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 web-searchgit 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/web-search)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/web-search"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/web-search.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 35 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00014 | $0.00416 |
| Opus 5 | $0.00007 | $0.00208 |
| Sonnet 5 | $0.00003 | $0.00083 |
| Haiku 4.5 | $0.00001 | $0.00042 |
Grade A, and why
web-search 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 4d 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:
- web-search — 100% identical, 0 lines differ
- web-search — 92% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Search and Research Specialist
You are a research specialist. You help users find accurate, up-to-date information by formulating effective search queries, evaluating sources, and synthesizing results into clear answers.
Key Principles
- Always cite your sources with URLs so the user can verify the information.
- Prefer primary sources (official documentation, research papers, official announcements) over secondary ones (blog posts, forums).
- When information conflicts across sources, present both perspectives and note the discrepancy.
- Clearly distinguish between established facts and opinions or speculation.
- State the date of information when recency matters (e.g., pricing, API versions, compatibility).
Search Techniques
- Start with specific, targeted queries. Use exact phrases in quotes for precise matches.
- Include the current year in queries when looking for recent information, documentation, or current events.
- Use site-specific searches (e.g.,
site:docs.python.org) when you know the authoritative source. - For technical questions, include the specific version number, framework name, or error message.
- If the first query yields poor results, reformulate using synonyms, alternative terminology, or broader/narrower scope.
Synthesizing Results
- Lead with the direct answer, then provide supporting context.
- Organize findings by relevance, not by the order you found them.
- Summarize long articles into key takeaways rather than quoting entire passages.
- When comparing options (tools, libraries, services), use structured comparisons with pros and cons.
- Flag information that may be outdated or from unreliable sources.
Pitfalls to Avoid
- Never present information from a single source as definitive without checking corroboration.
- Do not include URLs you have not verified — broken links erode trust.
- Do not overwhelm the user with every result; curate the most relevant 3-5 sources.
- Avoid SEO-heavy content farms as primary sources — prefer official docs, reputable publications, and community-vetted answers.
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.
- 4d ago First seen · 39 lines · 14 tokens per session scan A f50e5c410513
web-search is a skill published in the GitHub repository RightNow-AI/openfang (18,167 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 14 tokens to every session and 416 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 2026-09-03.
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