## Thinking Path > - Paperclip manages AI agents and prepares their runtime inputs before each turn. > - Shared company skills are part of those inputs for native and legacy adapters. > - Runtime materialization refreshed the full inventory again for every declared file. > - Remote skill directories were also downloaded and rebuilt on every turn. > - Measured preparation took 42–73 seconds while runner execution took 7–9 seconds. > - This change reads the inventory once and reuses validated installed revisions. > - Agents retain their selected skills while repeated preparation avoids upstream work. ## Linked Issues or Issue Description **What happened?** One 114-skill preparation performed 407 inventory refreshes, 48 directory rebuilds, and 388 GitHub file fetches. Reusing existing local copies took 151 ms. **Expected behavior** Each listing refreshes inventory once. Unchanged installed remote revisions reuse complete, validated local copies. Local edits remain visible. Explicit updates select new revisions. **Steps to reproduce** 1. Import GitHub skills with supporting files. 2. Run an agent turn, then run another with the same installed revisions. 3. Observe repeated inventory scans, downloads, and runtime directory replacement before execution. Related prior attempts: #2330 and #9268 (still open; #9268 last updated July 9). Those use a marker compared with `updatedAt`. This patch follows the required content validation, immutable revision, company isolation, atomic publication, and read-only semantics, and removes refresh-per-file multiplication. ## What Changed - Split public file reading from reading an already loaded skill. Runtime listing refreshes inventory once. - Add a company-scoped revision cache with file manifests outside the delivered skill directory. Fingerprints omit cosmetic metadata. - Validate exact file inventory, sizes, and hashes before warm reuse. Reject traversal and symlinks. Stage complete builds and serialize atomic publication across processes. - Preserve local/catalog direct sources, stored Markdown fallback, explicit version snapshots, and legacy mutable-ref compatibility. Report missing supporting files and keep older valid revisions readable. - Clean both runtime layouts on rename/removal and record `skills.prepare` under preparation timing. - Add service/cache regressions and an isolated 114-skill benchmark, including a new-process warm run. ## Verification - Final targeted skill-service/cache/trace validation: 86 tests pass (61 embedded-PostgreSQL service tests, 19 cache tests, 6 trace tests). Database tests executed rather than skipped. Focused skill routes, adapter selection, and native runtime context also pass. - `pnpm -r typecheck` and `pnpm build` pass locally at `22caa1fe4`. - The full `pnpm test:run` matrix passes on supported Linux CI at the final head: [CI run](https://github.com/paperclipai/paperclip/actions/runs/34236097762). Local full-suite execution encountered PostgreSQL startup contention, a random allocated-port boundary, and a socket hang-up; every affected suite passed on an isolated rerun. The interrupted local serialized run is not claimed as a complete local pass. - Repeatable benchmark: `pnpm --filter @paperclipai/server exec tsx ../scripts/benchmark-skill-preparation.ts`. Mixed 114-skill inventory with 429 remote files on Linux: cold 286 ms, warm median 96 ms / maximum 153 ms including a new process. Every warm sample performs one refresh, zero upstream fetches/rebuilds, and reports no missing entries; content assertions pass. - Controlled deployment against the previously deployed revision completed with zero lost runs. Real inventory: 114 skills, 670 declared files; 402 cached files match the prior installed copies byte-for-byte. Ten post-deployment warm preparations: median 129 ms / maximum 208 ms; new-process warm 194 ms, zero downloads/rebuilds/missing entries. - Five sequential real browser questions persisted in 10.6–20.7 s (median 12.2 s), versus 50–83 s before. Skill preparation median 240 ms, with one 2.37 s outlier. Total preparation median 3.337 s / maximum 8.728 s **does not fully meet** the <3 s / <5 s target. The excluded historical-run redaction query takes about 1.36 s per scan at two preparation call sites; wider application latency coincided with the outlier, without a cache rebuild. These residuals are reported rather than discarded. - Disposable skill reimport verified through actual selected-skill runs: the next run read the changed code. Fixture removed and agent configuration verified unchanged. - Greptile 5/5, zero unresolved review threads, all final-head CI checks green. ## Risks - Cold preparation still requires upstream availability for supporting files. An unavailable revision is reported missing and never falls back to an older revision. - Valid older revisions and quarantined invalid entries consume additive disk space until skill cleanup. An abruptly killed publisher can leave a lock that requires operator cleanup after confirming its PID is dead. - Warm validation reads all cached file bytes. Very large inventories still have proportional local I/O cost. - No HTTP API, schema, agent configuration, or first-party Telemetry changes. OpenTelemetry retains its operator endpoint gate. ## Model Used OpenAI GPT-6 in Codex, with reasoning, repository inspection, code editing, and test execution. The exact serving snapshot and context-window size are not exposed in this session. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work - [x] I have searched GitHub for duplicate or related PRs and linked them above - [x] I have either (a) linked existing issues with `Fixes: #` / `Closes #` / `Refs #` OR (b) described the issue in-PR following the relevant issue template - [x] I have not referenced internal/instance-local Paperclip issues or links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip` URLs) - [x] My branch name describes the change (e.g. `docs/...`, `fix/...`) and contains no internal Paperclip ticket id or instance-derived details - [x] I have run tests locally and they pass (targeted and isolated reruns; full Linux CI matrix passes, local full-run caveats above) - [x] I have added or updated tests where applicable - [x] I have updated relevant documentation to reflect my changes - [x] I have considered and documented any risks above - [x] All Paperclip CI gates are green - [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups - [x] I will address all Greptile and reviewer comments before requesting merge --------- Co-authored-by: Paperclip <noreply@paperclip.ing>
Quickstart · Docs · GitHub · Discord · Twitter · Website
Paperclip is the app people use to manage AI agents for work.
Open-source orchestration for teams of AI agents.
If OpenClaw is an employee, Paperclip is the company.
Paperclip is a Node.js server and React UI that orchestrates a team of AI agents to run a business. Bring your own agents, assign goals, and track work and costs from one dashboard.
It looks like a task manager. Under the hood: org charts, budgets, governance, goal alignment, and agent coordination.
Manage business goals, not pull requests.
| Step | Example | |
|---|---|---|
| 01 | Define the goal | "Build the #1 AI note-taking app to $1M MRR." |
| 02 | Hire the team | CEO, CTO, engineers, designers, marketers — any bot, any provider. |
| 03 | Approve and run | Review strategy. Set budgets. Hit go. Monitor from the dashboard. |
Paperclip is right for you if
- ✅ You want to build autonomous AI organizations
- ✅ You coordinate many different agents (OpenClaw, Codex, Claude, Cursor) toward a common goal
- ✅ You have 20 simultaneous Claude Code terminals open and lose track of what everyone is doing
- ✅ You want agents running autonomously 24/7, but still want to audit work and chime in when needed
- ✅ You want to monitor costs and enforce budgets
- ✅ You want a process for managing agents that feels like using a task manager
- ✅ You want to manage your autonomous businesses from your phone
The four pillars
Four things have to work for an organization of AI agents to actually produce: the tasks, the org, the training, and the infrastructure. Paperclip is built around exactly those four pillars.
| Pillar | Built for | What it covers |
|---|---|---|
| Agentic Task Manager — Declare intent. Agents work. You verify the output. | Everyone, daily | Tasks, approvals & review gates · proactive agent coworkers · auditable routines & workflows · verify from diffs, screenshots & tests |
| Org Chart for Agents — Roles, permissions & boundaries for humans and agents. | Managers | Mixed human + agent org chart · responsibilities, delegation, specialization · governance: who can do what · scoped secrets & company boundaries |
| Agent Employee Training — Design, train & evaluate your AI employees. | Enablers | Skill Studio & shared org-wide skills · evals & saved test runs · active learning loops & quality metrics · performance reviews for agents |
| Agentic OS — The infrastructure that makes the work run. | IT & platform | Cross-provider runtime: any model, any agent · sandboxing, integrations & MCP servers · SSO, GRC, RBAC & cost controls · data privacy, internal trace collection, compounding data value |
Features
🔌 Bring Your Own AgentAny agent, any runtime, one org chart. If it can receive a heartbeat, it's hired. |
🎯 Goal AlignmentEvery task traces back to the organization mission. Agents know what to do and why. |
💓 HeartbeatsAgents wake on a schedule, check work, and act. Delegation flows up and down the org chart. |
💰 Cost ControlMonthly budgets per agent. When they hit the limit, they stop. No runaway costs. |
🏢 Multi-OrganizationOne deployment, many organizations. Complete data isolation. One control plane for your portfolio. |
🎫 Ticket SystemEvery conversation traced. Every decision explained. Full tool-call tracing and immutable audit log. |
🛡️ GovernanceApprove hires, override strategy, pause or terminate any agent — at any time. |
📊 Org ChartHierarchies, roles, reporting lines. Your agents have a boss, a title, and a job description. |
📱 Mobile ReadyMonitor and manage your autonomous businesses from anywhere. |
Problems Paperclip solves
| Without Paperclip | With Paperclip |
|---|---|
| ❌ You have 20 Claude Code tabs open and can't track which one does what. On reboot you lose everything. | ✅ Tasks are ticket-based, conversations are threaded, sessions persist across reboots. |
| ❌ You manually gather context from several places to remind your bot what you're actually doing. | ✅ Context flows from the task up through the project and company goals — your agent always knows what to do and why. |
| ❌ Folders of agent configs are disorganized and you're re-inventing task management, communication, and coordination between agents. | ✅ Paperclip gives you org charts, ticketing, delegation, and governance out of the box — so you run a company, not a pile of scripts. |
| ❌ Runaway loops waste hundreds of dollars of tokens and max your quota before you even know what happened. | ✅ Cost tracking surfaces token budgets and throttles agents when they're out. Management prioritizes with budgets. |
| ❌ You have recurring jobs (customer support, social, reports) and have to remember to manually kick them off. | ✅ Heartbeats handle regular work on a schedule. Management supervises. |
| ❌ You have an idea, you have to find your repo, fire up Claude Code, keep a tab open, and babysit it. | ✅ Add a task in Paperclip. Your coding agent works on it until it's done. Management reviews their work. |
Why Paperclip is special
Paperclip handles the hard orchestration details correctly.
| Atomic execution. | Task checkout and budget enforcement are atomic, so no double-work and no runaway spend. |
| Persistent agent state. | Agents resume the same task context across heartbeats instead of restarting from scratch. |
| Runtime skill injection. | Agents can learn Paperclip workflows and project context at runtime, without retraining. |
| Governance with rollback. | Approval gates are enforced, config changes are revisioned, and bad changes can be rolled back safely. |
| Goal-aware execution. | Tasks carry full goal ancestry so agents consistently see the "why," not just a title. |
| Portable company templates. | Export/import orgs, agents, and skills with secret scrubbing and collision handling. |
| True multi-organization isolation. | Every entity is company-scoped, so one deployment can run many companies with separate data and audit trails. |
What's Under the Hood
Paperclip is a full control plane, not a wrapper. Before you build any of this yourself, know that it already exists:
┌──────────────────────────────────────────────────────────────┐
│ PAPERCLIP SERVER │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │Identity & │ │ Work & │ │ Heartbeat │ │Governance │ │
│ │ Access │ │ Tasks │ │ Execution │ │& Approvals│ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Org Chart │ │Workspaces │ │ Plugins │ │ Budget │ │
│ │ & Agents │ │ & Runtime │ │ │ │ & Costs │ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Routines │ │ Secrets & │ │ Activity │ │ Company │ │
│ │& Schedules│ │ Storage │ │ & Events │ │Portability│ │
│ └───────────┘ └───────────┘ └───────────┘ └───────────┘ │
└──────────────────────────────────────────────────────────────┘
▲ ▲ ▲ ▲
┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐
│ Claude │ │ Codex │ │ CLI │ │ HTTP/web │
│ Code │ │ │ │ agents │ │ bots │
└───────────┘ └───────────┘ └───────────┘ └───────────┘
The Systems
|
Identity & Access — Two deployment modes (trusted local or authenticated), board users, agent API keys, short-lived run JWTs, company memberships, invite flows, and OpenClaw onboarding. Every mutating request is traced to an actor. |
Org Chart & Agents — Agents have roles, titles, reporting lines, permissions, and budgets. Adapter examples match the diagram: Claude Code, Codex, CLI agents such as Cursor/Gemini/bash, HTTP/webhook bots such as OpenClaw, and external adapter plugins. If it can receive a heartbeat, it's hired. |
|
Work & Task System — Issues carry company/project/goal/parent links, atomic checkout with execution locks, first-class blocker dependencies, comments, documents, attachments, work products, labels, and inbox state. No double-work, no lost context. |
Heartbeat Execution — DB-backed wakeup queue with coalescing, budget checks, workspace resolution, secret injection, skill loading, and adapter invocation. Runs produce structured logs, cost events, session state, and audit trails. Recovery handles orphaned runs automatically. |
|
Workspaces & Runtime — Project workspaces, isolated execution workspaces (git worktrees, operator branches), and runtime services (dev servers, preview URLs). Agents work in the right directory with the right context every time. |
Governance & Approvals — Board approval workflows, execution policies with review/approval stages, decision tracking, budget hard-stops, agent pause/resume/terminate, and full audit logging. Nothing ships without your sign-off. |
|
Budget & Cost Control — Token and cost tracking by company, agent, project, goal, issue, provider, and model. Scoped budget policies with warning thresholds and hard stops. Overspend pauses agents and cancels queued work automatically. |
Routines & Schedules — Recurring tasks with cron, webhook, and API triggers. Concurrency and catch-up policies. Each routine execution creates a tracked issue and wakes the assigned agent — no manual kick-offs needed. |
|
Plugins — Instance-wide plugin system with out-of-process workers, capability-gated host services, job scheduling, tool exposure, and UI contributions. Extend Paperclip without forking it. |
Secrets & Storage — Instance and company secrets, encrypted local storage, provider-backed object storage, attachments, and work products. Sensitive values stay out of prompts unless a scoped run explicitly needs them. |
|
Activity & Events — Mutating actions, heartbeat state changes, cost events, approvals, comments, and work products are recorded as durable activity so operators can audit what happened and why. |
Company Portability — Export and import entire organizations — agents, skills, projects, routines, and issues — with secret scrubbing and collision handling. One deployment, many companies, complete data isolation. |
What Paperclip is not
| Not a chatbot. | Agents have jobs, not chat windows. |
| Not an agent framework. | We don't tell you how to build agents. We tell you how to run a company made of them. |
| Not a workflow builder. | No drag-and-drop pipelines. Paperclip models companies — with org charts, goals, budgets, and governance. |
| Not a prompt manager. | Agents bring their own prompts, models, and runtimes. Paperclip manages the organization they work in. |
| Not a single-agent tool. | This is for teams. If you have one agent, you probably don't need Paperclip. If you have twenty — you definitely do. |
| Not a code review tool. | Paperclip orchestrates work, not pull requests. Bring your own review process. |
Quickstart
Open source. Self-hosted. No Paperclip account required.
curl -fsSLO https://paperclip.ing/install.sh
curl -fsSLO https://paperclip.ing/install.sh.sha256
if command -v sha256sum >/dev/null 2>&1; then
sha256sum -c install.sh.sha256
else
shasum -a 256 -c install.sh.sha256
fi
bash install.sh
The installer ensures Node.js 24.11 or newer is available, installs a managed
Paperclip CLI under ~/.paperclip/cli, and starts interactive onboarding. It
can also install Paperclip as a background service on supported Linux and
macOS systems. The checksum detects transfer or publishing mistakes, but it is
served from the same origin as the script; use a release-tag or commit-pinned
GitHub copy when you need an independently hosted source.
For a non-interactive managed install:
curl -fsSL https://paperclip.ing/install.sh | bash -s -- --no-prompt --no-onboard
paperclipai onboard --yes
The piped form requires supported Node.js, npm, and npx to already be present.
If Node.js bootstrap is required, download and review install.sh before
running it so no privileged dependency-install command is accepted through a
pipe.
To try Paperclip without installing anything permanently:
npx --registry https://registry.npmjs.org paperclipai onboard --yes
For an isolated manual test instance that is already initialized with a CEO
agent, use test-drive. It stays in the foreground, never installs a service
or creates a first task, and opens the browser only after setup succeeds:
ANTHROPIC_API_KEY=... npx paperclipai test-drive
OPENAI_API_KEY=... npx paperclipai test-drive --harness codex
OPENROUTER_API_KEY=... npx paperclipai test-drive \
--harness opencode \
--model openrouter/anthropic/claude-sonnet-4.5
Each run without --data-dir gets a unique, retained temporary directory; its
absolute path is printed at startup. Pass --data-dir to reuse one, or
--no-browser to leave the initialized instance unopened. When invoked from a
linked Git worktree, test-drive also enables task execution in that worktree.
See doc/CLI.md for credential and
reuse behavior.
Troubleshooting: private npm registry
.npmrcIf this fails with an
E404forpaperclipai(or similar) and you use a private npm registry (for example GitHub Packages) via a global~/.npmrc,npxmay be resolvingpaperclipaiagainst that private registry instead of the public npm registry.Diagnostic:
npm config get registryWorkaround (cross-platform; force the public npm registry for this command):
npx --registry https://registry.npmjs.org paperclipai onboard --yes
That quickstart path now defaults to trusted local loopback mode for the fastest first run. To start in authenticated/private mode instead, choose a bind preset explicitly:
paperclipai onboard --yes --bind lan
# or:
paperclipai onboard --yes --bind tailnet
If you already have Paperclip configured, rerunning onboard keeps the existing config in place. Use paperclipai configure to edit settings.
See doc/INSTALLING.md for pinned versions, canary and
git-ref installs, updates, rollback, service management, and uninstalling.
Or manually:
git clone https://github.com/paperclipai/paperclip.git
cd paperclip
pnpm install
pnpm dev
This starts the API server at http://localhost:3100. An embedded PostgreSQL database is created automatically — no setup required.
Requirements: Node.js 24.11+, pnpm 9.15+
FAQ
What does a typical setup look like? Locally, a single Node.js process manages an embedded Postgres and local file storage. For production, point it at your own Postgres and deploy however you like. Configure projects, agents, and goals — the agents take care of the rest.
If you're a solo entrepreneur you can use Tailscale to access Paperclip on the go. Then later you can deploy to e.g. Vercel when you need it.
Can I run multiple companies? Yes. A single deployment can run an unlimited number of companies with complete data isolation.
How is Paperclip different from agents like OpenClaw or Claude Code? Paperclip uses those agents. It orchestrates them into a company — with org charts, budgets, goals, governance, and accountability.
Why should I use Paperclip instead of just pointing my OpenClaw to Asana or Trello? Agent orchestration has subtleties in how you coordinate who has work checked out, how to maintain sessions, monitoring costs, establishing governance - Paperclip does this for you.
(Bring-your-own-ticket-system is on the Roadmap)
Do agents run continuously? By default, agents run on scheduled heartbeats and event-based triggers (task assignment, @-mentions). You can also hook in continuous agents like OpenClaw. You bring your agent and Paperclip coordinates.
Development
pnpm dev # Full dev (API + UI, watch mode)
pnpm dev:once # Full dev without file watching
pnpm dev:server # Server only
pnpm dev:mobile # Serve prebuilt UI on :3101 for phones/tablets (proxies /api → :3100)
pnpm dev:both # Run `pnpm dev` and `pnpm dev:mobile` together
pnpm build # Build all
pnpm typecheck # Type checking
pnpm test # Cheap default test run (Vitest only)
pnpm test:watch # Vitest watch mode
pnpm test:e2e # Playwright browser suite
pnpm db:generate # Generate DB migration
pnpm db:migrate # Apply migrations
pnpm test does not run Playwright. Browser suites stay separate and are typically run only when working on those flows or in CI.
See doc/DEVELOPING.md for the full development guide.
Roadmap
- ✅ Plugin system (e.g. add a knowledge base, custom tracing, queues, etc)
- ✅ Get OpenClaw / claw-style agent employees
- ✅ companies.sh - import and export entire organizations
- ✅ Easy AGENTS.md configurations
- ✅ Skills Manager, Skill Studio & Skills Store
- ✅ Scheduled Routines
- ✅ Better Budgeting
- ✅ Agent Reviews and Approvals
- ✅ Multiple Human Users
- ✅ Cloud / Sandbox agents (e2b, Cloudflare, Daytona, Modal, Novita, self-hosted Kubernetes)
- ✅ Artifacts & Work Products
- ✅ Deep Planning (planning mode, revisioned plans, plan approvals)
- ✅ Enforced Outcomes (watchdogs, recovery actions, review gates)
- ✅ MCP Tool Gateway & Apps (governed tool access)
- ✅ Secrets Manager with per-agent access
- ✅ Activity log & action attribution
- ✅ Self-healing runs & automatic recovery
- ✅ Agent evals & feedback
- ⚪ Memory / Knowledge
- ⚪ MAXIMIZER MODE
- ⚪ Work Queues
- ⚪ Self-Organization
- ⚪ Automatic Organizational Learning
- ⚪ CEO Chat
- 🟡 Cloud deployments (multi-tenant isolation & company Import/Export shipped)
- ⚪ Desktop App
- ⚪ Bring-your-own-ticket-system (Asana / Linear / Jira as on-ramps)
- ⚪ Connected Apps (one-click integrations, e.g. Vercel)
This is the short roadmap preview. See the full roadmap in ROADMAP.md.
Community & Plugins
Find Plugins and more at awesome-paperclip
Observability
Paperclip ships with opt-in OpenTelemetry auto-instrumentation for the server (traces only). It activates when OTEL_EXPORTER_OTLP_ENDPOINT is set and supports grpc, http/protobuf, and http/json via the standard OTEL_EXPORTER_OTLP_PROTOCOL env var. @opentelemetry/api is a normal server dependency; the SDK, auto-instrumentation, and exporter packages are optional peer dependencies — install them only if you want tracing. See doc/observability.md for install commands and the full env-var reference.
Paperclip also ships with opt-in Sentry error monitoring for the server and the browser. Set SENTRY_DSN_FRONTEND to activate it for the browser and SENTRY_DSN_BACKEND to activate it for the server — each variable is optional, and the legacy SENTRY_DSN variable still works as a fallback for either component. The supported server SDK version is @sentry/node@10.71.0; it is an optional peer dependency for the server, so install it only if you want error monitoring. The browser SDK, @sentry/browser, is pinned to the same exact version. See doc/observability.md for the install command, the privacy settings, and the full default capture set.
Telemetry
Paperclip collects anonymous usage telemetry to help us understand how the product is used and improve it. No personal information, issue content, prompts, file paths, or secrets are ever collected. Private repository references are hashed with a per-install salt before being sent.
Contributors changing emitted telemetry events should follow the Telemetry Data Contract. For proposed first-party events that are not in the generated contract yet, follow Telemetry Workflow.
Telemetry is enabled by default and can be disabled with any of the following:
| Method | How |
|---|---|
| Environment variable | PAPERCLIP_TELEMETRY_DISABLED=1 |
| Standard convention | DO_NOT_TRACK=1 |
| CI environments | Automatically disabled when CI=true |
| Config file | Set telemetry.enabled: false in your Paperclip config |
Contributing
We welcome contributions. See the contributing guide for details.
Community
- Discord — Join the community
- Twitter / X — Follow updates and announcements
- GitHub Issues — bugs and feature requests
- GitHub Discussions — ideas and RFC
License
MIT © 2026 Paperclip Labs, Inc
Star History
Open source under MIT. Built for people who want to get work done, not babysit agents.
