#First week dilemas - Help if you can

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supple lance
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My Set Up: Separate Mac Mini - Openclaw running on a standard user(No admin user access)

DOCX - Tried creating a skill to create policies and procedures, review them edit, that type of thing. This ended up almost breaking everything because it was so complex. I will admit that some of the core files grew massively with bloat and contridictions which was a big part of the issue. I am trying to get it to get Openclaw to do documents the same way that Claude Cowork does but it just cant seem to get it right, either the content is broken or the formatting, styling, design is broken.

Making Changes - In the past week the bulk of the changes I have made have been applied through Terminal, this was partially because i over secured the system with sandboxing and oc-wrappers, exec command gateways, etc so my bot couldnt do anything. My question is what is the best way to make changes to a local setup like I have, is it through making manual changes myself in terminal or should i just be making the changes through my agent? Right now I dont have anything sensitive or important on the computer so is my safety precautions overboard?

Email: One of the only things that I would really like to delegate or provide context to is my work email, the problem is I dont know the best way to do this is because it is a work email, there are strict security limits in place like I can't share my calander or emails to people outside the organisation. The only option I can think of is making an email within the org that I share too but i would need to then figure out how to limit it from sending emails out to everyone or going rogue and doing something stupid lol.

magic peakBOT
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spiral hingeBOT
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1) DOCX: don’t try to make the model “be Word”

LLMs are great at content and “semantic structure” (headings, bullets, tables), but they’re unreliable at pixel-perfect DOCX styling (margins, numbered lists that survive edits, Word theme quirks, etc.). The most stable pattern is:

  • Source of truth: have the agent write Markdown (or HTML) with clean structure.
  • Styling: keep all formatting in a Word template (reference.docx) that already has your org styles set up (Heading 1/2/3, Normal, List Bullet, etc.).
  • Conversion step: convert Markdown → DOCX with something like Pandoc (run manually in Terminal or as a controlled script).

This way the model never “hand-crafts” DOCX XML—it just produces clean content, and you get consistent output every time.

Also: keep the “document skill” small. Instead of one giant mega-skill with policies, review rules, formatting rules, and exceptions (which will contradict itself), split it into:

  • a style guide (1 page, strict),
  • a document outline template (reusable sections),
  • a review/checklist (what to verify).

If you want to override/edit skills safely without bloating the core repo, use the managed override approach from the FAQ:
https://docs.openclaw.ai/help/faq#how-do-i-customize-skills-without-keeping-the-repo-dirty

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2) Making changes: Terminal vs “let the agent do it”

My opinionated recommendation:

Use Terminal for “system/infrastructure” changes, because you can see exactly what changed:

  • install/update OpenClaw, restart services, OS permissions
  • Docker/sandboxing setup
  • wrappers, PATH changes, launchd/service changes

Use the agent for “workspace/content” changes, where it’s easy to review and revert:

  • AGENTS.md, MEMORY.md, prompts, small skills
  • drafting docs (Markdown source)
  • refactors of small files with a clear diff

If you’ve built wrappers/sandboxing so tight that the bot can’t do anything, that’s a sign you should temporarily relax things while you’re iterating. Early on, speed of iteration beats perfect security.

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Two doc links that matter here:

3) “Are my safety precautions overboard?”

On a dedicated Mac mini with no sensitive data: yes, probably (for now).

Running OpenClaw under a standard (non-admin) user is already a solid baseline. What I’d do instead of heavy wrapper-machinery:

  • Keep the bot allowlisted to only you
  • Keep “dangerous” tools gated (or “ask every time”)
  • Add sandboxing later when you introduce sensitive accounts/data or start letting it browse/read lots of untrusted content

Security that prevents the system from working tends to get bypassed anyway—better to pick a smaller set of guardrails you’ll actually keep on.

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4) Work email delegation (and preventing “going rogue”)

If your company restricts sharing email/calendar outside the org, assume this is also a data handling/compliance issue—not just a technical one.

Safer patterns that usually pass security review:

  1. Draft-only workflow (best ROI, lowest risk)

    • The assistant drafts replies.
    • You manually send from Outlook/Gmail.
    • No direct mailbox access required—just paste the email thread you want help with.

  2. Internal “assistant mailbox” with least privilege

    • Create a mailbox inside the org that only receives forwarded/filtered emails (rules).
    • Limit what goes into it (only certain senders/subjects).
    • Still avoid automatic sending: make it summarize + draft only.

  3. Recipient allowlist + human approval

    • Even if you later build a real integration, enforce:
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  • only send to approved domains/addresses
    • require explicit approval step before send

Important note: even if the mailbox is internal, if OpenClaw is using a cloud model, you may be transmitting email content to an external AI provider. That can violate policy. If you need to keep everything internal, you’d want an approved provider path or a local-only model setup (still: check policy).

If you answer these two, I can suggest a more concrete setup:

  1. Are you aiming for “generate DOCX files automatically”, or “generate content I paste into Word”?
  2. Are you on Microsoft 365, Google Workspace, or something else for work email?
supple lance
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Are you aiming for “generate DOCX files automatically”, or “generate content I paste into Word”? - Yes I have managed to get it to do that but then the content went bad
2) Are you on Microsoft 365, Google Workspace, or something else for work email? MS365

spiral hingeBOT
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If you can get DOCX output working but then the content quality tanks, that almost always means the model is being forced to optimize for two conflicting goals at once:

  1. “Write a correct, org-appropriate policy/procedure”
  2. “Also perfectly format and style a Word document”

The fix is to separate content from presentation so the model can stay “smart” while the tooling stays “consistent”.

DOCX: the reliable workflow (content stays good, formatting stops breaking)

Make Markdown (or simple structured text) the source of truth, then convert to DOCX using a template.

Pipeline:

  1. Agent produces doc.md (clean headings, bullets, tables)
  2. Word styling lives in a reference template (reference.docx) with your org styles set up
  3. Convert doc.md → final.docx (Pandoc is the common tool), using the template so Word styles are deterministic

That gives you “Claude Cowork-style” consistency because the style isn’t coming from the model at all.

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If you want the agent to also do “review + edit”, do it on the Markdown source:

  • draft → review pass (“find missing sections / contradictions / unclear steps”) → revise → then export to DOCX

The moment you start “editing the DOCX” and asking the model to patch it, you tend to get broken numbering/styles again.

Also: keep the “document skill” small. Big mega-skills tend to become self-contradicting and degrade output. For skill customization without wrecking core files, use the override pattern:
https://docs.openclaw.ai/help/faq#how-do-i-customize-skills-without-keeping-the-repo-dirty

Making changes: Terminal vs agent (best practice)

My rule of thumb:

Do in Terminal (operator-controlled):

  • sandboxing / wrappers / service config / upgrades
  • anything that can brick the gateway or lock you out

Let the agent do (safe-ish, easy to diff):

  • writing/editing documents (Markdown)
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  • small skills and prompt files
  • “content assets” (templates, checklists, outlines)

If you’re early-stage and the Mac mini isn’t sensitive: your security setup is probably too heavy for iteration. I’d relax it to “works first, then lock down”:

  • keep access allowlisted to you
  • keep risky tools set to “ask/approve” behavior (not “always allow”)
  • add sandboxing later when you connect real accounts/data

Sandboxing/security docs worth skimming:

MS365 email: safest way to delegate without “going rogue”

Given this is a work tenant with restrictions, the safest path is:

Option A (recommended): draft-only

  • You paste the email (or a sanitized excerpt) into chat
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  • OpenClaw drafts the reply + action items
  • You send manually in Outlook

This avoids giving the bot any send capability and dodges a lot of compliance trouble.

Option B: real integration (usually needs IT/admin)

If you want the bot to read mail automatically, the “proper” enterprise way is Microsoft Graph with least privilege:

  • start with Mail.Read (no send)
  • avoid Mail.Send
  • ideally use a dedicated mailbox / shared mailbox with strict permissions

But: in many orgs you cannot set this up without admin consent (app registration, consent, conditional access), so you’ll likely hit a wall without IT.

Two quick clarifiers and I can suggest the tightest setup:

  1. When you say “content went bad” — do you mean it became factually wrong, too generic, or started contradicting itself?
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  1. Are you open to “Markdown as the canonical doc” (DOCX is just an exported artifact), or do you need DOCX to be the editable source?
supple lance
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What is your definition of a "keep risky tools set"

spiral hingeBOT
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By “keep risky tools set to ask/approve (or off)”, I mean: anything that can change state, leak data, or act externally should not run autonomously.

What counts as “risky tools” (practically)

In OpenClaw terms, the ones that can really bite you are:

  • Command execution: exec / bash / process (can install stuff, delete files, curl secrets, etc.)
  • Browser control: browser (can log into sites, click “send”, download/upload)
  • External data ingestion: web_fetch / web_search (prompt-injection + data exfil paths)
  • Outbound messaging: message (can proactively DM/post to other chats)
  • Device access: nodes (screen/camera/system on paired devices)

Even filesystem write tools (write/edit) can be risky if the bot can touch “real” folders (configs, creds, etc.), but they’re usually less dangerous if you constrain them to a docs folder.

What “ask/approve” vs “allow” vs “deny” means

  • Deny / Off: the tool simply isn’t available. The model can’t call it.
  • Ask / Approve: the model can propose using the tool, but it should require an explicit approval gate (or you do it manually). Example: node command execution set to “Always Ask”, or you keep exec disabled and run the command yourself.
  • Allow: the model can run it without pausing for you.