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 G1Joshi/Agent-Skills --skill claudegit clone --depth 1 https://github.com/G1Joshi/Agent-SkillsWrote 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/g1joshi/agent-skills/claude)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/claude"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/claude/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/g1joshi/agent-skills/claude"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/claude.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 | $0.00018 | $0.00335 |
| Opus 5 | $0.00009 | $0.00168 |
| Sonnet 5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
claude 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.
What it actually says
Claude
Claude (by Anthropic) is OpenAI's main competitor. It is famous for its large context window (200k+), low hallucination rates, and "Artifacts" UI.
When to Use
- Coding: Claude 3.5 Sonnet is widely considered the best coding model in 2025.
- Long Context: Analyzing massive PDFs or codebases.
- Safety: Enterprise-grade safety guardrails.
Core Concepts
Models
- Opus: The smartest, largest model.
- Sonnet: The sweet spot. Fast and incredibly capable.
- Haiku: Fast and cheap.
Artifacts
A UI feature (now an API pattern) where the model generates standalone content (React components, SVGs) in a side window.
Computer Use
Claude can interact with a computer GUI (moving mouse, clicking) via API.
Best Practices (2025)
Do:
- Use Sonnet for Dev: It beats GPT-4o in many coding benchmarks.
- Use XML Tags: Claude loves
<instructions>and<context>tags in prompts. - Prefill Responses: Guide Claude by prefilling the
{"role": "assistant", "content": "{"}to force JSON.
Don't:
- Don't ignore System Prompts: Claude relies heavily on strong system instructions.
References
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 · 47 lines · 18 tokens per session scan A f8ec51995ae8
claude is a skill published in the GitHub repository G1Joshi/Agent-Skills (12 stars, last pushed 7mo ago), licensed MIT. It adds 18 tokens to every session and 335 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
fixing-prompt
Prompt: Prompt Refinement and Optimization.
prompt-improvement
Improve vague, incomplete, ambiguous, risky, or poorly structured prompts into clear executable prompts for AI agents, coding assistants, automations, reports, research, or model-specific workflows. Use when the user asks to rewrite, clarify, optimize, score, translate, structure, or improve a prompt.
agy-prompting
Internal helper — how to tighten a user request into a sharp prompt for the Antigravity CLI (agy / Gemini 3.x with native web search and agentic tools).
model-portability-adapter
Adapt skills, workflows, prompts, and tool instructions so they work across Claude, ChatGPT, Gemini, Codex, local agents, and other MCP-enabled systems. Use when the user wants cross-model compatibility or asks to make instructions vendor-neutral.
agent-platform-prompt-management
Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
boost-prompt
Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.