generate-media

generate-media is a skill for Claude Code, Codex from anymouschina/TapCanvas. It costs 88 tokens per session (1,474 once invoked), scanned A, original, MIT.

A media-production workflow for creating reusable character cards, scene and prop references, and storyboard images for short dramas or novels.

In plain words
What is it for?
Use it to generate and track role cards, scene and prop references, special-effects references, storyboard frames, and media indexes.
Why use it?
It keeps generated visual assets connected to chapters and style rules, making recurring characters and locations easier to represent consistently.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to generate and track role cards, scene and prop references, special-effects references, storyboard frames, and media indexes.

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Install with agentmods
npx agentmods add skills/anymouschina/tapcanvas/generate-media
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.

Any agent
npx skills add anymouschina/TapCanvas --skill generate-media
Clone the repo
git clone --depth 1 https://github.com/anymouschina/TapCanvas

Made for: Claude Code, 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 generate-media

README.md
[![agentmods](https://agentmods.dev/badge/skills/anymouschina/tapcanvas/generate-media/github.svg)](https://agentmods.dev/skills/anymouschina/tapcanvas/generate-media)
Your own site
<a href="https://agentmods.dev/skills/anymouschina/tapcanvas/generate-media"><img src="https://agentmods.dev/badge/skills/anymouschina/tapcanvas/generate-media/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 generate-media

Your own site · 80×15
<a href="https://agentmods.dev/skills/anymouschina/tapcanvas/generate-media"><img src="https://agentmods.dev/badge/skills/anymouschina/tapcanvas/generate-media.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,474 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 $0.00088 $0.01474
Opus 5 $0.00044 $0.00737
Sonnet 5 $0.00018 $0.00295
Haiku 4.5 $0.00009 $0.00147

Measured 11d ago against content hash 6c1a782ce9d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

generate-media 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 11d 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/agents-cli/skills/generate-media/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generate Media (TapCanvas Public API)

Goal

将短剧/小说分镜生产链路中的“角色卡与分镜图”从简化版本升级为可复用的生产素材,且统一走 TapCanvas 公共接口:

  • 图像生成:通过 tapcanvas-api 调用 /public/draw
  • 任务轮询:通过 tapcanvas-api 调用 /public/tasks/result

禁止直接在技能内耦合三方 SDK(如 google-genai);模型选择通过 extras.modelAlias 完成。

Required Inputs

  • 项目与作品标识:projectIdbookId
  • 目标章节或集数范围:chapterstart/end
  • 视觉风格:assets.styleBiblestyleLockedconsistencyRulesnegativeDirectivesreferenceImages
  • 角色/场景/道具元数据:chapters[].characters/props/scenes/locations
  • 已有角色卡:assets.roleCards(用于一致性参考)

Output Contract

必须产出并回填以下结构(无兜底):

  1. roleCards: 每角色至少 1 张主参考图(可选多视角合成) 1.5 visualRefs:
    • category=scene_prop:每章节至少 1 张“场景+道具”参考图(默认单张 3x3 九宫格,最多 9 个元素)
    • category=spell_fx:涉及法术/特效时至少 1 张特效参考图
  2. storyboardChunks: 每组镜头输出 frameUrlstailFrameUrl
  3. ref_indexmedia_index(按 book 维度)
  4. 若任一步骤关键输入缺失,直接失败并返回可追踪错误

Workflow

  1. 触发判定(先判定再生成)

    • 非强制全量生成。仅当资产满足“可复用/需持久化”条件时触发生图。
    • 推荐判定:同名角色/场景/道具在跨章节复现(>=2 章)或被上游显式标记为长期锚点。
    • 未命中持久化条件时,不应为了凑齐素材而生成新图。
  2. 风格锁定检查

    • 若缺少已确认角色卡,不再中断流程;进入自动补齐阶段。
  3. 角色卡生成(Phase 1)

    • 以角色档案 + 章节阶段信息生成结构化 prompt。
    • 使用 tapcanvas-api/public/drawkind=image_edit|text_to_image(按是否有参考图决定)。
    • 将结果写回 assets.roleCards,状态置为 generated
    • 分镜流程内若发现缺失角色卡,仅对“持久化候选角色”自动补齐,不要求用户先手工生成。
  4. 场景/道具参考图(Phase 1B/1C)

    • 从章节聚合 scenes/props,优先一次生成“单张 3x3 九宫格(9格)”参考图。
    • 每格对应 1 个场景/道具元素,使用格位标签(1-9)与元素名建立映射。
    • 结果写入 assets.visualRefscategory=scene_prop),供分镜与视频参考。
    • 元数据必须包含:layout=3x3cellLabels(如 #1:窗边木桌)。
    • 分镜流程内若缺少 scene_prop,仅在命中“持久化候选场景/道具”时自动补齐。

3.5 法术技能/特效参考图(Phase 1D)

  • 从章节冲突/动作节点提取法术或特效线索,生成稳定特效参考图。
  • 结果写入 assets.visualRefscategory=spell_fx)。
  1. 分镜图生成(Phase 2)
    • 按组(4/9)处理镜头,首镜必须注入上一组 tailFrameUrl
    • 每镜头都需注入角色参考图 + 场景道具参考图;涉及特效时再注入特效参考图。
    • 参考图必须标注(角色名/场景道具名/特效名),并把引用 ID 回写到 storyboardChunks
    • 任何镜头未返回图片即失败,不允许模板兜底。
    • 在生成前,优先调用 tapcanvas_storyboard_continuity_get 校验上一组 tailFrameUrl、显式 chunk checkpoint、角色卡、视觉参考与 style bible 是否齐备。
    • recentShots / storyboard history 仅用于诊断,不得替代 chunk checkpoint 或 tail frame 作为续写边界。

Read the full file on GitHub · 93 lines

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. 11d ago First seen · 93 lines · 88 tokens per session scan A 6c1a782ce9d4

Subscribe to this mod's changes

generate-media is a skill published in the GitHub repository anymouschina/TapCanvas (602 stars, last pushed 2d ago), licensed MIT. It adds 88 tokens to every session and 1,474 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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