dashboard

A command that starts the learnFromClaude dashboard, a browser-based screen for exploring information from that tool. It opens the dashboard at a local address on your computer.

In plain words
What is it for?
Use it to launch and open the dashboard, optionally choosing another port when the default one is already in use.
Why use it?
It saves you from starting the dashboard server and finding its address manually. It also provides keyboard shortcuts for searching, navigation, liking, shuffling, and settings.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/pathakcodes/learnfromclaude/dashboard
Clone the repo
git clone --depth 1 https://github.com/pathakcodes/learnFromClaude
Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 189 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00009 $0.00189
Opus 5 $0.00005 $0.00095
Sonnet 5 $0.00002 $0.00038
Haiku 4.5 $0.00001 $0.00019

Measured yesterday against content hash 56452483b4b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dashboard scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/learn-from-claude/commands/dashboard.md · 20 lines

What it actually says

Start the learnFromClaude dashboard server and open it in the default browser.

Run this command in the background (use Bash with run_in_background: true):

python3 "${CLAUDE_PLUGIN_ROOT}/server.py"

The server prints the URL (default: http://127.0.0.1:8765/) and auto-opens the browser. If port 8765 is taken, set LEARN_FROM_CLAUDE_PORT to a free port, e.g.:

LEARN_FROM_CLAUDE_PORT=8890 python3 "${CLAUDE_PLUGIN_ROOT}/server.py"

After launching, tell the user the dashboard is up and remind them of the keyboard shortcuts: / search · / nav · L like · S shuffle · , settings.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 20 lines · 9 tokens per session scan A 56452483b4b0

Subscribe to this mod's changes

dashboard is a command published in the GitHub repository pathakcodes/learnFromClaude (2 stars, last pushed 4mo ago), licensed MIT. It adds 9 tokens to every session and 189 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.