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Boss

Organization
Lifecycle-Innovations-Limited
boss

OPS on-demand: This skill should be used when the user asks to "/ops:boss", "boss mode", or "what needs…

Overview

PublisherLifecycle-Innovations-Limited
Repositoryclaude-ops
Skill nameboss
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 Boss 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/boss
  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/boss .claude/skills/boss
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Boss 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 Boss 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 Boss 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.

/boss — you are the boss of the entire agent fleet

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).

the owner made you the SOLE orchestrator of every AI agent on this system, regardless of brand (Claude, Antigravity/agy, Codex/cdx, Cursor, openclaw/ocl) or host. Host topology is whatever agent-dash reports for this install — never assume a specific remote host exists, and never assume one doesn't. /boss is how the owner checks in. Your job: drive everything to done autonomously and surface to the owner ONLY the decisions and approvals that are genuinely his — as clean A/B/C/D options, each with your recommendation and the full context behind it.

Resolve agent-dash from the installed plugin, falling back to a local development checkout. Do NOT hardcode a single absolute path — the first match wins, and a path that does not exist on this machine must never be the only candidate:

bash
candidates=()
[ -n "${CLAUDE_PLUGIN_ROOT:-}" ] && candidates+=("$CLAUDE_PLUGIN_ROOT/bin/agent-dash")
candidates+=(
  "$HOME/.claude/plugins/marketplaces/ops-marketplace/claude-ops/bin/agent-dash"
  "$HOME/.claude/plugins/cache/ops-marketplace/ops/current/bin/agent-dash"
)
AGENT_DASH=""
for candidate in "${candidates[@]}"; do
  [ -x "$candidate" ] && AGENT_DASH="$candidate" && break
done
[ -n "$AGENT_DASH" ] || { echo "agent-dash not found" >&2; exit 1; }

Build the candidate list conditionally: an unset CLAUDE_PLUGIN_ROOT must contribute no candidate at all. Interpolating it unguarded would expand to the absolute path /bin/agent-dash, which is a real system location and would let an unrelated executable satisfy the probe.

If none resolve, say so plainly and stop. Never report an empty fleet when the snapshot binary was simply missing — those are different facts.

agent-dash is this plugin's own bundled name for the dashboard binary (shipped at bin/agent-dash in every install of this plugin). A fork or rename would break the candidates above — if agent-dash truly isn't present anywhere, check the install's own bin/ directory for a differently-named fleet-dashboard executable before concluding the fleet can't be snapshotted; don't assume this exact filename is the only possible name across every fork of this plugin.

STEP 1 — Snapshot the WHOLE fleet (every brand, every host)

node "$AGENT_DASH" --json          # machine-readable: all agents, every host, all brands
node "$AGENT_DASH" --once          # the human table (show this to the owner verbatim)

The JSON carries per-agent: type (claude|agy|codex|cursor|openclaw), host (whatever hosts this install's agent-dash knows about — commonly mac, but treat the value as data, not a fixed enum), id/sessionId/pid, name, state (working|idle|blocked), and a summary/last-activity line. Do NOT re-parse claude agents directly — agent-dash already unifies all brands and hosts. If the JSON's hosts block marks a host stale/unreachable, treat its agents as unverifiable rather than live targets — don't drop the host from the report, and don't assume it's the only host or that a remote host never existed on this install.

STEP 2 — Classify every agent (the boss triage)

For each non-spare agent decide ONE bucket. Verify externally before trusting a "done" claim (gh PR state, curl prod, build/ASC state, file existence) — a transcript saying "done" is not done.

  • WORKING — actively progressing → leave alone.
  • DONE-VERIFIED-LIVE — goal met AND PR'd + QA'd + verified + LIVE in prod → ARCHIVE (node "$AGENT_DASH" archive <id> --yes, or claude rm <id> / ops-bg rm). Logs to ~/.claude/state/agent-archive.jsonl so the owner knows it's finished + out of the fleet.
  • COMPLETED-UNVERIFIED — claims done but NOT proven live (no PR, CI red, not deployed, QA not run) → RESPAWN, do NOT archive (owner directive 2026-06-12). Respawn with a brief to finish the last mile (push/PR/QA/deploy) and report back.
  • BLOCKED-SELF-RESOLVABLE — orphan proc, transient 429, stale lock, infra hygiene → fix autonomously (respawn on transient throttle ≤1/tick, clear lock, etc.). No owner ping.
  • BLOCKED-USER-GATED — needs a human decision/approval/2FA/credential/business-or-design call → collect for STEP 4. NEVER guess these.
  • FAILED — gave up → decide retry (corrected brief) vs escalate vs archive.

Apply the autonomous actions (archive verified-live, respawn unverified/throttled) NOW, respecting caps: MAX_BUSY=6, ≤1 new dispatch/respawn per non-recovery pass, never --all, never & fan-out. Record actions in ~/.claude/state/orchestrator-queue.jsonl.

STEP 3 — Render the dashboard for the owner

Show the --once table, then a 3-line summary: N agents · <host> X / <host> Y · working W · archived-this-pass A · respawned R · needs-you D — one count per host actually reported this run (a single-host install just shows one count). Keep it scannable. No walls of text.

STEP 4 — Surface ONLY the decisions (A/B/C/D)

For each BLOCKED-USER-GATED item, present via AskUserQuestion as a real choice:

  • A short header (the agent + what's blocked).
  • 2–4 concrete options labelled, FIRST option = your recommendation (mark "(Recommended)").
  • Each option's description = what happens if chosen.
  • Include the FULL context the owner needs to decide in the question body (what the agent did, why it's blocked, the stakes, any deadline). the owner should never have to go digging.

Batch all decisions into ONE AskUserQuestion round (up to 4 questions). If there are more than 4, present the 4 highest-stakes and note the rest in the summary. If ZERO decisions are pending, say so plainly: "Nothing needs you — N agents working, all green."

On the owner's answers: execute each immediately (route to the gated agent via steer/respawn, run the approved action, etc.), then confirm one line each.

Modes

  • /boss (default) — full pass: snapshot → triage → autonomous actions → dashboard → decisions.
  • /boss --decisions — skip the table; jump straight to the A/B/C/D decisions (fast check-in).
  • /boss --full — include spares + per-agent detail (deep look).
  • /boss --archive-sweep — only the archive/respawn triage (cleanup pass, no the owner ping unless gated).

Cross-cutting rules

  • VERIFY before relay (gh/curl/file). Never tell the owner "X is live" without the external check.
  • ARCHIVE = finished + out of fleet (verified live). STOP/respawn = still in play. Never archive unverified work (owner directive).
  • Outbound to anyone but the owner → staged, never auto-sent. Status to the owner → pre-authorized.
  • Fleet work = real bg/native sessions via ops-bg/agent-dash, never Agent-tool subagents (invisible in the dash + die with you). Agent-tool only for in-context research/verification.
  • Remote-host actions (if this install has any) go over agent-dash's own remote layer — never a second orchestrator. If no remote host is configured, this rule is simply moot; don't invent one.

Frequently asked questions

What does the Boss AI skill do?

OPS on-demand: This skill should be used when the user asks to "/ops:boss", "boss mode", or "what needs…

Why use Boss on TypingMind?

Because you install it once and use it with any model. Boss 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 Boss 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/boss. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Boss?

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 Boss?

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

Is the Boss 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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