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 agents/thibautmelen/agentic-ai-systems/multi-windowgit clone --depth 1 https://github.com/ThibautMelen/agentic-ai-systemsWhat 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 | $0.00000 | $0.01623 |
| Opus 5 | $0.00000 | $0.00812 |
| Sonnet 5 | $0.00000 | $0.00325 |
| Haiku 4.5 | $0.00000 | $0.00162 |
Grade A, and why
multi-window scanned grade A with 0 findings against 26 rules in 11 categories โ prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency โ measured yesterday.
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 โ 225 lines โ stays where its author put it; the contents beside it link to each section on GitHub.
๐ Home โบ Autonomous โบ ๐ฅ๏ธ Multi-Window Context
โ Autonomous Agent โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Autonomous โ
๐ฅ๏ธ Multi-Window Context
TL;DR: State persistence across Claude Code sessions. Checkpoint your progress, resume from interruptions. Essential for long-running workflows.
Diagram
%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart TB
classDef checkpoint fill:#f59e0b,stroke:#d97706,stroke-width:2px,color:#ffffff
classDef state fill:#10b981,stroke:#059669,stroke-width:2px,color:#ffffff
subgraph Session1["Session 1"]
S1P1["๐๏ธ Phase 1"] --> S1CP["๐ฅ๏ธ Checkpoint"]:::checkpoint
S1CP --> S1P2["๐ Phase 2"]
S1P2 --> INTERRUPT["โ Interrupt"]
end
subgraph Session2["Session 2 (Resume)"]
RESUME["๐ Resume"] --> S2P2["Continue Phase 2"]
S2P2 --> S2P3["๐ Phase 3"]
S2P3 --> DONE["โ
Complete"]
end
S1CP -.->|๐พ State saved| STATE[("๐พ State Store")]:::state
STATE -.->|๐พ State loaded| RESUME
classDef session1Box fill:#fef2f2,stroke:#ef4444,stroke-width:2px,color:#991b1b
classDef session2Box fill:#ecfdf5,stroke:#10b981,stroke-width:2px,color:#065f46
Session1:::session1Box
Session2:::session2Box
When to Use
- Large-scale generation (1000+ files)
- Long research tasks
- Multi-day workflows
- Error recovery needs
- Context window limitations
Implementation
Session 1:
1. Work on Phase 1
2. Save checkpoint (progress, decisions, context)
3. Continue until context limit or interruption
Session 2:
1. Load checkpoint
2. Resume from saved state
3. Continue execution
Flow Example
๐ฅ๏ธ MULTI-WINDOW CONTEXT
Session 1: ๐โโ๏ธ๐ฅ โโโบ ๐๐ โโโบ ๐โก โโโบ ๐ฅ๏ธ๐พ โโโบ [Context Limit]
โ
Session 2: ๐ฅ๏ธ๐พ โโโบ ๐โก โโโบ ๐๐ โโโบ ๐๐ญ โโโบ ๐โโ๏ธ๐ค
Checkpointing for Long Workflows
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.
- yesterday First seen ยท 225 lines ยท 0 tokens per session scan A 5b378c76fcfc
multi-window is an agent published in the GitHub repository ThibautMelen/agentic-ai-systems (301 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,623 tokens. 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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