How do I install the Eval Dashboard skill?

Run npx skillmds@latest add hoangsonww/eval-dashboard in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with Eval Dashboard?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Eval Dashboard free to use?

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Who published Eval Dashboard?

hoangsonww (@hoangsonww) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Eval Dashboard by hoangsonww — Agent Skill

Name: Eval Dashboard
Author: hoangsonww

Eval Dashboard

Build the interactive offline eval dashboard (eval/dashboard/index.html) — Chart.js trend, axis radar, composite histogram, per-card stacked bars, sortable card table. Use when the user wants to "see eval results", "open dashboard", "visualize quality", or "compare cards".

hoangsonww b90bbcd 2.2 KB Updated Sep 17, 2026

File contents

Eval — Interactive Dashboard

Single-file offline UI over eval/store.sqlite + eval/golden/. No backend, no build step. Chart.js loads from a CDN, but everything else works over file://.

How to invoke

make eval-dashboard                                  # regenerate dashboard/data.js
make eval-dashboard OPEN=1                           # also open in default browser
make eval-dashboard DASHBOARD_JUDGE=claude-haiku-4-5-20251001  # filter rows

Direct invocation:

python3 eval/export_dashboard.py --judge claude-haiku-4-5-20251001 --open

Behavior

Pull rows from eval/store.sqlite (latest-per-date wins).
Join each row with its corresponding eval/golden/<date>.json baseline.
Compute summary stats: composite min/max/median/mean, axis medians, drift z-score, gate-fail count, regression count.
Serialize to eval/dashboard/data.js as window.EVAL_DATA = {...}.
Optionally launch the default browser pointing at eval/dashboard/index.html via file://.

Panels rendered

Panel	Visualization
Stat cards	Composite median + mean, drift status, gate fails, regressions
Composite trend	Line chart with baseline overlay + dashed 3.0 gate threshold
Axis radar	5-axis median across all cards
Composite histogram	Buckets `< 2.5` → `≥ 4.5`
Per-card stacked bars	Each card's weighted axis contributions
Per-card table	Sortable, filterable (`All` / `Below gate` / `Regressed` / `Composite ≥ 4`), live search

What to tell the user

After running, tell them the dashboard path (eval/dashboard/index.html) and how many cards / goldens loaded. If OPEN=1 was not passed, give them the open command for their platform (open on macOS, xdg-open on Linux, start on Windows). Mention the dashboard is regenerated from the store — they should re-run this after any make eval-backfill to refresh visualizations.

---name: eval-dashboarddescription: Build the interactive offline eval dashboard (eval/dashboard/index.html) — Chart.js trend, axis radar, composite histogram, per-card stacked bars, sortable card table. Use when the user wants to "see eval results", "open dashboard", "visualize quality", or "compare cards".---# Eval — Interactive DashboardSingle-file offline UI over `eval/store.sqlite` + `eval/golden/`. No backend, no build step. Chart.js loads from a CDN, but everything else works over `file://`.## How to invoke```bashmake eval-dashboard # regenerate dashboard/data.jsmake eval-dashboard OPEN=1 # also open in default browsermake eval-dashboard DASHBOARD_JUDGE=claude-haiku-4-5-20251001 # filter rows```Direct invocation:```bashpython3 eval/export_dashboard.py --judge claude-haiku-4-5-20251001 --open```## Behavior1. Pull rows from `eval/store.sqlite` (latest-per-date wins).2. Join each row with its corresponding `eval/golden/<date>.json` baseline.3. Compute summary stats: composite min/max/median/mean, axis medians, drift z-score, gate-fail count, regression count.4. Serialize to `eval/dashboard/data.js` as `window.EVAL_DATA = {...}`.5. Optionally launch the default browser pointing at `eval/dashboard/index.html` via `file://`.## Panels rendered| Panel | Visualization || --- | --- || Stat cards | Composite median + mean, drift status, gate fails, regressions || Composite trend | Line chart with baseline overlay + dashed 3.0 gate threshold || Axis radar | 5-axis median across all cards || Composite histogram | Buckets `< 2.5` → `≥ 4.5` || Per-card stacked bars | Each card's weighted axis contributions || Per-card table | Sortable, filterable (`All` / `Below gate` / `Regressed` / `Composite ≥ 4`), live search |## What to tell the userAfter running, tell them the dashboard path (`eval/dashboard/index.html`) and how many cards / goldens loaded. If `OPEN=1` was not passed, give them the open command for their platform (`open` on macOS, `xdg-open` on Linux, `start` on Windows). Mention the dashboard is **regenerated** from the store — they should re-run this after any `make eval-backfill` to refresh visualizations.

Frequently asked questions