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.
npx agentmods add commands/catlog22/claude-code-workflow/animation-extractgit clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00019 | $0.10115 |
| Opus 5 | $0.00010 | $0.05058 |
| Sonnet 5 | $0.00004 | $0.02023 |
| Haiku 4.5 | $0.00002 | $0.01012 |
Grade A, and why
animation-extract 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 1,155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Mode
When --yes or -y: Skip all clarification questions, use AI-inferred animation decisions.
Animation Extraction Command
Overview
Extract animation and transition patterns from prompt inference and image references using AI analysis. Directly generates production-ready animation systems with complete animation-tokens.json.
Strategy: AI-Driven Animation Specification with Visual Previews
- Dual Modes: Exploration mode (generate from scratch) or Refinement mode (fine-tune existing)
- Prompt Inference: AI analyzes design intent from textual descriptions and image references
- Question Generation: Agent generates context-aware specification questions with visual previews
- Refinement Options: Fine-tune timing, easing, context variations, and interaction intensity
- Visual Previews: Timeline representations, easing curve ASCII art, and animation sequence diagrams
- Flexible Input: Image references and prompts for animation specification
- Optional Interaction: User answers questions only when
--interactiveflag present - Production-Ready: CSS var() format, WCAG-compliant, semantic naming
- Default Behavior: Non-interactive mode uses inferred patterns + best practices
Execution Process
Input Parsing:
├─ Parse flags: --design-id, --session, --images, --focus, --interactive, --refine
└─ Decision (mode detection):
├─ --refine flag → Refinement Mode
└─ No --refine → Exploration Mode
Phase 0: Setup & Input Validation
├─ Step 1: Detect input mode & base path
├─ Step 2: Prepare image references (if available)
├─ Step 3: Load design tokens context
└─ Step 4: Memory check (skip if exists)
Phase 1: Animation Specification Generation
├─ Step 1: Load project context
├─ Step 2: Generate animation specification options (Agent Task 1)
│ └─ Decision:
│ ├─ Exploration Mode → Generate specification questions
│ └─ Refinement Mode → Generate refinement options
└─ Step 3: Verify options file created
Phase 1.5: User Confirmation (Optional)
└─ Decision (--interactive flag):
├─ --interactive present → Present options, capture selection
└─ No --interactive → Skip to Phase 2
Phase 2: Animation System Generation
├─ Step 1: Load user selection or use defaults
├─ Step 2: Create output directory
└─ Step 3: Launch animation generation task (Agent Task 2)
Phase 3: Verify Output
├─ Step 1: Check files created
└─ Step 2: Verify file sizes
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.
- 2d ago First seen · 1,155 lines · 0 tokens per session scan A 2ca46c8370be
animation-extract is a command published in the GitHub repository catlog22/Claude-Code-Workflow (2,134 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 10,115 once invoked, about $0.0001 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.
Other commands, from other repositories
ytdl
Download a video/podcast via yt-dlp, transcribe with whisper.cpp, save as markdown in llm-wiki.
verify-claim
Walk a claim through the SIFT method (Stop, Investigate, Find better coverage, Trace).
beat-brief
Draft a daily beat briefing from the files in sample-docs/.
hushflow
Configure HushFlow.
stts
User speaks the prompt, which is sent to the Model, the received response is spoken/read aloud in a loop.
cross-review
Run GitHub Copilot CLI and OpenAI Codex against the current git diff for cross-model review.