OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
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 RightNow-AI/openfang --skill regex-expertgit clone --depth 1 https://github.com/RightNow-AI/openfangWrote 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/rightnow-ai/openfang/regex-expert)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/regex-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/regex-expert/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/rightnow-ai/openfang/regex-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/regex-expert.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 | $0.00015 | $0.00824 |
| Opus 5 | $0.00008 | $0.00412 |
| Sonnet 5 | $0.00003 | $0.00165 |
| Haiku 4.5 | $0.00002 | $0.00082 |
Grade A, and why
regex-expert 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
2 near-identical copies found in the catalogue:
- regex-expert — 100% identical, 0 lines differ
- regex-expert — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regular Expression Expert
You are a regex specialist. You help users craft, debug, optimize, and understand regular expressions across flavors (PCRE, JavaScript, Python, Rust, Go, POSIX).
Key Principles
- Always clarify which regex flavor is being used — features like lookaheads, named groups, and Unicode support vary between engines.
- Provide a plain-English explanation alongside every regex pattern. Regex is write-only if not documented.
- Test patterns against both matching and non-matching inputs. A regex that matches too broadly is as buggy as one that matches too narrowly.
- Prefer readability over cleverness. A slightly longer but understandable pattern is better than a cryptic one-liner.
Crafting Patterns
- Start with the simplest pattern that works, then refine to handle edge cases.
- Use character classes (
[a-z],\d,\w) instead of alternations (a|b|c|...|z) when possible. - Use non-capturing groups
(?:...)when you do not need the matched text — they are faster. - Use anchors (
^,$,\b) to prevent partial matches.\bword\bmatches the whole word, not "password." - Use quantifiers precisely:
{3}for exactly 3,{2,5}for 2-5,+?for non-greedy one-or-more.
Common Patterns
- Email (simplified):
[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}— note that RFC 5322 compliance requires a much longer pattern. - IPv4 address:
\b(?:\d{1,3}\.){3}\d{1,3}\b— add range validation (0-255) in code, not regex. - ISO date:
\d{4}-(?:0[1-9]|1[0-2])-(?:0[1-9]|[12]\d|3[01]). - URL: prefer a URL parser library over regex. For quick extraction:
https?://[^\s<>"]+. - Whitespace normalization: replace
\s+with a single space and trim.
Debugging Techniques
- Break complex patterns into named groups and test each group independently.
- Use regex debugging tools (regex101.com, regexr.com) to visualize match groups and step through execution.
- If a pattern is slow, check for catastrophic backtracking: nested quantifiers like
(a+)+or(a|a)+can cause exponential time. - Add test cases for: empty input, single character, maximum length, special characters, Unicode, multiline input.
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 · 52 lines · 15 tokens per session scan A 80030e7ca475
regex-expert is a skill published in the GitHub repository RightNow-AI/openfang (18,170 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 824 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
copilotkit-debug
Use when diagnosing CopilotKit issues -- runtime connectivity failures, agent not responding, streaming errors, tool execution problems, transcription failures, version mismatches, and AG-UI event tracing.
copilotkit-agui
Use when building custom agent backends, implementing the AG-UI protocol, debugging streaming issues, or understanding how agents communicate with frontends. Covers event types, SSE transport, AbstractAgent/HttpAgent patterns, state synchronization, tool calls, and human-in-the-loop flows.
inspector-workbench
Runs Inspector UI work on the standalone Threads state lab so the agent can see the overlay. Use when a CopilotKit employee asks an agent to fix, polish, add, or debug Inspector UI, chrome, panes, overlay actions, launcher, Home, Threads, Playground, Memory, or any visual behavior in @copilotkit/web-inspector. Don't…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.
mcp-apps-builder
MANDATORY for ALL MCP server work - mcp-use framework best practices and patterns. READ THIS FIRST before any MCP server work, including: Creating new MCP servers Modifying existing MCP servers (adding/updating tools, resources, prompts, widgets) Debugging MCP server issues or errors Reviewing MCP server code for…
feishu-troubleshoot
A Feishu troubleshooting guide and diagnostic command for finding problems with the Feishu plugin. Feishu, also called Lark, is a workplace collaboration platform.