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feishu-tech-diagram

feishu-tech-diagram is a skill for Codex from zszz3/AgentRecall. It costs 52 tokens per session (1,058 once invoked), scanned A, original, MIT.

A guide for creating editable technical diagrams in Lark, also known as Feishu. It covers architecture, processes, data relationships, agent workflows, and other system views.

In plain words
What is it for?
Use it to create architecture diagrams, flowcharts, sequence diagrams, state models, roadmaps, and reliability or security views in editable Feishu whiteboards.
Why use it?
It helps turn complex system relationships into diagrams that are easier to review and update. It also checks for common layout problems such as overlaps, cut-off text, and unclear failure paths.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tests/validate_assets.py.

not rated 594repo +4 today A scan SkillSpector: pass 52 tokens original MIT

Good fit Use it to create architecture diagrams, flowcharts, sequence diagrams, state models, roadmaps, and reliability or security views in editable Feishu whiteboards.

Compare 6 skills from other repositories ↓
View source ↗ zszz3/AgentRecall
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/zszz3/AgentRecall
agentmods
npx agentmods add skills/zszz3/agentrecall/feishu-tech-diagram

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for feishu-tech-diagram

README.md
[![agentmods](https://agentmods.dev/badge/skills/zszz3/agentrecall/feishu-tech-diagram/github.svg)](https://agentmods.dev/skills/zszz3/agentrecall/feishu-tech-diagram)
Your own site
<a href="https://agentmods.dev/skills/zszz3/agentrecall/feishu-tech-diagram"><img src="https://agentmods.dev/badge/skills/zszz3/agentrecall/feishu-tech-diagram/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for feishu-tech-diagram

Your own site · 80×15
<a href="https://agentmods.dev/skills/zszz3/agentrecall/feishu-tech-diagram"><img src="https://agentmods.dev/badge/skills/zszz3/agentrecall/feishu-tech-diagram.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,058 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00052 $0.01058
Opus 5.5 $0.00021 $0.00423
Sonnet 5.5 $0.00010 $0.00212
Haiku 4.5 $0.00005 $0.00106

Measured 1mo ago against content hash fc7bb0b8d72a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

feishu-tech-diagram 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 1mo 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.

apps/main-2.0/assets/bundled-skills/feishu-tech-diagram/SKILL.md · 80 lines

What it actually says

飞书技术图表

先讲清关系，再处理布局和配色。图只补充正文，不重复正文；最终交付优先使用可编辑飞书画板。

必做流程

  1. 读取目标章节和相邻上下文；有现有画板时先回读代码、raw 节点或预览。
  2. 写图意图卡：一句话结论、目标读者、抽象层级、主链、分组、分支、方向和目标载体。
  3. 从 template-catalog.md 选择关系结构最接近的模板，再读取 template-specs.json 中同编号的输入、必备语义和坏味道。
  4. 打开 visual-examples.md 中同编号 SVG，只复用构图；必须替换示例里的通用节点。
  5. 生成后检查文字截断、节点重叠、交叉线、空白、抽象层级、边界、边标签和失败路径；最多迭代两轮，仍拥挤则拆图。
  6. 写入飞书前预览；覆盖已有画板先 dry-run，写入后回读验证。

图意图卡

一句话结论：
目标读者：
抽象层级：Context / Container / Component / Runtime / Process / Decision
主链：
分组：
分支或异常：
方向：LR / TB / 泳道 / 时序 / 状态 / 脑图
目标：本地 SVG 预览 / 新建可编辑画板 / 更新已有画板

选型规则

  • 先按“要回答的问题”选模板，不按视觉外形选。
  • 一张图只使用一个主要抽象层级；跨层信息拆成图组。
  • 主节点控制在 6–12 个；边超过 15 条或多条跨层回边时拆图。
  • 横向主链用 LR，稳定层次用 TB，角色协作用泳道，调用先后用时序。
  • 节点写“短标题 + 一行职责”，边标签写协议、动作、数据或条件。
  • Context 与安全图必须标系统或信任边界；生产评审图必须表达失败路径。

最小图组

  • 系统说明：Context + Container。
  • 核心链路：Container + 时序或数据流。
  • 生产评审：Container + 部署拓扑 + 故障传播 + SLO。
  • 安全评审：Context + 信任边界 + 认证授权 + 敏感操作审批。
  • Agent 系统：Context + Agent 平台 + 执行时序 + 工具权限 + Trace/Eval。

可编辑交付

  • 本地 SVG 只使用飞书画板可识别的基础形状、文字、连线和安全变换。
  • 写入飞书时使用 <whiteboard type="svg">...</whiteboard> 或 <whiteboard type="svg" path="@...">，让基础元素转换为可编辑节点。
  • 禁止用 PNG/JPEG 作为模板交付；位图只用于临时预览。
  • 多个模板写入同一文档时，每个画板紧跟对应模板说明，不集中堆到文档末尾。
  • 交付物不得包含水印、来源声明、会话链接、任务标识、真实业务名或账号信息。

资产

更新资产后运行：

python3 tests/validate_assets.py

交付检查

  • 主链、边界和结论三秒内可辨认。
  • 不含无依据新增的组件、依赖、日期或指标。
  • 同层对齐、同组同色，形状语义一致。
  • 箭头有方向，关键边有协议、动作、数据或条件。
  • 无文字截断、节点重叠、明显交叉线或大面积空白。
  • 飞书中的节点、文字和连线可以继续编辑。
  • 写入后已通过 preview、source 或 raw 至少一种方式回读。
Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago First seen · 80 lines · 52 tokens per session scan A fc7bb0b8d72a

Subscribe to this mod's changes

feishu-tech-diagram is a skill published in the GitHub repository zszz3/AgentRecall (594 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 1,058 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.

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