From Prompt to Output: Day-to-Day AI Agent Workflow

disclaimer: all personal opinions, based on the experience of using Hermes and OpenClaw recently

1. Mindset

• When the result/output isn’t satisfactory, check the prompt first — unclear instructions are usually the human’s error, not the agent’s
• Tell the story clearly, one chapter at a time.

2. Environment (Pre-requisites)

• Update ~/.openclaw/SOUL.md and ~/.hermes/SOUL.md if there isn't, to make the agent more specific
• Linux is ideal; macOS is fine. Avoid running agents on Windows:
• Administrator privilege is too broad — risk of touching the whole OS
• PowerShell is optional for the OS but often required by agents, which adds friction
• Understand markdown
• Learn basic Unix/Linux as a non-root user
• Python: basic understanding is nice to have
• Result filename convention (OpenClaw and Hermes): YYMMDD + time + topic + subtopic, e.g. 2605211430-report-summary.md
• Avoid spaces in filenames
• Know where to save outputs. Default agent paths: ~/.openclaw, ~/.hermes (config, skills, state, including conversation history and output files)

3. Skills (personal opinion)

• Write my own most of the time
• Read others at https://clawhub.ai, https://www.skills.sh and https://hermes-agent.nousresearch.com/docs/skills
• Understand exactly what each installed skill does before you rely on it
• Install skills and plugins only when needed — performance and security. Skills: AI chooses when to use. Plugins: auto hooks (e.g. email) without AI choosing.
• Be skeptical of long skill files; harder to audit and more likely to hide unwanted behavior

4. Prompts and Language

• Prefer English for prompts (vs Chinese or others) when you need precision
• Use precise wording; cross-check with tools like Gemini or Perplexity if needed
• Keep prompts short and precise — saves tokens and reduces errors
• Break work from large to small (goal → steps → single tasks)
• No duplicated messages in the same session
• New task → new session — unrelated history gets loaded as prompt context
• Do not keep correcting an old prompt; that confuses the agent. Start fresh instead

5. Work Style

• Architectural thinking: overall → details, step by step (e.g. build a house: plan → materials → foundation → plumbing, wiring, tiling, paint → finish)
• Run independent pieces in parallel (e.g. plumbing, wiring, tiling at the same time)
• Break work into small pieces when it cannot be done in one shot; start small
• Guardrails: state what must not happen (e.g. “Everything in Python. Do not use Java”)

6. Quality and Testing

• Let AI review your SKILL.md before you rely on it
• Enable verbose mode and watch the test run
• **SKILL.md**: standard skill markdown — YAML frontmatter + declarative human-language instructions

7. Security

• Trust official docs and repos only (e.g. Nous, https://clawhub.ai)
• Stay cautious always
• Trust less when skill files are very long — read before install

8. Closing Note

• AI and agents change fast — stay curious and keep learning