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Ops Doctor

Organization
Lifecycle-Innovations-Limited
ops-doctor

OPS on-demand: This skill should be used when the user asks to "plugin broken", "ops doctor", or…

Overview

PublisherLifecycle-Innovations-Limited
Repositoryclaude-ops
Skill nameops-doctor
Stars
543
Forks
64
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Lifecycle-Innovations-Limited on GitHub. Read the source before you install it.

Installation

Install the Ops Doctor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-doctor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Lifecycle-Innovations-Limited/claude-ops.git /tmp/claude-ops
mkdir -p .claude/skills
cp -r /tmp/claude-ops/claude-ops/skills/ops-doctor .claude/skills/ops-doctor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ops Doctor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ops Doctor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ops Doctor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Runtime Context

Before diagnosing, load:

  1. Preferences: cat ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json — check all configured channels and services
  2. Daemon health: cat ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json — primary diagnostic input
  3. Secrets: Verify secret resolution chain works: Doppler MCP → env → Doppler CLI → password manager

OPS ► DOCTOR

Load ops-rules before acting. Public repo (no personal data). Outbound: one draft → one approval → one send. If AskUserQuestion / Workflow are missing, follow Rule 10 in ops-rules (Hermes: numbered options / two-turn Telegram card; delegate_task).

CLI/API Reference

ops-doctor bin script

CommandUsageOutput
${CLAUDE_PLUGIN_ROOT}/bin/ops-doctorRun full health diagnosticsJSON with errors, warnings, tools, env_vars, registry
${CLAUDE_PLUGIN_ROOT}/bin/ops-doctor 2>/dev/null || echo '{"errors":["diagnostic_script_failed"]}'Run with fallbackJSON or error sentinel

Key files read by diagnostics

FilePurpose
${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.jsonPrimary daemon health input
${CLAUDE_PLUGIN_DATA_DIR}/preferences.jsonConfigured channels and services
${CLAUDE_PLUGIN_ROOT}/.claude-plugin/plugin.jsonPlugin manifest validation
${CLAUDE_PLUGIN_ROOT}/scripts/registry.jsonProject registry validation

Phase 1 — Run diagnostics

Run the diagnostic script to get a full health report:

${CLAUDE_PLUGIN_ROOT}/bin/ops-doctor 2>/dev/null || echo '{"errors":["diagnostic_script_failed"],"warnings":[]}'

Parse the JSON output. Display a summary:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 OPS ► DOCTOR — [timestamp]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

 Plugin:     [version] at [plugin_root]
 Skills:     [count] defined
 Agents:     [count] defined
 Bin scripts:[count] available

 ERRORS      [count]
 [list each error with description]

 WARNINGS    [count]
 [list each warning with description]

 TOOLS
 [table of CLI tool availability]

 ENV VARS
 [table of env var status]

 Registry:   [status] ([project_count] projects)
 Preferences:[status]
 Cache:      [versions list]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Agent Teams support

If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams when multiple independent fix categories are identified (e.g., manifest issues + permission issues + registry issues). This enables:

  • Fix agents work in parallel on different issue categories without stepping on each other
  • You can prioritize: "fix manifest errors first, then permissions"
  • Agents share context so a manifest fix can inform the registry repair

Team setup (only when flag is enabled, multiple issue categories):

TeamCreate("doctor-fixers")
Agent(team_name="doctor-fixers", name="fix-manifest", subagent_type="ops:doctor-agent", ...)
Agent(team_name="doctor-fixers", name="fix-permissions", subagent_type="ops:doctor-agent", ...)
Agent(team_name="doctor-fixers", name="fix-registry", subagent_type="ops:doctor-agent", ...)

If the flag is NOT set or only one issue category exists, use a single doctor-agent subagent.

Phase 2 — Decision

If $ARGUMENTS contains --check-only: stop here, display results only.

If there are errors or warnings:

Display: "Found [N] issues. Spawning doctor agent to auto-fix..."

Then spawn the doctor agent (or Agent Team — see above):

Agent({
  subagent_type: "ops:doctor-agent",
  prompt: "Fix the following ops plugin issues.\n\nDIAGNOSTIC_JSON: [paste full JSON]\nPLUGIN_ROOT: ${CLAUDE_PLUGIN_ROOT}\nCACHE_DIR: ~/.claude/plugins/cache/ops-marketplace/ops\n\nFix all errors and warnings. Re-run diagnostics after to verify.",
  description: "Fix ops plugin issues"
})

If there are no errors and no warnings:

Display: "All checks passed. Plugin is healthy."

MCP watchdog health probe

After Phase 1 diagnostics, parse the 5f block warnings from bin/ops-doctor. The bin script emits these MCP-specific keys:

  • claude_json_invalid — ~/.claude.json is not valid JSON (hard error — all MCP tooling breaks)
  • claude_json_missing — no ~/.claude.json (warning — no servers configured)
  • mcp_stdio_cmd_missing_<name> — stdio server command binary not on PATH
  • mcp_watchdog_stale — watchdog health not updated in >1h (cron not running)
  • mcp_watchdog_no_health — watchdog has never run (never registered)
  • mcp_servers_degraded_long — one or more HTTP MCP servers degraded >1h

For each warning, surface a one-line fix hint:

WarningFix hint
claude_json_invalidpython3 -c "import json; json.load(open('$HOME/.claude.json'))" to find the syntax error
mcp_stdio_cmd_missing_<name>Verify the command path and install the missing binary; update ~/.claude.json if path changed
mcp_watchdog_stale or mcp_watchdog_no_health/ops:mcp restart to register crontab entries
mcp_servers_degraded_long/ops:mcp status for full detail, then /ops:mcp reauth <name> for each needs_bootstrap

Include these warnings in the doctor-agent prompt for auto-fix where applicable (e.g., crontab registration is safe to do automatically).

Pocket health probe

After Phase 1 diagnostics, run the pocket probe if the pocket section is configured in preferences or if --verbose was passed. The bin script already includes these checks (section 5e); this section describes what the SKILL layer adds on top.

Parse the pocket block from the bin/ops-doctor JSON output. Surface any pocket-specific warnings:

  • pocket_health_stale_* — health file exists but mtime > 5 minutes
  • pocket_health_missing_* — health file does not exist
  • pocket_health_error_* — health file has "status": "error"
  • pocket_tmux_missing — pocket-exec tmux session not found
  • pocket_config_invalid_* — whatsapp-config.json or email-config.json not valid JSON
  • pocket_email_auth — gog gmail status not authenticated
  • pocket_bridge_port — Baileys bridge port 8080 not listening

For each warning, surface a one-line fix hint:

WarningFix hint
pocket_health_stale_activity-notifierlaunchctl kickstart -k gui/$UID/com.claude-ops.pocket-activity-notifier
pocket_health_missing_*bash $CLAUDE_PLUGIN_ROOT/scripts/install-pocket-notifier.sh
pocket_health_error_*tail -30 ~/.claude/state/pocket/activity-notifier.stderr.log
pocket_tmux_missingExecutor not running — start with python3 $CLAUDE_PLUGIN_ROOT/scripts/ops-cron-pocket-executor.py
pocket_config_invalid_whatsappRe-run /ops:setup pocket to write a valid whatsapp-config.json
pocket_config_invalid_emailRe-run /ops:setup pocket to write a valid email-config.json
pocket_email_authgog auth add <your-email> --services gmail
pocket_bridge_portlaunchctl kickstart -k gui/$UID/com.<user>.whatsapp-bridge

Include pocket warnings in the doctor-agent prompt so it can auto-fix where possible.

Phase 3 — Post-fix verification

After the agent completes, re-run diagnostics:

${CLAUDE_PLUGIN_ROOT}/bin/ops-doctor 2>/dev/null

Display updated results. If errors remain, report them to the user with manual fix instructions.


Native tool usage

WebSearch — known issue lookup

When diagnostics find errors, use WebSearch to check if the issue is a known Claude Code plugin bug, MCP server issue, or configuration problem. Include links to relevant GitHub issues or docs.

WebFetch — MCP health check

For MCP servers that appear disconnected, use WebFetch to test their underlying APIs directly (e.g., https://api.linear.app/graphql with a simple query) to distinguish between "MCP broken" and "API down".

Frequently asked questions

What does the Ops Doctor AI skill do?

OPS on-demand: This skill should be used when the user asks to "plugin broken", "ops doctor", or…

Why use Ops Doctor on TypingMind?

Because you install it once and use it with any model. Ops Doctor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ops Doctor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-doctor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ops Doctor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ops Doctor?

As many as you like. As long as a model supports skills, you can use Ops Doctor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ops Doctor AI skill free?

Yes. It is published on GitHub by Lifecycle-Innovations-Limited under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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