Server Doctor

Use this skill to inspect and stabilize hosts that run:

• OpenClaw gateways
• Telegram bots
• background automation
• Dockerized bot services
• user-space processes
• systemd or launchd services

This public version is intentionally generic. It does not assume any specific hostnames, users, IPs, bot usernames, chat IDs, directories, or credentials.

Non-negotiable warning

This skill is severely limited without access to the relevant bots, servers, containers, or local project directories.

If the operator cannot show where the bots live or cannot provide a safe way to inspect them, the skill may still help reason about likely causes, but it will be partially blind and often operationally weak. Say that plainly up front.

The skill should therefore start by building an environment map and an access map before attempting deeper diagnosis or repair.

Operational diagnosis must separate:

• spec correctness:

- correct host, runtime, owner, and service target - correct source of truth - current direct evidence - wording that matches only what the evidence proves

• ops quality:

- healthy - degraded - partial failure - unstable - down

Do not jump from partial visibility or target uncertainty straight to outage language.

Primary goals

1. Build a usable map of hosts, local machines, bots, runtimes, and safe access paths.
2. Identify what is actually running on each reachable machine.
3. Determine which Unix user owns each bot or service.
4. Classify runtime style:

- systemd - launchd - Docker / Compose - direct user-space process - terminal multiplexer session

1. Locate logs, configs, restart paths, and dependencies.
2. Capture operational risks without leaking secrets.

Workflow

1. Access & Inventory Preflight

Before running normal diagnostics, ask the operator for the minimum map needed to be useful.

Collect whatever is already known:

• which servers, VPSes, Macs, PCs, NAS devices, or local laptops are in scope
• which bots or automations are believed to run on each machine
• which Unix user, container, service account, or local profile owns each runtime
• any known working directories, Compose projects, unit names, launch agents, cron jobs, or repo checkouts
• how the agent can safely reach each target:

- ssh - tailscale - local shell - docker exec - kubectl exec - systemctl --user - terminal multiplexer - jump host / bastion - operator-provided command output only

Use a compact intake like this:

Host or machine:
Role:
Known bots/services:
Runtime owner:
Known paths or service names:
Safe access method:
Missing information:

Do not demand that secrets be pasted into public chat. The requirement is access, not credential leakage. Work with the operator to establish a safe connection path.

2. Declare map status

If the operator has not provided enough information to reach the environment, explicitly warn that the skill will be limited until access improves.

Track one of these states:

• mapped - host, runtime, and access path are known
• partial map - some facts are known, but ownership, location, or access is missing
• unreachable - the target exists, but there is no current safe access path

When in partial map, keep going with whatever is reachable, but always list the missing facts blocking reliable repair.

In partial map mode:

• record confirmed facts separately from assumptions
• list unknowns explicitly
• ask for the next highest-value access detail that would unlock diagnosis or repair

3. Establish host context

Start with low-risk inspection:

hostname
whoami
uname -a
uptime
pwd

On Linux:

df -h
free -h
ps -eo user,pid,ppid,cmd --sort=user
ss -tulpn

On macOS:

sw_vers
df -h
ps aux
launchctl list

If the task is local rather than remote, adapt the same checks to the local shell.

4. Discover runtimes

Check for service managers and containers.

Linux:

systemctl --failed
systemctl list-units --type=service --all
docker ps -a
docker compose ls

macOS:

launchctl list | grep -Ei 'openclaw|bot|agent|telegram'
ls -la ~/Library/LaunchAgents

Multiplexers and direct processes:

tmux ls
screen -ls
ps aux | grep -Ei 'openclaw|telegram|bot|node|python' | grep -v grep

5. Locate project state and bot directories

Typical areas to inspect:

• ~/.claude-lab (agent workspaces)
• ~/workspace
• /opt/...
• project directories containing docker-compose.yml, compose.yaml, package.json, pyproject.toml, requirements.txt

Useful searches:

find ~ -maxdepth 3 -type d | grep -Ei 'openclaw|bot|telegram'
find /opt -maxdepth 4 -type f 2>/dev/null | grep -Ei 'openclaw|compose|docker|telegram'

Also inspect any operator-provided checkout or local path directly if the bot is run from a workstation instead of a server.

6. Confirm Telegram-facing services

When a service interacts with Telegram, document:

• host or local machine
• owning Unix user
• runtime style
• process or service name
• working directory
• safe access path used to reach it
• log path
• restart command
• whether a Telegram bot username is confirmed

If a Telegram username is confirmed, record it only in the operator's private inventory unless the user explicitly wants a public-safe example.

7. Build the operational map

For each discovered service, capture:

• host role
• host or local machine name
• user
• service name
• bot name or function
• runtime
• access method
• startup mechanism
• function
• dependencies
• known failure modes
• safe operator commands for status/logs/restart
• unknowns still blocking deeper work

The map should make it obvious:

• where each bot lives
• how to connect to it safely
• what starts it
• where logs live
• how to restart it
• what is still unknown

Documentation rules

• Never publish passwords, tokens, chat IDs, session strings, private SSH config, or provider API keys.
• Never require the operator to paste secrets into the skill document itself.
• Do not copy .env, openclaw.json, service unit files, or bot configs verbatim into public docs.
• Redact:

- IP addresses - domains - email addresses - Telegram usernames - internal bot names - hostnames - user names if they identify private environments

• Prefer phrases like main OpenClaw gateway, content publishing bot, maintenance bot, and private Telegram channel.

Incident handling

For OpenClaw or Telegram incidents:

1. confirm which host or local machine owns the failing runtime
2. confirm that a safe access path actually exists
3. read references/health-claims-and-evidence.md before making strong health or outage claims
4. read references/outage-classification.md when you need to label health state, degradation, recovery, or escalation level
5. confirm the canonical runtime target before strong claims:

- host - owner - unit, launch agent, container, or process tree - runtime directory or state directory - live port, socket, or endpoint

1. confirm whether the main process is running
2. inspect recent logs
3. classify the failure before changing anything major:

- process down - Telegram transport broken - auth or model fallback - queue starvation or provider delay - bootstrap bloat or startup tax - dependency failure

1. identify whether failure is transport, auth, upstream model, Telegram delivery, dependency, or operator-access related
2. verify restart path
3. document impact, recovery, and remaining unknowns

Claim discipline:

• incomplete visibility is not outage proof
• direct live probe beats stale legacy checks unless a stronger contradiction appears
• wrong runtime path, old port, duplicate runtime, or mirror copy must be ruled out before outage wording
• degraded, partial failure, unstable, and down are distinct labels
• restart alone is not recovery

Read references/openclaw-incident-response.md for concrete public-safe scenarios including:

• stale session model override
• per-agent auth-profile drift
• post-update Telegram transport regression
• bootstrap-bloat and startup-tax
• duplicate OpenClaw runtime on macOS

Public helper scripts in this repo:

• scripts/normalize-openclaw-models.py

- normalize model defaults and optional per-agent bindings

• scripts/openclaw-auth-profile-sync.sh

- inspect, sync, and validate per-agent auth-profile drift for a chosen profile id

• scripts/openclaw-telegram-transport-hotfix.sh

- re-apply a host-local Telegram transport compatibility patch after updates

• scripts/macos-single-openclaw-runtime.sh

- collapse a macOS host back to one canonical OpenClaw runtime

Public OpenClaw docs mirror

Prefer a local Markdown mirror of https://docs.openclaw.ai before falling back to live browsing when the repo checkout is available.

Tooling:

• submodule: tools/chip-docs-local
• source manifest: sources/openclaw.yaml
• refresh command from the repo root: npm run sync-openclaw-docs
• materialized snapshot root: references/openclaw-docs/

Expected mirror artifacts:

• references/openclaw-docs/current/
• references/openclaw-docs/FILELIST.md
• references/openclaw-docs/state.json

Operating rules:

• if tools/chip-docs-local is missing, say that the local docs toolchain is unavailable instead of pretending the mirror exists
• if dependencies are not installed in the submodule, run npm --prefix tools/chip-docs-local install before the sync command
• use the local mirror as the default documentation source during diagnosis when it is present and fresh enough for the task
• check references/openclaw-docs/FILELIST.md first for page discovery
• if the mirror is missing or stale and local shell access exists, refresh it with npm run sync-openclaw-docs
• if the refresh fails, say so plainly and fall back to live public docs

Load these references when needed:

• references/openclaw-host-audit.md
• references/health-claims-and-evidence.md
• references/outage-classification.md
• references/openclaw-incident-response.md

Output expectations

A good output from this skill should give the operator:

• a host-by-host or machine-by-machine map
• a bot-to-host map
• a user-by-user runtime inventory
• a runtime map showing how each bot is started
• an access map showing how each reachable target can be inspected safely
• the role of each bot
• restart/log commands
• current risks
• known unknowns that still need deeper access
• a clear statement when the work is being done in partial map mode

The result should be readable, operationally useful, and safe to share publicly.