Spool
Shared space for readable, searchable, resumable AI agent sessions
Spool fixes a real pain: turning dead-end agent logs into a searchable, shareable resource your team actually learns from. The share-before-resume flow is smart and privacy-respecting, but macOS-only is a hard limit for Windows/Linux shops. If you live in Claude, Codex, and Gemini daily, adopt it. For mixed-OS or non-agent teams, consider alternatives like Langfuse or Helicone for cloud-native tracing.
Verified 14d ago · liveness 64/100 · cite: rightaichoice.com/tools/spool
- Teams using multiple AI coding agents (Claude, Codex, Gemini) wanting a shared session history
- Developers on macOS who need local, searchable archives of agent sessions
- Privacy-conscious teams requiring on-device storage before sharing
- CLI power users who want to query or resume sessions from terminal
- Non-developers or teams not using agentic coding tools
- Windows or Linux users (macOS-only, Apple Silicon)
- Users needing cloud sync or multi-device access without manual sharing
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Skip Spool if you're on Windows or Linux, don't use agentic coding tools, or need automatic cloud sync across devices — it's macOS-only and local-first.
Sessions published as Public are searchable by anyone on the Explore page, so you must rely on the review step to avoid leaking sensitive code — a process overhead.
Spool is free and open-source (MIT), making it an attractive option for cost-conscious dev teams. Compared to paid cloud tracing tools like Langfuse or Helicone, Spool saves money but requires you to manage your own infrastructure and accept macOS-only support.
In short
Spool — Shared space for readable, searchable, resumable AI agent sessions. Best for Teams using multiple AI coding agents (Claude, Codex, Gemini) wanting a shared session history, Developers on macOS who need local, searchable archives of agent sessions, Privacy-conscious teams requiring on-device storage before sharing. Free to use.
What's new in Spool
Checked 14 days agoAcross the latest 1 update: 1 news mention.
What people actually say about Spool — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
100 mentions across 7 sources (Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, GitHub, Lemmy) · researched Aug 17, 2026.
Average across the 7 sources that answered — each source counts once, not each post.
- +Local-first privacy with all data on-device
- +Auto-indexes Claude, Codex, and Gemini sessions
- +Searchable library with fast FTS5 and AI modes
- +Share sessions as public or team links
- +Resume sessions in your own agent
- −Only works on macOS with Apple Silicon
- −No multi-device sync or cloud option
- −Setup requires installing daemon and CLI
- −Occasional indexing bugs or missed sessions
- −Niche tool: useless without AI coding agents
- • No hidden costs—totally free and open source
Viability Score
How well maintained and how widely used is Spool? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Auto-indexes Claude, Codex, and Gemini sessions
- Groups sessions by working directory project
- Browsable Library Home with recent and pinned sessions
- Global ⌘K search with Fast FTS5 and AI modes
- One-click pinning for easy retrieval
- CLI (spool search) for agent integration
- Daemon for background session monitoring
- Share sessions as public or team links
- Resume session from link in own agent
- Review sensitive data before publishing
- Session route map showing dead ends and goal path
- macOS (Apple Silicon) only
- Local-first, on-device index and queries
- /spool skill for Claude Code integration
- Publish sessions via npx @spool-lab/cli share
About Spool
Spool turns scattered AI agent sessions into a shared, searchable, resumable knowledge base for your team. It's a local-first macOS app (Apple Silicon) that streams sessions from Claude, Codex, and Gemini into one browsable library. You can search instantly with Fast FTS5 or ask an AI mode to synthesize answers from your local index. Everything stays on-device until you deliberately share it, keeping your agent traces private by default. Built for teams juggling multiple AI coding agents, Spool's `spool share` command publishes a session as a public or team link after a review step flags the exact record range and sensitive data. Teammates can read the session, see the route map showing dead ends and the final goal path, and then resume the work in their own agent with `spool resume`. This transforms private archives into collaborative artifacts — no cloud lock-in required. The tool runs as a background daemon, offers a CLI (`spool search`) and a `/spool` skill for Claude Code, letting any agent query your library. It's MIT-licensed and prioritizes privacy with local-first indexing. Compared to cloud-based alternatives like Langfuse or Helicone, Spool's local-first, open-source stance gives it a privacy edge, though it sacrifices the convenience of automatic multi-device sync. Spool is ideal for developers and teams who want to learn from past agent failures, share reasoning with colleagues, and avoid repeating dead ends. It's a niche tool — if you're not using agentic coding tools, you won't need it — but for those who do, it turns session chaos into a structured, resumable knowledge base.
Behind the Verdict
Spool addresses a genuine gap in the AI coding workflow: after an agent session ends, the reasoning, dead ends, and final approach usually vanish into a log file nobody reads. By automatically indexing sessions from Claude, Codex, and Gemini, Spool makes that history browsable and searchable. The route map feature is particularly clever — it visually shows which attempts failed and which path reached the goal, giving you a fast way to glean lessons without reading every token. Strengths: local-first storage means your session data stays on your machine until you share it, a privacy win over cloud tracing tools. The share-before-resume loop is practical: `spool share` reviews sensitive data, then a teammate reads the link and resumes in their own agent with `spool resume`. The CLI and `/spool` skill for Claude Code let you query the library programmatically, which power users will love. It's free and MIT-licensed. Weaknesses: macOS (Apple Silicon) only — no Windows or Linux support, so mixed-OS teams are out. There's no built-in cloud sync; multi-device access requires manual sharing, which doesn't scale as smoothly as cloud tools like Langfuse or Helicone. The tool is also only useful if you're actively using agentic coding tools; if you're not, it's dead weight. Where it fits: solo developers or small teams on macOS who use multiple AI agents and care about privacy, want to learn from past failures, and are comfortable with CLI workflows. Where it doesn't: enterprises needing cross-platform support, centralized dashboards, or compliance-grade audit trails. For those, a cloud solution may be a better fit.
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Real-world workflow fit
Concrete scenarios for the personas Spool actually fits — and what changes day-one when you adopt it.
After a frustrating debugging session with Claude Code, you want to find out if you tackled a similar issue before.
Outcome: You open Spool, search for 'JWT refresh', and instantly retrieve a past session where you solved it — you resume that approach and avoid repeating the same dead ends.
Your team uses Claude, Codex, and Gemini for different tasks, and you want everyone to learn from a tricky architecture decision made in one agent session.
Outcome: You run `spool share` on the session, review the sensitive-data findings, and paste the link into Slack. Teammates read the route map and can resume the session in their own agent.
Use Cases
- Browse all AI sessions related to a project in one view, regardless of which agent was used.
- Search your library using ⌘K to instantly find a past discussion on JWT rotation or idempotency keys.
- Pin critical sessions like architectural decisions or design patterns for quick access.
- Let Claude Code load relevant past sessions via the /spool skill when building on prior work.
- Set the daemon to automatically index new sessions as soon as they're created.
- Use the CLI in scripts or custom workflows to query session content programmatically.
Models Under the Hood
as of 2026-09-01
Limitations
- Spool is a CLI tool that requires manual sharing via public or team links; sessions are public in Explore and searchable by default.
- Publishing reviews the exact record range and sensitive-data findings before anything leaves the machine.
- The tool is macOS (Apple Silicon) only.
- Multi-device access requires manual sharing.
as of 2026-09-01
Verification history
We have re-verified Spool 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Spool tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo developers on macOS who use multiple AI agents and want a searchable, local archive without any cost.
What this tier adds
Starting tier: includes all core features (auto-indexing, search, sharing, resume) at $0/mo, with local-first storage.
Where the pricing makes sense
The company stage and team size where Spool's pricing actually pencils out — and where peers do it cheaper.
Spool is free and open-source (MIT), making it an attractive option for cost-conscious dev teams. Compared to paid cloud tracing tools like Langfuse or Helicone, Spool saves money but requires you to manage your own infrastructure and accept macOS-only support.
Setup time & first value
How long it actually takes to get something useful out of Spool — broken out by persona, not the marketing-page minute.
For solo devs: install the macOS app, run the daemon, and Spool auto-indexes existing sessions — first searchable content within minutes. For teams: each member installs Spool and 'spool share' a session; a new hire can start reading shared links immediately.
Switching to or from Spool
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Langfuse or Helicone: Export your session traces as JSON and import them into Spool's local index — it's a one-time manual process.
- ↗To Langfuse or Helicone: Reconstruct sessions from your local Spool library and manually upload them to the cloud tracing tool, but note the loss of live streaming.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Spool”, and we withheld 6: 6 could not be judged, because “Spool” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Spool.
Official links
Tools that pair well with Spool
Common stack mates teams adopt alongside Spool, with the specific reason each pairing earns its keep.
Bito
AI model router and code context engine that cuts coding agent token spend by grounding requests in your codebase.
Poolside AI
Open-weight agentic coding models — Laguna XS 2.1 and Laguna S 2.1 — built for secure on-prem and air-gapped enterprise AI.
Roo Code
Multi-agent AI coding assistant for VS Code, launching soon
Featured Head-to-Head Comparisons
Spool vs Gem
Gem and Spool serve completely different needs. Gem is a paid all-in-one recruiting platform for talent acquisition teams, while Spool is a free open-source macOS tool for developers to search and organize their AI coding sessions. Your choice depends entirely on role: recruiting vs. development.
Spool vs Poke Interaction Co
If you're a developer who lives in CLI and wants to search every AI coding session across agents without sending data to the cloud, Spool is the clear choice—and it's free. If you'd rather have an AI butler inside your messaging apps handling email, calendar, health, and automations, Poke's freemium tiers (Pro $19/mo) offer a more versatile, cross-platform assistant. Choose based on whether your pain point is 'finding old chat history' vs. 'getting tasks done without opening multiple apps.'
Spool vs Cognition Ai
Choose Spool if you're a developer needing to search and organize past AI sessions locally on macOS for free. Choose Cognition AI if you're an enterprise team needing an autonomous agent that writes, tests, and ships production code with a financial guarantee.
Alternatives to Spool
View all
Bito
AI model router and code context engine that cuts coding agent token spend by grounding requests in your codebase.
Poolside AI
Open-weight agentic coding models — Laguna XS 2.1 and Laguna S 2.1 — built for secure on-prem and air-gapped enterprise AI.
Frequently Asked Questions
Best-of guides
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