report-generator

report-generator is a skill for Claude Code, Codex from bytedance/agentkit-samples. It costs 89 tokens per session (1,097 once invoked), scanned A, original, Apache-2.0.

A video-analysis report generator that combines shot breakdown data with optional opening-hook analysis and writes a structured Markdown report.

In plain words
What is it for?
Use it to prepare video-analysis documents, review creative work, or create competitor-video reports from JSON data.
Why use it?
It removes the need to assemble video details, music notes, scene findings, and recommendations by hand. It can also produce a report from shot data alone.

Skill for Claude CodeCodex

About the project

bytedance/agentkit-samples is a collection of examples and tutorials for Volcengine AgentKit, an AI-agent development platform for building, deploying, and operating agent applications. Developers use the samples to learn agent creation, multi-agent collaboration, memory, retrieval, MCP integrations, media generation, customer service, and other workflows. The catalogue skills provide agent workflows based on these examples.

bytedance/agentkit-samples · 446 stars · on GitHub

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/bytedance/agentkit-samples/report-generator-skill
Any agent
npx skills add bytedance/agentkit-samples --skill report-generator-skill
Clone the repo
git clone --depth 1 https://github.com/bytedance/agentkit-samples

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 report-generator

README.md
[![agentmods](https://agentmods.dev/badge/skills/bytedance/agentkit-samples/report-generator-skill.svg)](https://agentmods.dev/skills/bytedance/agentkit-samples/report-generator-skill)
Your own site
<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/report-generator-skill"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/report-generator-skill.svg" alt="Measured on agentmods" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,097 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 $0.00089 $0.01097
Opus 5 $0.00044 $0.00549
Sonnet 5 $0.00018 $0.00219
Haiku 4.5 $0.00009 $0.00110

Measured 4d ago against content hash 8cf6a4ccf7b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

report-generator 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 4d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/generate_report.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

python/02-use-cases/video_breakdown_agent/.skills/report-generator-skill/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

视频分析报告生成 (Report Generator)

概述

视频分析报告生成技能将分镜拆解数据和(可选的)钩子分析结果整合为一份专业的 Markdown 格式分析报告。报告包含视频基本信息、前三秒钩子评分、分镜概览表格、BGM 分析、场景分析和平台推荐等章节。

适用场景

  1. 视频分析交付:为客户或团队生成完整的视频分析文档
  2. 创意复盘:生成结构化的视频内容复盘报告
  3. 竞品报告:批量生成竞品视频分析报告

使用步骤

完整报告(分镜 + 钩子分析)

# 1. 准备分镜拆解数据和钩子分析数据(JSON 文件)
# 2. 生成报告
python scripts/generate_report.py breakdown.json hook_analysis.json

# 3. 保存到文件
python scripts/generate_report.py breakdown.json hook_analysis.json > report.md

仅分镜报告(无钩子分析)

python scripts/generate_report.py breakdown.json

报告结构

生成的报告包含以下章节:

# 视频分析报告

## 基本信息
- 视频时长、分镜数量、分辨率

## 前三秒钩子分析(核心)
- 综合评分
- 5维度评分表格
- 钩子类型
- 优势/不足/优化建议
- 留存预测

## 分镜概览
- 前10个分镜的概览表格

## BGM 分析
- 音乐风格、情绪基调、节拍

## 场景分析
- 主要场景、视频风格、目标受众
- 平台推荐

报告生成时间

输入格式

breakdown.json(必需)

{
  "duration": 30.5,
  "segment_count": 12,
  "resolution": "1920x1080",
  "segments": [...],
  "bgm_analysis": {
    "music_style": {"primary": "流行"},
    "emotion": {"primary": "欢快"},
    "tempo": {"bpm_estimate": 120, "pace": "中速"}
  },
  "scene_analysis": {
    "primary_scene": "室内",
    "video_style": {"overall": "生活方式", "target_audience": ["年轻人"]},
    "platform_recommendations": [...]
  }
}

hook_analysis.json(可选)

{
  "overall_score": 7.5,
  "visual_impact": 8.0,
  "visual_comment": "评价...",
  "language_hook": 7.0,
  "language_comment": "评价...",
  "emotion_trigger": 7.5,
  "emotion_comment": "评价...",
  "information_density": 7.0,
  "info_comment": "评价...",
  "rhythm_control": 8.0,
  "rhythm_comment": "评价...",
  "hook_type": "好奇型",
  "strengths": ["优点1", "优点2"],
  "weaknesses": ["不足1"],
  "suggestions": ["建议1", "建议2"],
  "retention_prediction": "中:50-70%,因为..."
}

输出格式

Markdown 格式的完整报告文本,直接输出到 stdout。

示例

# 完整流程
python ../video-breakdown-skill/scripts/process_video.py "https://example.com/video.mp4" > breakdown.json
cat breakdown.json | python ../hook-analyzer-skill/scripts/analyze_hook_segments.py - > hooks.json
# (hooks.json 需经 LLM 评分后得到 hook_analysis.json)
python scripts/generate_report.py breakdown.json hook_analysis.json > report.md

Read the full file on GitHub · 141 lines

Files

What ships with it

1 file 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. 4d ago First seen · 141 lines · 89 tokens per session scan A 8cf6a4ccf7b7

Subscribe to this mod's changes

report-generator is a skill published in the GitHub repository bytedance/agentkit-samples (446 stars, last pushed today), licensed Apache-2.0. It adds 89 tokens to every session and 1,097 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 2026-08-31.

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