anthropics/skills180kadd-clidash
Add clidash — a zero-dependency, read-only web dashboard that derives its tabs and tables at runtime from any CLI that lists resources as JSON. Ships pre-wired for NanoClaw's ncl CLI (agent groups, sessions, channels, users, roles), plus message-activity charts, a log tail, and a read-only file viewer for group skills/CLAUDE.md/profiles.
Install
Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.
读取 https://funcoding.ai/skills/nanocoai/nanoclaw/add-clidash/install.md ,按里面的步骤帮我安装这个 Skill。
SKILL.md
/add-clidash — CLI-derived read-only dashboard
clidash is a small, read-only web dashboard. You point it at any CLI that can
list resources as JSON (NanoClaw's ncl, docker, kubectl, …) and it builds
the dashboard at runtime: one tab per resource, a generic table over whatever
columns the rows have. A new ncl resource becomes a new tab and a new column
becomes a new table column with zero code changes.
It ships pre-wired for NanoClaw's ncl CLI and adds three NanoClaw-aware
panels driven entirely by config:
- Agents overview — status cards joining groups + sessions + messaging groups + wirings (green <15m / amber <2h / red older).
- Activity — per-session inbound/outbound message totals and a daily series,
read directly from the session DBs (
nclhas no messages resource). - Logs — last N lines of allowlisted host log files.
- Files — a read-only viewer for group skills,
CLAUDE.md, and profiles.
Why it's safe
clidash is read-only by construction: the server can only execFile the
argv templates in its config. {resource} is the sole substitution and is
allowlist-validated against the discovered/static resource set before exec —
never a shell, no free-form input reaches argv. There is no auth; the network
is the auth boundary — it binds 127.0.0.1 by default. Only ever bind a
private interface (e.g. a tailnet IP), never a public one.
It's distinct from /add-dashboard (which pushes JSON snapshots to a separate
@nanoco/nanoclaw-dashboard npm package): clidash has zero dependencies, no
build step, no push pipeline, and no edits to NanoClaw source — it just reads
ncl and the session DBs.
Steps
1. Copy the tool into place
clidash is fully self-contained — copy the whole directory in:
tools/ is not a standard NanoClaw directory and cp -R won't create it, so
make it first:
mkdir -p tools
cp -R .claude/skills/add-clidash/add/tools/clidash tools/clidash
That is the only file change this skill makes. Nothing in NanoClaw src/ is
touched, no dependency is added.
2. Create the config
The example config is pre-wired for NanoClaw with paths relative to the repo
root, so it works as-is when you run clidash from tools/clidash/:
cd tools/clidash
cp clidash.config.example.json clidash.config.json
clidash.config.json is your local config — add it to .gitignore if you
don't want to commit install-specific paths:
echo 'tools/clidash/clidash.config.json' >> ../../.gitignore
The example assumes ncl is built at bin/ncl. If bin/ncl doesn't exist,
build it first (pnpm run build) or point clis.ncl.bin at the right path.
3. Test
Tests use a stub CLI — no real ncl or docker needed:
npm test
All tests should pass (Node ≥ 22.5, node:test, zero dependencies).
4. Run and verify
node server.js # serves http://127.0.0.1:4690
In another shell, confirm it's live and that ncl discovery worked:
curl -s http://127.0.0.1:4690/api/clis | head -c 400 # CLIs + discovered resources
curl -s http://127.0.0.1:4690/api/r/ncl/groups | head -c 400 # a real resource table
Then open http://127.0.0.1:4690/ in a browser. You should see the Agents
overview plus a tab per ncl resource.
5. (Optional) Run as a service
clidash binds 127.0.0.1 by default. To reach it from other devices, bind a
private (e.g. tailnet) IP via the BIND env var or bind in config — never a
public interface.
# ~/.config/systemd/user/clidash.service (Linux)
[Unit]
Description=clidash read-only CLI dashboard
[Service]
WorkingDirectory=%h/nanoclaw/tools/clidash
ExecStart=/usr/bin/node %h/nanoclaw/tools/clidash/server.js
Environment=BIND=127.0.0.1
Restart=on-failure
[Install]
WantedBy=default.target
systemctl --user enable --now clidash
On macOS, wrap node server.js (with WorkingDirectory = tools/clidash) in a
launchd plist the same way the main NanoClaw service is configured.
Configuration reference
clidash.config.json keys (see tools/clidash/README.md and
clidash.config.example.json for the full shape):
| Key | Purpose |
|---|---|
port, bind, refreshSeconds | server bind + UI auto-refresh cadence |
clis.<name>.bin / cwd / env | how to invoke the CLI (bin is relative to cwd) |
clis.<name>.discover or resources | runtime discovery (ncl help) vs a static resource list |
clis.<name>.list | argv template; {resource} is the only substitution |
clis.<name>.output | json or jsonlines (docker/kubectl style) |
clis.<name>.unwrap | dot-path into a response envelope (e.g. data) |
clis.<name>.enrich/badges/summary | table decorations (ID→name joins, status colors, summary cards) |
activity | sessionsRoot + days for the message-activity charts |
logs | dir, tailLines, and an allowlist of files to tail |
docs | file viewer: root, a deny glob list, and collections of glob patterns |
Adding a second CLI is config-only — e.g. docker is included as a jsonlines
example. View plugins (views/<cli>-<view>.js) are the only per-CLI code and
are optional.
Troubleshooting
ENOENT/ config not found — run fromtools/clidash/and make sure you copiedclidash.config.example.jsontoclidash.config.json(step 2), or setCLIDASH_CONFIG=/abs/path.json.- No
nclresources / discovery empty —bin/nclisn't built or the path is wrong. Build it (pnpm run build) or fixclis.ncl.bin. - docker tab errors — the docker daemon isn't running, or remove the
dockerCLI from config if you don't need it. - Can't reach it from another device — it binds
127.0.0.1; setBIND=<private-ip>(tailnet), never a public interface. - Empty Activity/Logs/Files — check that
activity.sessionsRoot,logs.dir, anddocs.rootresolve to your NanoClaw root (relative to where you launchnode server.js).
Removal
See REMOVE.md.
Similar Skills
anthropics/skills180k
anthropics/skills180kbrand-guidelines
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
AI & agents
anthropics/skills180kinternal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
AI & agents
anthropics/skills180kmcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
AI & agents
anthropics/skills180kalgorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
AI & agents
anthropics/skills180kacademy-guide
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
AI & agents