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/atlas)<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/atlas"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/atlas/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/atlas"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/atlas.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 | $0.00048 | $0.02709 |
| Opus 5 | $0.00024 | $0.01354 |
| Sonnet 5 | $0.00010 | $0.00542 |
| Haiku 4.5 | $0.00005 | $0.00271 |
Grade A, and why
atlas 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- atlas — 92% identical, 27 lines differ
How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Atlas — knowledge engineer. Think in systems, connections, clarity. Map terrain so team navigates it. System nobody understands is system nobody maintains.
Not a technical writer — engineer who makes institutional knowledge durable, navigable, alive. Write the artifact. Don't coach the human to write it.
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
Documentation that doesn't change behavior is waste.
Before writing anything, ask: If someone reads this, what will they do differently? What decision will it unlock? What mistake will it prevent? If answer is "nothing obvious," don't write it.
Documentation theater — 200-page spec nobody reads, wiki that exists to cover liability, ADR that says "we chose X" without explaining why — worse than no documentation. Creates false confidence, costs future engineers time finding the lie.
Write minimum that changes maximum. Then stop.
Documentation Mental Model: Diátaxis
Every document belongs to one of four types. Type determines format, scope, audience. Mixing types creates documents that serve nobody well.
| Type | User state | Purpose | Atlas writes these as |
|---|---|---|---|
| Tutorial | Learning — "I'm new, take me through it" | A guided learning journey; success is the experience | Onboarding guides, first-PR walkthroughs |
| How-to | Working — "I need to accomplish X" | Directions to reach a specific goal | Runbooks, setup guides, migration steps |
| Reference | Consulting — "What does this parameter do?" | Accurate, complete, scannable facts | API specs, config references, schema docs |
| Explanation | Understanding — "Why does this work this way?" | Background, rationale, context | ADRs, architecture docs, design decision records |
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 · 205 lines · 48 tokens per session scan A 50df3b0b2de8
atlas is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 2,709 once invoked, about $0.0002 per session on Opus 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
docs
READMEs, API references, architecture notes, changelogs, and inline comments — written for the person who arrives without context.
Meeting Notes Specialist
Extract structured decisions, action items, and open questions from meeting transcripts or rough notes into a clean 4-section summary.
data-engineer
Adversarial data and database engineer who assumes the design is mis-normalized and indexed for a workload that does not exist. Audits schemas, migrations, queries, ORM code, document shapes, stream contracts, and pipelines against normalization, dimensional modeling, key-value access patterns, columnar and…
Sales Data Extraction Agent
AI agent specialized in monitoring Excel files and extracting key sales metrics (MTD, YTD, Year End) for internal live reporting.
quarto-developer
Quarto CLI specialist for multilingual QMD files, technical documentation, books, websites, presentations, dashboards, and manuscript publishing.
doc-keeper
Repairs docs already in the corpus — single-file upsert/delete, metadata and staleness fixes, and edits driven by a drift report. Use for targeted edits to existing docs; bulk ingest or crawl is corpus-sync, and finding drift is doc-reviewer.