Tips and usage for hermes-agent.nousresearch.com
Hermes can handle scheduled jobs such as checking email once a day by writing a script and setting up cron to run it. That setup can be fragile. In firsthand use, a Himalaya email config was wiped, and troubleshooting took more time than the automation saved. Kimi k2.6 felt reliable, but it was expensive. Problems seemed to start after switching to cheaper models that changed or worked around the setup Kimi had created. The main goal is to connect Hermes to email, reminders, and calendars so it can act like a steadier second brain for ADHD support. The practical question is how to make scheduled tasks reliable, avoid erased settings, and decide how much manual review is needed.
Before the World Cup group stage began, 12 advanced AI models predicted every group match. Each model received the same prompt and had to give the winning team, exact score, possession, Man of the Match, confidence level, and tactical reasoning. Once a match kicked off, its prediction was locked. Knockout-stage predictions have not been made yet because the bracket is not known until the group stage ends. After 54 matches, Claude Opus 4.7 led the overall table with 141 points and also had the most exact-score predictions, with 9. Sonar 2 predicted the most match winners, with 35 correct winners. Grok 4.3 ranked only sixth overall but correctly picked the Man of the Match 10 times, the best result for that category. Scores were based on exact score, correct winner, goal difference, Man of the Match, an underdog bonus, and confidence calibration. One concern remains: not every model was running under exactly the same conditions, but the provided material does not show what those condition differences were.
Composer 2.5 is included in the $30 per month SuperGrok plan and can be used inside Hermes agent. In firsthand use, it feels very fast, gives smart answers, and formats responses cleanly. GPT-5.5 has also worked well, but it can feel a little slow, and its formatting or writing style may not fit every user’s taste. Composer 2.5 already felt fast and capable in Cursor, and it also performs well inside Hermes agent. The price may be a practical advantage. With normal use, the SuperGrok plan’s rate limits seem hard to hit, so it may offer more value than a comparable $20 ChatGPT plan for some Hermes agent users. The main current drawback is that Composer 2.5 does not support image input or vision. Hermes agent can reduce that problem by sending image understanding work to other models through auxiliary settings.
Hermes Agent OS is presented as one workspace that connects Hermes, Codex, Claude Code, OpenClaw, and other specialized AI tools instead of using each one as a separate chatbot. Hermes is positioned for ongoing work such as watching for new developments, organizing useful information, and keeping tasks moving. Codex is used for building or improving software, while Claude Code is used for longer and more complex projects. OpenClaw adds browser control, computer control, memory, and scheduled automation, so agents can act on tasks rather than only answer questions. The broader setup also mentions OpenSEO, Obsidian, OMI, Ollama, Open Montage, local models, voice control, content creation, outreach, app building, lead generation, media creation, and team workflows. AI Profit Boardroom is promoted as the paid training and support space for learning these setups step by step.
Hermes Agent can reduce the need to open the Reddit app and manually move through many screens. With OpenCLI and a browser that is already logged in, Hermes Agent can search r/hermesagent for posts marked with the “USE CASES” flair across multiple pages. Asking for summaries of each post and its replies is more useful than asking for a direct copy of everything. The results can be turned into a PDF with custom formatting. Hermes Agent can also send the finished file through Telegram, making the whole flow a small search, summary, document, and delivery automation.
Hermes Agent Computer Use is presented as a way for an AI to click, type, scroll, and open apps on a computer. Its main promise is that it does not take over the user’s main screen or physical mouse cursor. Many computer control tools interrupt normal work because the cursor moves by itself, windows jump forward, and the user has to stop using the machine. Hermes Agent is described as handling this differently by sending input directly to the app it needs to control. That means it could work inside one program while the user keeps typing in another. The available setup steps, practical workflows, and guided support are promoted through a video and a separate community.
On Windows 11, the official Hermes Desktop installer also installs Hermes Agent. A separate setup can already run Hermes Agent directly on a home Ubuntu server, with access from a Windows browser through `http://localhost:9119`. Hermes Desktop has a gateway option, so the desktop app can connect to a remote Hermes Agent instead of relying only on a local one. The practical problem is whether Windows can keep only the official desktop app without installing the local Hermes Agent, or whether specific installed files and folders can be removed safely. The item does not confirm an official desktop-only installer or a safe list of agent files to delete.
Founder.exe was built in about six hours at a Nous Research Hermes Buildathon. A solo founder gives it a mission, and a manager AI agent plans the work and assigns it to specialist agents. Those specialists handle market research, decide what the product should emphasize, and build or ship the final output. The goal is to produce something usable instead of returning only a long conversation. The core workflow works, but it remains an early hackathon prototype with access offered through a waitlist. It has not yet been shown that several specialist agents perform better than one capable agent.
After moving a small AI assistant project to Hermes, most of the next two weeks were spent fixing Hermes itself. Sessions broke or disappeared, the gateway stopped working, and the command-line tool broke so agents could not do useful work. Configuration reset unexpectedly. Agents also wrote low-quality content into skills and filled memory with skill-related clutter. The experience raises a practical question about whether Hermes is worth using if messaging integration can be built directly and self-improvement can be handled with a scheduled job.
Hermes can be paired with a local model through Ollama instead of relying only on a remote model service. The main focus is adjusting the context that an AI agent uses when it works inside Hermes. The confirmed substance is about why a local model may be useful, how Ollama fits into that setup, and how Hermes-specific context customization is part of the workflow.
Markdown tables made by Hermes Agent or OpenClaw can appear broken in Discord and Telegram chats. Turning those tables into PNG images can make them display cleanly inside the chat. The image-conversion skill itself works well. The weak point is that the agent often forgets to use the skill when it should. Adding the instruction to the agent’s base guidance did not make the behavior fully reliable.
For marketing and business development work, Hermes agent looks useful as a personal work assistant, while n8n can handle workflow automation and tool connections. From an automation agency perspective, OpenClaw has already been used for internal work and some client work, but Hermes agent feels stronger in early use. The current setup depends heavily on n8n automations, and the main interest is how to combine n8n for workflow automation and orchestration with Hermes agent for personal productivity. No detailed setup steps or measured results are given yet, but the practical question is how a marketer or business development person can use Hermes agent well.
A coding Pro plan can still fail in Hermes Agent after only about 2% of quota has been used. The shown error is HTTP 429, and the API call fails after 3 retries. The message says the service may be temporarily overloaded and asks the user to try again later. The practical point is that remaining quota does not always mean a request will go through right away. Short-term service load or request limits can still block the run.
One practical way to make hermes-agent lighter may be to disable extra skills and tools so the context size becomes smaller. The question becomes more important because the hermes-agent skill itself is the largest one. The main uncertainty is whether that specific skill should also be disabled, or whether it is required for hermes-agent to work properly. The available information does not confirm whether disabling it is possible or what would break if it were turned off.
‘Vibe Creating’ is an agent skill that turns rough ideas, stories, or overly detailed scripts into prompts for text-to-video models. It is packaged as an open-source SKILL.md file, with compatibility aimed at Claude Code and other large language model tools. The skill first judges and scores the input, then chooses whether to clean it up, rewrite it, or pass it through with little change. The output uses a fixed four-part format so it can be checked more easily. The main goal is to keep precise creative control when needed while making the prompt easier for a video model to use.
AI coding agents can repeat the same failed bug fix, treat tests as successful without real proof, skip the step of reproducing a problem, or run risky commands without enough guardrails. A safer workflow starts by making the agent choose a task mode before meaningful work begins, such as debug, fix, review, or test-first. Each mode has a short checklist that keeps the agent focused on the right kind of work. The main rules are to verify changes with real checks, never make tests weaker just to pass, avoid destructive commands unless the allowed scope is clear, and match the agent’s behavior to the job at hand. The workflow is aimed at intermediate users and applies to quality control, context handling, debugging, shipping, skills, and multi-agent work.
Using Hermes to fill website forms raises a safety question. Normal browser autofill works well for fixed details like name, address, and phone number. It does not handle open-ended fields well, such as writing to customer support or asking for information. Those fields need the agent to read the page and write a suitable message from the context. Many of these tasks happen while the person is logged in to the website. The main concern is whether there is a safer setup than giving Hermes full browser control and general computer access.
YouTube and X have many sources about Hermes and agent features, but some channels mix in paid promotion for services like Hostinger. That makes it hard to tell which advice is organic, research-focused, and actually useful. A better learning setup needs a way to separate ads from real hands-on experience and serious research. Personal content and self-promotion can still be useful, but the main test is whether the material helps people understand what they can actually do with Hermes and agentic workflows.
The goal is to connect local or frontier models to an AI harness and run them without internet access. Online provider models such as Claude, OpenAI, Mistral, Perplexity, xAI Grok, and Gemini are outside the target. The focus is model choice and training, not browser control, file use, or MCP setup. Many current AI harness setups depend on online providers, which can lead to token costs and too many tool calls. The desired direction is to reduce those costs and wasted calls in work environments such as VSCode, Cursor, OpenCode, OpenClaw, and Hermes. The setup already has a working AI harness and access to strong hardware, so space, power use, and heat matter more than budget. Past experience with OpenAI Operator and Claude Code, Claude Desktop, and Claude Cowork showed that computer use worked fairly well before workflows moved more toward API-only access. Larger models and MoE models have produced usable results, even with the usual drift in tool and function use.
Hermes Agent could be used with a PHP forum instead of only pairing it with Obsidian for personal knowledge management. The forum would act like a topic-based knowledge space, where subjects are created as discussion threads or boards. Multiple bots could work inside that space every day by searching the web, discussing findings, and doing deeper research with each other. The idea is closer to a small research center than a private notes app, because the knowledge grows through visible discussion and repeated investigation. No setup steps, test results, or proven workflow are included.
SecureVector v4.9.1 adds tool-level enforcement for Hermes Agent. This likely means Hermes Agent can have stricter rules for which outside tools it may use and how those tools may run. The available information does not confirm which tools are covered, how setup works, or whether this is officially supported by Nous Research.
A developer combined Codex, Claude Code, and Hermes into a self-built agentic coding platform by repurposing an existing project management workflow originally used to track client projects. Initially, the workflow was simple: tell Codex what to do, let it act, then manually verify whether it did the right thing, approve any sandbox permission escalations, and push it to the next task. That approach required sitting at the computer constantly, checking each AI action. To fix this, the developer fed tasks into the same human-gated PM workflow already used for tracking internal client projects, letting it advance tasks along a pipeline instead of requiring constant manual oversight.
The main issue is whether the Hermes Agent desktop software can run tasks on two or more profiles at the same time. The setup is the desktop app, and the person has 20 profiles available. The provided content does not include a confirmed answer, setup steps, or known limits. The practical question is whether profile tasks can run in parallel and, if so, whether computer power or account limits could become a problem.
On Windows, updating Hermes to 0.17.0 can leave the gateway stopped after the update finishes. The problem happens when a git-based update fails and Hermes falls back to the ZIP updater. A direct ZIP update already restarts paused gateways at the end, but the ZIP fallback path after a git failure missed that same cleanup step. This means the update can succeed while the user’s Windows gateway profile stays paused. PR #50060 fixes this by applying the same gateway resume behavior to the fallback path. The change is still open and not merged, but the same fix can be applied temporarily.
The new Hermes Agent version adds Blank Slate Mode, which lets an agent start with only the basic pieces needed to run. Instead of turning on a large set of skills, tools, and connections before the first task, Hermes begins with the model, file access, basic operations, and terminal access. The user can then add only the skills needed for a clear job, such as research, coding, search engine optimization, content work, or client tasks. Related updates also describe a way to turn a PDF, URL, folder, blog post, or written instruction into a reusable skill. That means a repeated workflow can be taught once and used again later instead of being explained from scratch in each session. Version 0.17 is also described as the Reach release, with broader support for devices, workflows, images, and team collaboration. Some of the material mixes product details with paid coaching promotion, so the useful feature claims should be separated from the sales pitch.
This is a local AI agent workflow for watching and structuring Google SERP snapshots for a small set of keywords. The goal is not full SEO analysis. The agent only records what is visible on the search results page. It checks whether ads appear, which advertiser domains and ad titles are visible, the top organic result titles and snippets, the visible URL paths, and whether a target domain appears in organic results. It also checks for image blocks, product or shopping blocks, People Also Ask questions, related searches, local packs or business panels, and AI Overview visibility. Anything uncertain or cut off on screen is marked for manual review. The agent must not click ads, click search results, fill forms, log in, or make SEO conclusions. In a Windows test with a Hermes-style local agent, the workflow could create structured CSV output when the search results page was accessible. When Google showed a CAPTCHA or sorry page, the run was handled as blocked.
General office assistant work showed clear problems with document creation and formatting. OpenClaw and MiniMax could be used for tasks such as making a sales letter, proposals, and documents with tables, but the results needed constant correction and the document style often broke. After repeated fixes, some sales proposals with tables became usable. A second assistant for nonprofit work made a staff schedule calendar in HTML, and that result worked well. It also created staff timecards as spreadsheet files, but updates from chat messages with staff hours often went wrong. A Hermes and Nous subscription did not produce a real usable document in this test. Switching Hermes to MiniMax made document files, but they were very incomplete. GPT-4o mini was also tried after an AI recommendation, but it was not good for this office assistant use case.
A Raspberry Pi 5 setup is being used with Hermes and a direct DeepSeek API connection. The main tradeoff is whether using DeepSeek directly is better than using the model through Nous because of price, fewer connection steps, or some other benefit. DeepSeek’s data collection and retention policies are also a practical concern. Even if sensitive data will not be used, it is still worth asking whether a China-based hosted model creates more risk than other hosted models outside China. v4-flash is being considered as the default model because it may offer a useful balance of quality and speed. For harder tasks, a heavier model would be useful as a fallback, but it is unclear whether Hermes can keep that fallback inside the same profile or switch profiles without manual action.
A travel-focused MCP has been built for frequent travelers. It lets AI use travel details such as points, loyalty status, past trips, and preferences. With that information, an AI agent can search for and book flights, hotels, and rental cars in a way that tries to make better use of loyalty benefits. Interest appears to be coming more from general AI agents such as OpenClaw and Hermes than from ordinary frequent travelers. The main promise is that an AI agent could save money or get more value from travel rewards.
A hobbyist writer using Claude AI for sci-fi fiction and roleplay describes keeping all world-building information in a single markdown file called a 'story bible' — covering world rules, characters, locations, and a timeline of what happened in each story arc and scene. A key challenge is tracking which characters or factions know which facts; for example, in a card game like blackjack within the story, it breaks immersion if character A somehow knows character B's cards, so this kind of knowledge is tracked carefully in the bible. The old workflow involved pasting the entire story bible into a chat interface or API call, discussing how the story should progress, outlining a scene's key beats before writing, having the LLM write the scene, then asking for minor corrections afterward. To make this process smoother, the writer is now using Hermes's agentic workflow, which involves delegating parts of the task to sub-agents with human review in the loop, and includes a diagram of this workflow.