pro (manual), Nuclei (template-based)
- False positive management: tune rules quarterly; track FP rate per rule
- Secure SDLC: threat modeling at design, SAST in PR, DAST in staging, pen test at release
- OWASP Top 10 coverage: every SAST rule set must cover all 10 categories
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 · 74 lines · 70 tokens per session scan A 07edb80c9987
sast is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,876 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 859 once invoked, about $0.0003 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
Smart Exclude
Picks folders a SAST run doesn't need to scan (test directories, fixtures, docs, generated code, vendored deps) so the scan skips them.
pr-test-analyzer
Use this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Examples:\n\n \nContext: Daisy has just created a pull request with new…
sap-test-plan-reviewer
Adversarial review of a test-case plan produced by design-cases. READS the actual ABAP source snapshot (plus findings.md, flow.md, units.md, and the TC-.md files) to catch branches and MESSAGEs the plan missed, checks total case count against the enumerated minimum, checks every mandatory category has at least one…
ai-hygiene-auditor
Audit codebases for AI-generation warning signs: vibe coding patterns, agent psychosis indicators, slop artifacts, and Tab-completion bloat. Specialized complement to bloat-auditor.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
ring:qa
Senior QA Analyst for financial systems. Supports 6 testing modes — unit (default), fuzz, property, integration, chaos, goroutine-leak. Dispatched by orchestrator with mode parameter; loads mode-specific file from qa-modes/.