Hermes Agent is an AI assistant that learns from its use by creating and improving skills, retaining knowledge, searching past conversations, and adapting to its users. It is for people who want to run an agent through a terminal or messaging platforms while connecting it to different AI models and scheduled tasks.
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 NousResearch/hermes-agent --skill one-three-one-rulegit clone --depth 1 https://github.com/NousResearch/hermes-agentWrote 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/nousresearch/hermes-agent/one-three-one-rule)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/one-three-one-rule"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/one-three-one-rule/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/nousresearch/hermes-agent/one-three-one-rule"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/one-three-one-rule.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00021 | $0.00985 |
| Opus 5 | $0.00010 | $0.00492 |
| Sonnet 5 | $0.00004 | $0.00197 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
one-three-one-rule 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 10d 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
8 near-identical copies found in the catalogue:
- one-three-one-rule — 100% identical, 0 lines differ
- one-three-one-rule — 100% identical, 0 lines differ
- one-three-one-rule — 86% identical, 9 lines differ
- one-three-one-rule — 86% identical, 9 lines differ
- one-three-one-rule — 86% identical, 9 lines differ
- one-three-one-rule — 86% identical, 9 lines differ
- one-three-one-rule — 84% identical, 12 lines differ
- one-three-one-rule — 83% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1-3-1 Communication Rule
Structured decision-making format for when a task has multiple viable approaches and the user needs a clear recommendation. Produces a concise problem framing, three options with trade-offs, and an actionable plan for the recommended path.
When to Use
- The user explicitly asks for a "1-3-1" response.
- The user says "give me options" or "what are my choices" for a technical decision.
- A task has multiple viable approaches with meaningful trade-offs (architecture, tooling, migration strategy).
- The user needs a proposal they can forward to a team or stakeholder.
Do NOT use for simple questions with one obvious answer, debugging sessions, or tasks where the user has already decided on an approach.
Procedure
-
Problem (one sentence)
- State the core decision or desired outcome in a single concise sentence.
- Focus on the what, not the how — no implementation details, tool names, or specific technologies.
- Keep it tight. If you need "and", you're describing two problems.
-
Options (exactly three)
- Present three distinct, viable approaches labeled A, B, C.
- Each option gets a brief description, pros, and cons.
- Options should represent genuinely different strategies, not minor variations of the same approach.
-
Recommendation (one option)
- State which option you recommend and why, based on the user's context and priorities.
- Be direct — this is your professional judgment, not a hedge.
-
Definition of Done
- List the specific success criteria for the recommended option.
- These are concrete, verifiable outcomes — not vague aspirations.
- If the user picks a different option, revise this section to match.
-
Implementation Plan
- Concrete steps to execute the recommended option.
- Include specific commands, tools, or actions where applicable.
- If the user picks a different option, revise this section to match.
Verification
- Response has exactly one Problem sentence.
- Response has exactly three Options (A, B, C) with pros and cons for each.
- Response has a single Recommendation that picks one option with reasoning.
- Definition of Done and Implementation Plan align with the recommended option.
- If the user selects a different option, Recommendation, DoD, and Implementation Plan update accordingly.
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.
- 10d ago First seen · 98 lines · 21 tokens per session scan A 31ae7d7c5fc1
one-three-one-rule is a skill published in the GitHub repository NousResearch/hermes-agent (243,598 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 985 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
rubyllm
Build and maintain Ruby or Rails applications with the RubyLLM AI framework. Use for chats, agents, tools, structured output, media generation, transcription, OCR, moderation, embeddings, reranking, Rails integration, and RubyLLM upgrades; not for contributing to the framework itself.
creative-writing
Creative content workflow: brief, research, outline, draft, refine. Use when the user asks for a blog post, article, story, social media content, marketing copy, headline, or any writing where tone and voice matter.
document-authoring
Document and office-output workflow: clarify audience, ingest sources, outline, draft, review. Use when the user asks for a report, summary, email draft, memo, presentation, or any structured document deliverable.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project…
doc-coauthoring
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers.…
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude…