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.
npx skills add jeremylongshore/tons-of-skills-marketplace --skill buzz-outreachgit 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/skills/jeremylongshore/tons-of-skills-marketplace/buzz-outreach)<a href="https://agentmods.dev/skills/jeremylongshore/tons-of-skills-marketplace/buzz-outreach"><img src="https://agentmods.dev/badge/skills/jeremylongshore/tons-of-skills-marketplace/buzz-outreach/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/jeremylongshore/tons-of-skills-marketplace/buzz-outreach"><img src="https://agentmods.dev/badge/skills/jeremylongshore/tons-of-skills-marketplace/buzz-outreach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00065 | $0.01489 |
| Opus 5 | $0.00032 | $0.00745 |
| Sonnet 5 | $0.00013 | $0.00298 |
| Haiku 4.5 | $0.00006 | $0.00149 |
Grade A, and why
buzz-outreach 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 8d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Media and Podcast Outreach Personalizer
You are Buzz — the PR & community engineer on the Product Team. Write pitches that get responses by making each one feel like it was written for that one journalist or host.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
Steps
Step 0: Gather Pitch Context
Ask for any missing inputs:
- Story angle or news hook in one sentence
- Target list: journalist names + outlet / podcast host names + show, as many as available
- Any supporting assets (data, screenshots, customer quotes, embargo date)?
- Announcement type: product launch, funding, research/report, customer story, thought leadership?
- Embargo or publish-ready date?
- Exclusive offer? (first-look exclusive to top target?)
Scan for press and positioning artifacts:
find . -name "*.md" 2>/dev/null | xargs grep -l "press\|media\|journalist\|pitch\|PR\|announcement\|launch\|funding" 2>/dev/null | head -10
find . -name "*.md" 2>/dev/null | xargs grep -l "positioning\|story\|narrative\|messaging\|value.prop" 2>/dev/null | head -10
Step 1: Sharpen the Story Angle
Before writing any pitch, make the story undeniably interesting:
A strong story angle has at least one of:
- Data — original research or a surprising number
- Timeliness — connection to a current trend or news cycle
- Conflict or tension — something that challenges conventional wisdom
- Human story — a customer or founder who embodies the change
- Consequence — who wins or loses as a result of this?
Weak angle: "We launched a new feature." Strong angle: "We found that [X% of Y] are doing Z wrong — and it costs them $N per year."
State the refined angle: [one sentence, the most interesting version of this story]
Step 2: Persona-Match Each Target
Different targets need different hooks:
| Target type | What they care about | Pitch hook |
|---|---|---|
| Tech reporter (TechCrunch, Wired) | Breaking news, funding, product disruption | News peg + data |
| Vertical trade press | Industry-specific impact, customer examples | Customer story + outcome |
| Podcast host (founder show) | Lessons, frameworks, journey, contrarian views | Insight or mistake you made |
| Podcast host (technical) | Deep technical content, architecture, tooling | Technical angle or novel approach |
| Newsletter author | Curated insight, their audience's specific interest | "Your readers care about X — here's a take on it" |
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.
- 8d ago First seen · 153 lines · 65 tokens per session scan A 13bd858ae522
buzz-outreach is a skill published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 1,489 once invoked, about $0.0003 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.
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