Ops Statusline logo

Ops Statusline

Organization
Lifecycle-Innovations-Limited
ops-statusline

OPS on-demand: This skill should be used when the user asks to "statusline theme", "cockpit", or…

Overview

PublisherLifecycle-Innovations-Limited
Repositoryclaude-ops
Skill nameops-statusline
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 Statusline 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-statusline
  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-statusline .claude/skills/ops-statusline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ops Statusline 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 Statusline 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 Statusline 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 any subcommand, resolve paths:

bash
PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(ls -d "$HOME/.claude/plugins/cache/ops-marketplace/ops"/*/ 2>/dev/null | sort -V | tail -1)}"
STATUSLINE_CMD="$HOME/.claude/statusline-command.sh"
STATUSLINE_CFG="$HOME/.claude/statusline.config.json"
THEMES_FILE="${PLUGIN_ROOT}templates/statusline/themes.json"
SETTINGS_FILE="$HOME/.claude/settings.json"
SUGGEST_BIN="${PLUGIN_ROOT}bin/ops-statusline-suggest"

OPS ► STATUSLINE

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).

Manages the Claude Code cockpit statusline — a 3-line terminal status bar showing context-window health, quota gauges, burn rate, git branch, fleet state, sys metrics, and per-project ops badges.

Parse $ARGUMENTS and route:

Argument (first word)Action
preview or emptyRender a sample output at current terminal width
configRe-run the wizard: preset, theme, projects, gauge widths
theme <name>Switch theme in config
doctorValidate config, settings.json wiring, renderer path
resetRestore default config from template
(anything else)Show help + current status

Subcommand: preview

Render the statusline using the current config against a built-in sample payload. Never touches real config or settings files.

Step 1 — Build sample payload

bash
COLS="${COLUMNS:-$(tput cols 2>/dev/null || echo 120)}"
SAMPLE_PAYLOAD=$(cat <<'JSON'
{
  "workspace": { "current_dir": "/home/user/Projects/my-app" },
  "model": { "display_name": "Claude Sonnet 4.6" },
  "rate_limits": {
    "five_hour":  { "used_percentage": 42, "resets_at": 0 },
    "seven_day":  { "used_percentage": 18, "resets_at": 0 }
  },
  "context_window": { "used_percentage": 31 },
  "cost": { "total_cost_usd": 0.14, "total_lines_added": 120, "total_lines_removed": 40 },
  "session_id": "preview-sample",
  "transcript_path": ""
}
JSON
)

Step 2 — Run renderer

bash
COLUMNS="$COLS" printf '%s' "$SAMPLE_PAYLOAD" | "$STATUSLINE_CMD" 2>/dev/null

If $STATUSLINE_CMD is not executable, fall back to the template:

bash
COLUMNS="$COLS" printf '%s' "$SAMPLE_PAYLOAD" | sh "${PLUGIN_ROOT}templates/statusline/statusline-command.sh" 2>/dev/null

Print the rendered output between ruler lines so the user sees the actual width context:

──────────────────────────────────────── (preview at 120 cols)
<rendered lines>
────────────────────────────────────────

If rendering fails (exit non-zero), print:

○ Preview failed — renderer returned non-zero.
  Check: /ops:statusline doctor

Subcommand: config

Re-run the wizard — preset, theme, projects, and gauge widths. Calls the suggest engine to seed a recommended config, then lets the user confirm or adjust each section. Writing to ~/.claude/statusline.config.json (never touches the real settings.json statusLine wiring — that is only changed by /ops:setup).

Step 1 — Run suggest engine

bash
SUGGESTED=$("$SUGGEST_BIN" 2>/tmp/ops-statusline-suggest.log)

Parse the _detected block to present context to the user:

bash
PROJ_COUNT=$(printf '%s' "$SUGGESTED" | jq -r '._detected.projects_found // 0')
INTEGRATIONS=$(printf '%s' "$SUGGESTED" | jq -r '._detected.integrations | to_entries | map(select(.value)) | map(.key) | join(", ") // "none"')

Print detection summary:

Detected N projects · integrations: <list>

Step 2 — Preset selection

Use AskUserQuestion (max 4 options per CLAUDE.md Rule 1):

Which preset?
  [cockpit — full color, all widgets (Recommended)]
  [minimal — essentials only, low noise]
  [full — all metrics, widest gauges]
  [Keep current preset]

Re-run suggest with chosen preset:

bash
SUGGESTED=$("$SUGGEST_BIN" --preset "$CHOSEN_PRESET" 2>/dev/null)

Step 3 — Theme selection

Use AskUserQuestion:

Which theme?
  [cockpit — rich color, graded gauges (Default)]
  [minimal — two shades, no color grading]
  [nord — cool blues]
  [mono — bold only, no color]

Patch the suggested config with chosen theme:

bash
SUGGESTED=$(printf '%s' "$SUGGESTED" | jq --arg t "$CHOSEN_THEME" '.theme = $t')

Step 4 — Write config

bash
TMP=$(mktemp)
printf '%s\n' "$SUGGESTED" | jq 'del(._comment, ._detected)
  | . + {"_comment": "Configured by /ops:statusline config on '"$(date -u +%Y-%m-%dT%H:%M:%SZ)"'."}' > "$TMP"
mv "$TMP" "$STATUSLINE_CFG"

Validate the written JSON:

bash
jq . "$STATUSLINE_CFG" >/dev/null 2>&1 && echo "✓ Config written to $STATUSLINE_CFG" || echo "✗ JSON validation failed"

Step 5 — Offer preview

Use AskUserQuestion:

Config saved. Preview now?
  [Yes — show preview]  [No — done]

On Yes, run the preview subcommand inline.


Subcommand: theme

Switch the theme key in the existing config without touching other settings.

bash
NEW_THEME="${ARGUMENTS#theme }"
NEW_THEME=$(printf '%s' "$NEW_THEME" | tr -d '[:space:]')

Validate theme exists in themes.json:

bash
VALID=$(jq -e --arg t "$NEW_THEME" '.[$t] // empty' "$THEMES_FILE" 2>/dev/null)

If invalid, list available themes and error:

bash
AVAILABLE=$(jq -r 'keys | join(", ")' "$THEMES_FILE" 2>/dev/null)
echo "Unknown theme '$NEW_THEME'. Available: $AVAILABLE"
exit 1

If valid, merge into existing config:

bash
TMP=$(mktemp)
if [ -f "$STATUSLINE_CFG" ]; then
  jq --arg t "$NEW_THEME" '.theme = $t' "$STATUSLINE_CFG" > "$TMP"
else
  jq -n --arg t "$NEW_THEME" '{"theme": $t}' > "$TMP"
fi
mv "$TMP" "$STATUSLINE_CFG"
echo "✓ Theme set to '$NEW_THEME'"

Run a quick preview automatically after switching.


Subcommand: doctor

Validate that all statusline components are healthy. Check and report:

Check 1 — Renderer exists and is executable

bash
if [ -x "$STATUSLINE_CMD" ]; then
  echo "✓ Renderer: $STATUSLINE_CMD"
else
  echo "✗ Renderer not found at $STATUSLINE_CMD"
  echo "  Fix: /ops:setup → Statusline section, or run:"
  echo "  cp '${PLUGIN_ROOT}templates/statusline/statusline-command.sh' '$STATUSLINE_CMD' && chmod +x '$STATUSLINE_CMD'"
fi

Check 2 — settings.json statusLine wiring

bash
if [ -f "$SETTINGS_FILE" ]; then
  SL_CMD=$(jq -r '.statusLine.command // empty' "$SETTINGS_FILE" 2>/dev/null)
  if [ -n "$SL_CMD" ]; then
    echo "✓ settings.json statusLine.command: $SL_CMD"
    # Verify it points at an executable
    eval SL_EXPANDED="$SL_CMD"
    [ -x "$SL_EXPANDED" ] || echo "  ⚠ command path is not executable — may need /ops:setup statusline"
  else
    echo "○ settings.json has no statusLine.command — statusline not wired"
    echo "  Fix: /ops:setup → Statusline section"
  fi
else
  echo "○ ~/.claude/settings.json not found — statusline not wired"
fi

Check 3 — Config JSON validity

bash
if [ -f "$STATUSLINE_CFG" ]; then
  if jq . "$STATUSLINE_CFG" >/dev/null 2>&1; then
    THEME=$(jq -r '.theme // "cockpit"' "$STATUSLINE_CFG")
    PROJ_COUNT=$(jq -r '(.projects // []) | length' "$STATUSLINE_CFG")
    echo "✓ Config: $STATUSLINE_CFG (theme=$THEME, projects=$PROJ_COUNT)"
  else
    echo "✗ Config JSON invalid: $STATUSLINE_CFG"
    echo "  Fix: /ops:statusline reset"
  fi
else
  echo "○ No config at $STATUSLINE_CFG — using built-in defaults"
fi

Check 4 — Themes file present

bash
if [ -f "$THEMES_FILE" ]; then
  THEMES=$(jq -r 'keys | join(", ")' "$THEMES_FILE" 2>/dev/null)
  echo "✓ Themes: $THEMES"
else
  echo "⚠ themes.json missing at $THEMES_FILE — theme switching may fail"
fi

Check 5 — Quick render smoke test

bash
PAYLOAD='{"model":{"display_name":"Test"},"rate_limits":{},"context_window":{},"cost":{}}'
RESULT=$(printf '%s' "$PAYLOAD" | COLUMNS=80 "$STATUSLINE_CMD" 2>/dev/null)
if [ -n "$RESULT" ]; then
  echo "✓ Render smoke test: PASS ($(printf '%s' "$RESULT" | wc -l | tr -d ' ') lines)"
else
  echo "✗ Render smoke test: FAIL — no output"
fi

Print final verdict: OK (all checks pass) or Issues found (with remediation steps).


Subcommand: reset

Restore ~/.claude/statusline.config.json from the default template.

Use AskUserQuestion:

Reset statusline config to defaults?
  [Yes — overwrite ~/.claude/statusline.config.json]  [Cancel]

On Yes:

bash
cp "${PLUGIN_ROOT}templates/statusline/statusline.config.default.json" "$STATUSLINE_CFG"
echo "✓ Config reset to defaults"

Then run preview.


CLI/API Reference

CommandEffect
/ops:statusline previewRender sample output
/ops:statusline configRe-run wizard
/ops:statusline theme cockpit|minimal|mono|nordSwitch theme
/ops:statusline doctorValidate all components
/ops:statusline resetRestore default config

Key files

FilePurpose
~/.claude/statusline-command.shThe renderer script
~/.claude/statusline.config.jsonUser config (theme, widgets, projects)
~/.claude/settings.jsonContains .statusLine.command wiring
${PLUGIN_ROOT}templates/statusline/statusline-command.shCanonical renderer template
${PLUGIN_ROOT}templates/statusline/themes.jsonAvailable themes
${PLUGIN_ROOT}templates/statusline/statusline.config.default.jsonDefault config
${PLUGIN_ROOT}bin/ops-statusline-suggestRegistry-driven config generator

Frequently asked questions

What does the Ops Statusline AI skill do?

OPS on-demand: This skill should be used when the user asks to "statusline theme", "cockpit", or…

Why use Ops Statusline on TypingMind?

Because you install it once and use it with any model. Ops Statusline 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 Statusline 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-statusline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ops Statusline?

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 Statusline?

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

Is the Ops Statusline 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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