create-canvas

A tool for creating a one-page or multi-section visual research report on a canvas. It combines written findings, tables, statistics, charts, and quotations in a report layout.

In plain words
What is it for?
Use it for investment research canvases, comparison-table reports, and other one-page institutional-style reports built from available market, financial, or news data.
Why use it?
It gives research a reviewable visual format when a normal web page or a small chart is not the requested delivery. It also keeps facts separate from conclusions.

Skill for Claude CodeCodex

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 skills/travisun/opptrix/create-canvas
Any agent
npx skills add Travisun/Opptrix --skill create-canvas
Clone the repo
git clone --depth 1 https://github.com/Travisun/Opptrix

Made for: Claude Code, Codex.

Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 758 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 $0.00088 $0.00758
Opus 5 $0.00044 $0.00379
Sonnet 5 $0.00018 $0.00152
Haiku 4.5 $0.00009 $0.00076

Measured 3d ago against content hash 48827eb5a692, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-canvas 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 3d ago.

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.

packages/agent-skills/builtin/create-canvas/SKILL.md · 56 lines

What it actually says

投研画布(备选交付)

何时使用

用户明确点名要一份可预览的画布 / 一页式机构风图文报告(对比表、多章节 TSX 排版)。

默认投研交付是网页@skill:create-web / create_web)。未点名画布时,投研技能应优先 create_web,不要主动改用本技能。

与网页 / 围栏的区别

形态 何时用
create_web(默认) 投研 HTML 报告页、离线交互页
create_canvas(本技能) 用户点名画布 / 一页式机构报告
正文 chart 围栏 日常定量小插图,无需 artifacts

「画个柱状图」→ 优先围栏;「出一份画布报告」→ 本技能。

步骤

  1. 确认交付形态:用户已点名画布/一页式机构报告;否则转 create_web
  2. 取数:用已有行情/基本面/资讯等工具;缺失写明,禁止编造。
  3. 创建画布create_canvas 写入 TSX source。仅允许 import … from 'react'import { … } from '@opptrix/canvas';用 Surface / Stack / H1H3 / Text / Stat / Table / Chart / Callout / Quote 等 curated 组件。
  4. 版式:机构调研报告风格——H1 → 导语 → H2 分章;定量优先 Chart;须有说明文字。
  5. 更新:已有画布先 read_canvas,再 update_canvas
  6. 输出边界:事实与推断分开;不给出买卖建议。

禁止

  • 外网 CDN、任意第三方 npm/脚本(含直接 import echarts
  • 荐股、编造数据
  • workspace_write 代替 create_canvas
  • 把未点名画布的投研流程默认做成画布(应优先 create_web

与网页技能分工

  • 默认投研 HTML 报告 → @skill:create-web
  • 用户点名画布 → 本技能
  • 只要结构图 → @skill:create-mindmap
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. 3d ago First seen · 56 lines · 88 tokens per session scan A 48827eb5a692

Subscribe to this mod's changes

create-canvas is a skill published in the GitHub repository Travisun/Opptrix (224 stars, last pushed 5d ago), licensed Apache-2.0. It adds 88 tokens to every session and 758 once invoked, about $0.0004 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 2026-08-30.

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