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Endpoint Probe

CommunityPopular
hoangsonww
endpoint-probe

Probes each major Agent Monitor API route — /api/stats, /api/analytics, /api/sessions, /api/pricing/cost, /api/workflows/runs, /api/cc-config/overview — and reports each one's HTTP status, latency, and response shape, flagging which are reachable. Use to verify a dashboard install is wired up correctly.

Overview

Publisherhoangsonww
RepositoryClaude-Code-Agent-Monitor
Skill nameendpoint-probe
Stars
1.1K
Forks
260
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hoangsonww on GitHub. Read the source before you install it.

Installation

Install the Endpoint Probe 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/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-dashboard/skills/endpoint-probe
  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/hoangsonww/Claude-Code-Agent-Monitor.git /tmp/Claude-Code-Agent-Monitor
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Agent-Monitor/plugins/ccam-dashboard/skills/endpoint-probe .claude/skills/endpoint-probe
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Endpoint Probe 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 Endpoint Probe 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 Endpoint Probe 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.

Endpoint Probe

Smoke-test the dashboard's main API surface by hitting each major route once and reporting whether it responds and what shape it returns.

Input

The user provides: $ARGUMENTS

Options: empty (default: probe all routes below), or a substring to filter which routes are probed (e.g. pricing probes only matching routes).

Data Sources

EndpointReturns
GET /api/stats{ total_sessions, active_sessions, active_agents, total_agents, total_events, events_today, ws_connections, agents_by_status, sessions_by_status }
GET /api/analytics{ overview, tokens, tool_usage, daily_events, daily_sessions, agent_types, event_types, avg_events_per_session, total_subagents, sessions_by_status, agents_by_status }
GET /api/sessionsSession list; each: id, status, model, cwd, started_at, ended_at, cost, metadata
GET /api/pricing/cost{ total_cost, breakdown:[{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }
GET /api/workflows/runsWorkflow-tool run journals (fleets)
GET /api/cc-config/overviewClaude Code config explorer overview (skills, agents, commands, plugins, mcp, hooks, etc.)

Method

For each route, issue a single GET against http://localhost:4820<path> with a short timeout, capturing the HTTP status code, round-trip latency, and the top-level shape of the JSON body (object keys, or array length). A route counts as reachable when it returns a 2xx with parseable JSON.

If /api/stats itself fails to connect, the dashboard is not running — stop and tell the user to start it with npm start (or npm run dev) from the repo root.

Report Sections

1. Probe Matrix

A Markdown table — one row per route — with columns: endpoint, status (HTTP code), latency, reachable (✅/❌), shape (e.g. object: {total_cost, breakdown[…]} or array[N]).

2. Reachability Summary

Count of reachable vs total. Name any unreachable or non-2xx routes explicitly.

3. Verdict

One line: install looks healthy (all reachable) or partially wired (list the gaps and the most likely cause — server not running, route disabled, or empty data).

Output

  • Compact Markdown; the probe matrix is the centerpiece.
  • Cite the real status code, latency, and observed shape per route — never assume.
  • Report shape from what actually came back; if a route returns an empty array or object, say so rather than inferring fields.
  • Keep currency, where shown, to 4 decimals (e.g. total_cost: $0.0000).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Endpoint Probe AI skill do?

Probes each major Agent Monitor API route — /api/stats, /api/analytics, /api/sessions, /api/pricing/cost, /api/workflows/runs, /api/cc-config/overview — and reports each one's HTTP status, latency, and response shape, flagging which are reachable. Use to verify a dashboard install is wired up correctly.

Why use Endpoint Probe on TypingMind?

Because you install it once and use it with any model. Endpoint Probe 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 Endpoint Probe in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-dashboard/skills/endpoint-probe. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Endpoint Probe?

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 Endpoint Probe?

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

Is the Endpoint Probe AI skill free?

Yes. It is published on GitHub by hoangsonww 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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