本文へ移動
cccskills
無料GitHub で公開

ego-browser-native-charts

Generate self-contained HTML/CSS benchmark and comparison charts in an ego-inspired Browser-Native Editorial style. Use for blue-white product metrics, model benchmarks, A/B comparisons, efficiency reports, difficulty breakdowns, and compact technical data panels.

インストール方法を見る

含まれるファイル(6)

  • SKILL.md11.3 KB
  • examples/interaction-turns.html10.2 KB
  • README.md794 B
  • templates/browser-native-dual-card.html8.1 KB
  • templates/browser-native-hybrid.html9.7 KB
  • VALIDATION.md603 B

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Ego Browser-Native Charts

Generate data charts that look like a restrained, product-native browser interface rather than a generic AI dashboard.

Style Identity

Use the name Browser-Native Editorial Benchmark for this visual system.

It combines:

  • browser chrome and tab geometry;
  • editorial hierarchy and generous white space;
  • technical benchmark conventions;
  • monochrome surfaces with one functional blue accent;
  • compact monospace metadata and metric labels;
  • thin borders, flat fills, and minimal decoration.

The result should feel like a benchmark page built into a browser product: calm, precise, utilitarian, and brand-led.

When to Use

Use this skill when the user asks for:

  • product or model benchmark comparisons;
  • REPL versus Heredoc, baseline versus target, or competitor versus product charts;
  • cost, latency, token, tool-call, turn-count, success-rate, or percentile metrics;
  • blue-and-white technical charts;
  • an ego-lite-like browser-native or editorial chart style;
  • self-contained HTML sections that can be pasted into a blog, landing page, or report.

Do not use this style for playful consumer dashboards, colorful marketing infographics, 3D charts, glossy gradients, or dense financial terminals.

Output Contract

Unless the user requests otherwise:

  1. Output one complete self-contained <section> block.
  2. Put all CSS inside a nested <style> element.
  3. Use no JavaScript and no external libraries.
  4. Namespace every class with a unique component prefix.
  5. Keep the component responsive.
  6. Preserve all supplied data exactly unless a derived percentage must be recalculated.
  7. Use English interface copy by default when the surrounding article is English; otherwise match the user’s language.
  8. Do not add explanations before or after the code when the user asks for code only.

Core Design Tokens

Use these defaults unless the user gives explicit brand tokens:

--ego-blue: #2457ff;
--ego-black: #161616;
--ego-surface: #f6f6f3;
--ego-line: #d8d8d3;
--ego-muted: #777772;
--ego-white: #ffffff;

Color Roles

  • --ego-blue: target product, improvement, selected state, positive efficiency signal.
  • --ego-black: primary title, model metadata, axes, important values.
  • --ego-surface: browser chrome, chart card interiors, subtle rows.
  • --ego-line: borders, separators, tracks, and grid lines.
  • --ego-muted: descriptions, run metadata, secondary labels.
  • Baseline bars: light neutral gray with a thin gray border.
  • Target bars: solid brand blue with no gradient.

Never use neon glow, purple gradients, glassmorphism, heavy shadows, or multicolor palettes.

Typography

Use system sans-serif for editorial copy and system monospace for technical labels.

font-family: Arial, Helvetica, -apple-system, BlinkMacSystemFont,
  "Segoe UI", sans-serif;
font-family: ui-monospace, SFMono-Regular, Menlo, monospace;

Recommended scale for a component around 920 px wide:

  • main title: 14px, weight 700;
  • description: 10px, muted;
  • metric header: 9–9.5px, monospace, weight 600;
  • value labels: 9.5–10px, monospace, weight 600;
  • category labels: 8–9px;
  • metadata: 8–8.5px, monospace;
  • model metadata: 8.5px, monospace, black, weight 600.

Avoid oversized dashboard typography. Titles should be short and compact.

Browser Shell

The default outer structure is:

  1. a 34 px browser chrome row;
  2. three small circular controls;
  3. one active tab with a 6 px blue square;
  4. a content area with title on the left and model/run metadata on the right;
  5. one or more bordered chart panels;
  6. a small footer such as lower is better.

Recommended shell styling:

  • outer border: 1px solid #161616;
  • outer radius: 10px;
  • card radius: 7px;
  • no drop shadow;
  • active tab bottom border blends into white content;
  • browser chrome uses #f6f6f3.

If the user asks to remove the browser shell, keep the same internal cards, typography, tokens, and spacing, but remove only the chrome row and outer browser frame.

Model Metadata

When model and effort information is available, place it at the upper right of the content header.

Preferred copy:

model gpt-5.5 · effort medium

Rules:

  • render it in monospace;
  • use --ego-black, not muted gray;
  • use weight 600;
  • keep run/sample metadata on a second line in --ego-muted;
  • do not turn it into a pill, badge, button, or colored chip;
  • keep it horizontally aligned with the title block.

Data Semantics and Percentage Math

Choose one comparison direction and keep it consistent throughout a component.

Default comparison language

Prefer target-relative reduction language:

21.6% lower
44.0% lower

Use this formula when comparing a lower target value against a baseline:

reduction_percent = (baseline - target) / baseline × 100

Example:

baseline = 43.65
target = 24.43
reduction = (43.65 - 24.43) / 43.65 = 44.0%

Do not mix this with “baseline increase over target,” which uses a different denominator:

increase_percent = (baseline - target) / target × 100

If the supplied table contains REPL +78.7% but the chart is meant to follow the X% lower convention, recompute the value using the baseline denominator and relabel it. Mention the conversion only when explanatory prose is requested.

For metrics where higher is better, use X% higher or +X pp and state higher is better in the footer.

Chart Selection Rules

1–2 metrics: Dual Card Bars

Use two side-by-side cards. Each card contains two vertical bars:

  • baseline on the left in neutral gray;
  • target product on the right in brand blue;
  • values above each bar;
  • reduction label in the card header;
  • shared footer: lower is better.

3–5 related metrics: Hybrid Panel

Use:

  • one large primary vertical-bar comparison on the left;
  • difficulty or subgroup rows with paired horizontal tracks on the right;
  • compact summary statistics below.

This is the preferred layout for overall plus Easy/Medium/Hard data.

6–10 metrics: Benchmark Report Rows

Use grouped horizontal rows rather than many miniature vertical charts.

Each row should show:

  • metric name;
  • baseline and target values;
  • a pair of horizontal tracks;
  • one consistently defined delta.

Time series

Use a simple line chart with thin black/gray baseline and solid blue target. Keep the browser shell and compact metadata, but do not force time-series data into bars.

Bar and Track Grammar

Vertical bars

  • baseline: background: #dededa; border: 1px solid #a2a29d;;
  • target: background: #2457ff;;
  • top corners: 2px radius;
  • no gradients;
  • baseline height is usually 100% within each metric card;
  • target height is target / baseline × 100%;
  • do not compare bar heights across cards with different units.

Horizontal tracks

  • track background: #e2e2de or #ecece8;
  • track height: 5–7px;
  • baseline fill: gray with thin border;
  • target fill: solid blue;
  • square ends or at most 1–2 px radius;
  • place exact values at the right edge.

Grid lines

Use thin, low-contrast horizontal lines. A repeating linear gradient is acceptable:

background-image: repeating-linear-gradient(
  to bottom,
  transparent 0,
  transparent 41px,
  #e3e3df 41px,
  #e3e3df 42px
);

Axes should be black or medium gray, never blue.

Copywriting Rules

Use short, factual, product-oriented titles:

  • Same workload. Fewer calls.
  • Less back-and-forth at every level.
  • Nearly half the interaction turns.
  • Same tasks. Lower overhead.

Descriptions should explain the comparison in one sentence and avoid hype.

Metric labels should be compact and technical:

  • AVG_COST_USD
  • AVG_TOOL_CALLS
  • OVERALL_AVERAGE
  • AVERAGE_BY_DIFFICULTY
  • TOTAL_TURNS
  • OVERALL_P95

Use sentence case only for editorial titles and descriptions. Use uppercase monospace labels for metric identifiers.

Layout and Spacing

Default component:

width: 100%;
max-width: 920px;
margin: 26px auto;

Typical spacing:

  • content padding: 15px 16px 14px;
  • header bottom margin: 12–13px;
  • panel gap: 10px;
  • panel header padding: 8px 10px;
  • chart body padding: 11–13px;
  • summary gap: 10px.

Preserve white space. Do not compress every region into a dense dashboard.

Responsive Behavior

At 640–700px:

  • stack two-column panels into one column;
  • move right-side metadata under the title and align it left;
  • stack summary cards vertically;
  • keep chart labels readable;
  • never allow model metadata or values to overlap.

Use media queries inside the component. Do not rely on page-level CSS.

Accessibility and Robustness

  • Maintain readable contrast between blue, black, gray, and white.
  • Do not communicate comparison using color alone; include values and labels.
  • Use semantic elements such as header, article, aside, and footer when practical.
  • Add aria-label to the root section when the chart’s meaning is not obvious from surrounding context.
  • Keep tabular numbers aligned with font-variant-numeric: tabular-nums.
  • Do not use absolute positioning for important content unless necessary.

Anti-Patterns

Do not generate:

  • glowing blue bars;
  • large rounded pills for deltas;
  • gradients on chart bars;
  • floating glass cards;
  • colorful legends with many accent colors;
  • giant headings or oversized KPI numerals;
  • icons that add no data meaning;
  • fake browser controls that dominate the content;
  • inconsistent percentage denominators;
  • a gray model label when the corresponding component uses black metadata.

Generation Workflow

  1. Parse the user’s table and identify baseline, target, unit, grouping, and direction of improvement.
  2. Verify every derived percentage with the correct denominator.
  3. Choose a layout based on metric count.
  4. Write one concise title and one factual description.
  5. Add model and run metadata when available.
  6. Apply the design tokens and browser shell.
  7. Use neutral gray for baseline and blue for target.
  8. Add an explicit lower is better or higher is better footer.
  9. Add responsive CSS.
  10. Check the final output against the quality checklist.

Quality Checklist

Before returning the HTML, verify:

  • All input values are present and correct.
  • Every percentage uses one consistent comparison direction.
  • Baseline is gray and target is blue.
  • Model metadata is black and semibold.
  • Secondary metadata is muted gray.
  • No gradients, glow, glassmorphism, or heavy shadow are present.
  • Metric identifiers use compact monospace styling.
  • The browser shell is visually subordinate to the data.
  • The chart remains usable on narrow screens.
  • Every class is namespaced.
  • The output is self-contained HTML/CSS with no JavaScript.

Reference Templates

Use the templates bundled with this skill as starting points:

  • templates/browser-native-dual-card.html: two-metric side-by-side comparison.
  • templates/browser-native-hybrid.html: overall metric plus subgroup/difficulty breakdown.

Replace placeholders carefully; do not change the design language unless the user asks.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Author or expand browser-agent benchmark tasks in data/real_world_bench.json (Odysseys schema, per-rubric graded). Use when creating, adding, or expanding real-world browser tasks, writing rubrics, or picking bot-friendly sites — every task MUST be verified runnable through ego-browser before it is written.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

Analyze Codex provider rollout JSONL and ego-benchmark-harness run artifacts to identify slow or failed individual tasks, tool retries, token/cost anomalies, and differences in agent execution paths. Use when users ask to analyze a Codex session or rollout, explain why a Codex task was slow or failed, inspect a Codex provider execution trace, compare Codex runs, count function_call or tool output events, or investigate agent-home/.codex/sessions.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

Export Codex rollout/session JSONL as a self-contained HTML report that can be opened offline. Use when a user provides a complete session file path or Codex session ID, or asks to export a Codex session to HTML, generate a session report, or convert a rollout to HTML. Supports exact full-ID lookup in the CODEX_HOME sessions and archived_sessions directories.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

Verify a tested web agent's real behavior from its recorded Pi or Codex session and selected screenshots before scoring. The judge prompt provides absolute artifact paths; use targeted queries to compare actual outputs, errors, and the final answer with the recorded behavior, then return only the verdict JSON. Only for ego-bench judging—never to drive a browser or rerun the agent.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

ego-browser (ego-lite) is a Chromium-based browser that gives AI agents a CLI-accessible Node.js runtime for driving a real browser. Use this skill whenever the user needs to interact with a website opening pages, filling forms, clicking buttons, taking screenshots, extracting page data, testing web apps, logging into sites, automating browser operations, or any other browser automation task. Triggers include requests to "open a website", "visit a URL", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "extract content from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also used for exploratory testing, dogfooding, QA, bug hunting, or reviewing app quality. Prefer ego-browser over any built-in browser automation, web fetch, or other web tools.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

keel

無料

Architecture design and governance protocol for system structure, boundaries, contracts, APIs, schemas, migrations, rewrites, and long-lived codebase health. Use when designing or reviewing architecture, planning structural refactors or migrations, governing tech debt, or containing rewrite risk. Keeps the load-bearing spine small, owned, checked, and deletable over time.

日本語の概要は準備中です。原文の説明を表示しています。

citrolabs/ego-browser-benchmark-framework92026年8月10日 更新

citrolabs のスキルをすべて見る

このスキルの問題を報告する