DottaandClaude Opus 5.5 0b20ea6fe9 fix(accounting): keep budget admission and usage handoff alive under run-row updates (#20484)
## Thinking Path

> - Paperclip is the open source app people use to manage AI agents for
work.
> - Before a run starts provider work, Paperclip reserves its budget and
binds a usage recorder. Both write the run's `heartbeat_runs` row.
> - Run-log appends, output progress and lifecycle events update that
same row while the run prepares and streams.
> - #20385 fixed this race for the standalone usage-receipt write only.
Budget admission and the recorder handoff still take a repeatable-read
snapshot before they lock the run row.
> - Each concurrent row update makes that snapshot stale. Four retries
run out with SQLSTATE `40001`, and the run ends `adapter_failed` with
raw SQL as its error.
> - This pull request applies the #20385 pattern (READ COMMITTED under
the existing locks) to those writers and to the final dispatch gate. It
also gives exhausted retries a bounded cause.
> - The benefit is that busy runs start and account normally, and a
remaining failure names its cause.

## Linked Issues or Issue Description

Refs #20385. Builds on #20483 (bounded failure cause and
`withoutSqlStatementText`).

**What happened?**

The restart-chaos L1 workload with `--db-pressure 4` (harness writers
that update each running run row, one row per statement, like a fast
stream) failed on master. In one wave, 0 of 4 tasks passed. Every first
run failed in `reserveRunBudget` before spawn. In an earlier wave, a run
failed in `createRunUsageRecorder`. The stack in both cases is `could
not serialize access due to concurrent update` (`40001`) on the run-row
`FOR UPDATE`. The board `runError` showed the full `select ... from
heartbeat_runs ... for update` statement. The server log line `heartbeat
execution failed` dropped the database cause.

Realism: the harness writers are synthetic, but the product has the same
writers on the same row. `appendHeartbeatRunEvent` increments
`next_event_seq`, output progress updates `last_output_*`, and lifecycle
events land while a run prepares. On a hosted database the window
between snapshot and row lock is wider than locally, so a busy run
reaches the same race without the harness.

**Expected behavior**

Budget admission and the recorder handoff commit while other writers
update the run row. Budget invariants stay intact: one reservation per
run, a reached hard stop still refuses work, and committed holds count
against later admissions. Usage receipts are journaled once. If retries
still run out, the run shows a bounded cause without SQL, and the server
log records the SQLSTATE.

**Steps to reproduce**

Run `server/src/services/run-accounting-contention.test.ts` against the
parent commit. The deterministic cases commit a real
`appendHeartbeatRunEvent` after the writer's transaction checks the
company and before it locks the run. Six of the eight cases fail with
`40001`.

## What Changed

- `reserveRunBudget` runs at READ COMMITTED. All mutable reads follow
the shared admission fences, the agent `FOR SHARE` lock and the run-row
`FOR UPDATE`. Exposure stays one SQL statement (hold-to-ledger atomic).
The `budget_reservations_run_idx` unique index and the run lock still
prevent a second hold.
- The final dispatch gate's accounting phase
(`dispatchResolvedInteractionIfCurrent` through `withIssueThenRunLocks`
in `run-dispatch/adapters/postgres.ts`) runs at READ COMMITTED. Its
ownership phase already read the same staleness facts at READ COMMITTED
under the same issue and run locks. Retry promotion and stale-run
cancellation keep their repeatable-read snapshot. The first L1 proof
wave found this writer exhausting `40001` once the other three were
fixed.
- `createRunUsageRecorder` runs its receipt-source handoff and its
capture-failure fence at READ COMMITTED. Both lock the run row first,
the same as `persistUsageReceipt` after #20385.
- `withOperationAccountingTransaction` raises
`AccountingContentionError` when retries run out. It has a bounded
message, `code` keeps the SQLSTATE (`40001`/`40P01`), `cause` keeps the
database error, and a warning logs both.
- `failRun` shows that bounded message. The code stays `adapter_failed`,
so chat and recovery retry paths still apply. #20483's `failureCause`
records `40001`. All other SQL text handling comes from #20483
(`withoutSqlStatementText`), unchanged here.
- `doc/DATABASE.md` documents the isolation choice and the failure
contract.

### Inventory of REPEATABLE READ / SERIALIZABLE transactions that write
run-scoped rows

| Writer | Status | Notes |
| --- | --- | --- |
| `persistUsageReceipt` (`usage-receipts.ts`) | Fixed in #20385 | READ
COMMITTED under the run lock. |
| `reserveRunBudget` (`budget-reservations.ts`) | Fixed here | Seen in
waves (`budget-reservations.ts:90`). |
| `createRunUsageRecorder` handoff (`usage-receipts.ts`) | Fixed here |
Seen in waves (`usage-receipts.ts:572`). |
| `createRunUsageRecorder` capture-failure fence (`persistFailure`) |
Fixed here | Same shape: run lock first, runs mid-stream. |
| Native finalizer `claimCoordinator` (`native-run-finalizer.ts`) | Safe
| A default READ COMMITTED transaction with `FOR UPDATE` on the
coordinator row. It cannot raise `40001`. The wave errors there were
`native_finalization_missing`, a symptom of the failed reservation (no
coordinator existed yet). |
| Final dispatch gate, accounting phase
(`dispatchResolvedInteractionIfCurrent`) | Fixed here | Seen in proof
wave `w-20261110T075857-s20386` (runs `140ddb10`, `c028c6c4`,
`fea0ee5a`). Its ownership phase already used READ COMMITTED under the
same locks with the same staleness reads. |
| Retry promotion and stale-run cancellation (`promoteOrCancelDueRetry`,
`cancelStaleQueuedRun`, same lock helper) | Follow-up | Kept at
repeatable read: `loadGateFacts` combines wakes, comments, dependencies,
tree holds and repair state in one decision. They act on queued or
scheduled runs, not streaming ones. Not seen failing in waves. If
retries run out, they now fail with the bounded cause. |
| Run settlement `accountRunCost` (`run-cost-accounting.ts`) | Follow-up
| Seen with `40001` in a wave log. Leaves the run pending;
`reconcileRunCosts` retries it durably. Multi-aggregate (coordinator,
receipts, images, closure). |
| Tool cost events (`paperclip-runner-tool-authority.ts`, `costs.ts`) |
Safe | Insert `cost_events` only; the run row is referenced, not locked
or updated. |
| Budget enforcement and evaluation (`budgets.ts`), billing
reconciliation, accounting-integrity repair | Safe | Lock policy,
invoice or company rows, not a streaming run row. Run reads are plain
selects. |
| Browser use, decisions, prompt-injection, fast responses | Safe |
Write their own invocation/reservation rows, not `heartbeat_runs`. |
| Read-only RR snapshots (`withAccountingReadSnapshot`, idle-sleep, tool
gateway, customer success, `routes/decisions.ts`) | Safe | Read only, or
no run-scoped writes. |

## Verification

- Red on the parent commit, green on this branch:
`server/src/services/run-accounting-contention.test.ts` (real embedded
PostgreSQL).
- `reserveRunBudget > reserves once when run events commit between its
company check and its run lock` (red: `40001`)
- `reserveRunBudget > reserves every run while back-to-back writers
update the run row` (red: `40001`)
- `reserveRunBudget > counts every committed hold, so successive
admissions never exceed the budget` (red)
- `reserveRunBudget > still refuses a run once the hard stop is reached`
(red: `40001` instead of `409`)
- `createRunUsageRecorder > binds its receipt source when run events
commit between its company check and its run lock` (red: `40001`; green
asserts the spooled receipt is journaled exactly once)
- `createRunUsageRecorder > binds while back-to-back writers update the
run row` (red: `40001`)
- `reserveRunBudget > never creates a second reservation for one run
when two dispatches race` (invariant; passes before and after)
- `final dispatch gate > admits and hands off a reserved run when run
events commit between its company check and its run lock` (red:
`AccountingContentionError` after 4 × `40001`)
- `createRunUsageRecorder > persists its capture-failure fence once when
run events commit between its company check and its run lock`
- `final dispatch gate > admits while back-to-back writers update the
run row` (red: `40001`)
- `exhausted retries > fail with a bounded, SQL-free cause that keeps
the SQLSTATE` (new contract)
- `run-completion.test.ts > saves a bounded cause and keeps the
retryable generic code when accounting retries are exhausted` (saved
code, message and `failureCause`, and log fields, through `failRun`)
- Related suites pass: `usage-receipts-read`,
`admission-independent-of-cleanup`, `budget-live-attempts`,
`idle-accounting-work`, `budget-enforcement-scoping`,
`closed-native-receipt-accounting`, `budget-evaluation-work`,
`run-dispatch/adapters/postgres`, `heartbeat/run-completion` (all 126
run-completion cases pass; its `afterAll` embedded-PostgreSQL teardown
exceeded 30 s on this loaded host, the known local flake).
- `pnpm --filter @paperclipai/server typecheck` passes.
- Latency of `reserveRunBudget` on the normal path (no contention,
embedded PostgreSQL, 350 measured reservations per run, 3 runs each):
before p50 14.7 / 15.0 / 18.6 ms, p95 25.6 / 31.4 / 39.4 ms; after p50
14.2 / 14.0 / 16.6 ms, p95 29.7 / 24.0 / 29.3 ms. No added latency: the
statements are the same, only the isolation level changes. Under
contention it removes the retry backoff.
- Live restart-chaos L1 waves (`--seed 20386 --db-pressure 4`, codex and
claude, K1):
- Master before this change: `w-20261110T050818-s20386`, 0/4. Every
first run failed in `reserveRunBudget` with `40001`.
- Head `90530789b0` (first three writers fixed):
`w-20261110T075857-s20386`, 2/4. Both codex tasks passed. Both claude
failures (t02, t03) trace to the dispatch gate, now fixed. Those runs
already showed the bounded cause, with no SQL on the board. The failure
was logged with `sqlState` 40001. No `reserveRunBudget` or recorder
`40001` remained.
- Head `d5ed21926f` (dispatch gate fixed): `w-20261110T090531-s20386`.
All 4 tasks reached done with no retry and R1–R6 passed. There were no
failed runs and zero `40001` in the server log, under 310k pressure
updates. Each task still failed the T-oracle `company_spend_settled`
with `pending_runs=1`. That pending run is t02's continuation run
`601ae80a`, cancelled before provider work as `issue_terminal_status`,
whose accounting debt was not yet settled when graded about 15 s later.
It is not a contention failure. Caveat: I edited the worktree during
this wave (`worktree_changed_mid_wave`), so a clean wave on the final
head follows.
- Final head `9f1c480717`, clean worktree: `w-20261110T094417-s20386`.
All 4 tasks reached done with no retry, and R1–R6 passed for each. There
were no failed runs and zero serialization failures in the server log,
under about 523k pressure updates. Each task still fails only the
T-oracle `company_spend_settled` (`pending_runs=1`). It is the same
cancelled pre-provider continuation run (`issue_terminal_status`), whose
accounting debt was still unsettled at grading. That is a separate
settlement-timing follow-up, not database contention. Master was 0/4 on
the same seed.

## Risks

- READ COMMITTED gives each statement its own snapshot. Admission reads
policy, scope and exposure in separate statements. The shared
company/project fences and the agent share lock exclude concurrent pause
and policy edits, and exposure stays one statement, so each read is at
least as fresh as the old snapshot.
- Concurrent admissions of different runs stay best-effort, as
`doc/SPEC-implementation.md` already states ("concurrent starts can
exceed the same observed balance"). This change does not widen that
window: each statement snapshot is newer than the old transaction
snapshot. It does not add a company mutex.
- A run that fails after exhausted retries now records
`accounting_contention` instead of `adapter_failed`. Retry rules that
key on `adapter_failed` spawn-like messages did not match this failure
before, so no automatic retry changes.
- No schema, migration or persisted-format change.

## Model Used

- Claude Opus 5.5 (Anthropic), model ID `claude-opus-5-5`, used through
Claude Code with shell, file-edit and code-execution tools.

## 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
- [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

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-10 03:47:48 -06:00
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Paperclip is the app people use to manage AI agents for work.

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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. Choose models and harnesses per agent while keeping your team's tasks, skills, permissions, and history in one place.

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.

Works
with
OpenClaw
OpenClaw
Claude Code
Claude Code
Codex
Codex
Cursor and Cursor Cloud
Cursor
+ Cloud
Gemini CLI
Gemini CLI
OpenCode
OpenCode
Pi
Pi
Hermes and Hermes Gateway
Hermes
+ Gateway
Grok Build
Grok Build
Kimi Code
Kimi Code

If it can receive a heartbeat, it's hired.

Custom processes, HTTP endpoints, and external adapter packages extend the roster. See the adapter overview for setup and capabilities.


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.

The four pillars of Paperclip
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 · connection permissions & responsible-user identities
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 · saved test inputs · skill version history & restore · reusable team templates
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 · personal & shared app connections · run history & opt-in tracing

Features

🔌 Bring Your Own Agent

Any agent, any runtime, one org chart. If it can receive a heartbeat, it's hired.

🎯 Goal Alignment

Link tasks and projects to your organization goals. Agents receive the goal context behind their work.

💓 Heartbeats

Agents wake for assigned work, follow-up messages, or configured schedules. Delegation flows up and down the org chart.

💰 Cost Control

Company, agent, and project budgets. Track reported spend, get threshold alerts, and pause work at configured limits.

🏢 Multi-Organization

One deployment, many organizations. Separate tasks, agents, permissions, and activity histories for each.

🎫 Task Threads

Keep conversations, plans, blockers, files, and run history attached to the work. Assign tasks to agents or people.

🛡️ Governance

Configure review and approval stages, approve hires, and pause, reassign, or stop work when needed.

📊 Org Chart

Hierarchies, roles, reporting lines. Your agents have a boss, a title, and a job description.

📱 Mobile Ready

Monitor and manage your autonomous businesses from anywhere.

🔗 Apps & Connections

Connect services such as GitHub, Notion, and Railway, or your own MCP server. Set gateway actions to Allowed, Ask first, or Off.

👥 Shared Agents, Personal Accounts

Choose who can use a connection and which agents can access it. Managed GitHub operations can use the account of the person directing the work.

🧠 Skills & Skill Studio

Install or write shared skills, test them with saved inputs, inspect results, and restore earlier versions.

📅 Scheduled Routines

Run recurring work on a schedule or trigger it through an API or webhook. Each run has a task, an owner, and a history.

📎 Artifacts & Feedback

Find the files and documents agents produce. Preview supported formats and leave comments on specific passages in documents.

📦 Ready-Made Teams

Preview and install teams with roles, skills, projects, and routines. Choose their runtimes and make the setup your own.

Experimental Agent Chat and chat/email connectors add conversations with agents in Paperclip and through configured services such as Slack, Discord, Telegram, and AgentMail. Enable the relevant instance settings to try them.


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. ✅ Spend tracking, budget alerts, and automatic pauses help you control the cost of ongoing work.
❌ You have recurring jobs (customer support, social, reports) and have to remember to manually kick them off. ✅ Routines create assigned tasks on a schedule, with outputs and run history you can inspect.
❌ 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 task checkout. A single assignee and execution locks prevent competing runs from claiming the same task.
Persistent work context. Tasks, comments, and documents stay in Paperclip. Supporting adapters resume saved sessions across runs.
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.
Accountable connections. Human access, agent eligibility, and gateway action permissions are separate controls. Approve a call once or save a revocable rule.
Goal-aware execution. Linked tasks and projects carry goal ancestry so agents see the "why," not just a title.
Portable company templates. Export/import orgs, agents, and skills with secret scrubbing and collision handling.
Organization boundaries. Company-scoped access checks keep each organization's work, agents, and activity separate within one deployment.

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), human roles and permissions, agent API keys, short-lived run JWTs, company memberships, and invite flows. Responsible-user attribution follows work through delegation and supported managed connections.

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. Search across work, review document revisions, and leave anchored feedback.

Heartbeat Execution — DB-backed wakeup queue with coalescing, budget checks, workspace resolution, secret injection, skill loading, and adapter invocation. Runs produce logs, usage records, and adapter-specific session state. Bounded recovery handles supported failures and surfaces cases that need human action.

Workspaces & Runtime — Project repositories and workspaces, optional isolated execution workspaces (git worktrees, operator branches), and runtime services (dev servers, preview URLs). Sandbox providers extend execution beyond the local host; availability depends on the configured environment and adapter.

Governance & Approvals — Board approval workflows, execution policies with review/approval stages, decision tracking, budget hard-stops, and agent pause/resume/terminate. Configured task reviews govern completion; connection action approvals govern calls through the tool gateway.

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. Enforcement uses recorded spend; usage reporting and in-flight work can delay a stop.

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 — Company secrets and per-person secret values, encrypted credential storage, local or S3-compatible file storage, attachments, and work products. Secret references supply credentials to authorized runs without copying values into ordinary agent configuration.

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 — Preview, export, and import organization packages with agents, skills, and optional projects, routines, tasks, and attachments. Referenced secret values are omitted; review packages before sharing because plain environment values and local paths can remain. Packages share an operating setup; full-instance recovery uses backups.


What Paperclip is not

Not just a chatbot. Conversations stay attached to tasks, plans, decisions, and outputs. Experimental Agent Chat can hand work off to assigned tasks.
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 just a workflow builder. Routines operate within an organization, with roles, goals, budgets, and governance.
Not a prompt manager. Agents bring their own prompts, models, and runtimes. Paperclip manages the organization they work in.
Not limited to one agent. Start with one agent and grow into a team with shared skills, delegation, and review.
Not only for code review. Coding and PR review fit alongside research, operations, content, and other work.

Quickstart

Open source. Self-hosted. No Paperclip account required. Follow the guided quickstart to set up your first agent.

Just ask your agent to install Paperclip

Share the installation guide with your agent.

Or install it yourself

With Node.js 24.11 or newer installed:

npx paperclipai@latest onboard --yes

The CLI runs from npm's cache; your instance configuration and data persist locally.

See the installation guide for managed installs, pinned versions, canary and git-ref installs, updates, rollback, service management, and uninstalling.

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 the test-drive guide for credential and reuse behavior.

Troubleshooting: private npm registry .npmrc

If this fails with an E404 for paperclipai (or similar) and you use a private npm registry (for example GitHub Packages) via a global ~/.npmrc, npx may be resolving paperclipai against that private registry instead of the public npm registry.

Diagnostic:

npm config get registry

Workaround (cross-platform; force the public npm registry for this command):

npx --registry https://registry.npmjs.org paperclipai@latest 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:

npx paperclipai@latest onboard --yes --bind lan
# or:
npx paperclipai@latest onboard --yes --bind tailnet

If you already have Paperclip configured, rerunning onboard keeps the existing config in place. Use npx paperclipai configure to edit settings.

Or manually:

git clone https://github.com/paperclipai/paperclip.git
cd paperclip
pnpm install
pnpm dev

This starts the UI and API at http://localhost:3100. An embedded PostgreSQL database is created automatically — no setup required.

Requirements: Node.js 24.11+, pnpm 9.15+

Local Claude and Codex subscription sign-in also needs Python 3 and the corresponding provider CLI on the Paperclip host. The Docker image includes them.

Source development also builds the native Paperclip Runner when enabled (the self-hosted default). Install a Rust toolchain, or set PAPERCLIP_RUNNER_BINARY to a compatible prebuilt runner.


FAQ

Q: Is this project maintained or just slop?

A: Paperclip is maintained by the Paperclip team. We've merged over 2,700 pull requests.


Q: What does a typical setup look like?

A: 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.

For remote access, use authenticated mode with a private-network bind such as Tailscale, or deploy the persistent server with Docker. See deployment modes and the Docker guide.


Q: Can I run multiple companies?

A: Yes. A single deployment can host multiple organizations with company-scoped data and access checks.


Q: How is Paperclip different from agents like OpenClaw or Claude Code?

A: Paperclip uses those agents. It orchestrates them into a company — with org charts, budgets, goals, governance, and accountability.


Q: Why should I use Paperclip instead of just pointing my OpenClaw to Asana or Trello?

A: 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)


Q: Do agents run continuously?

A: Agents wake for assigned work and follow-up messages. Optional timer heartbeats let them check for work periodically; routines create recurring tasks on their own schedules. You can also connect externally running agents such as OpenClaw. A mention alone does not assign work or wake another agent.


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, boxd, 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
  • ✅ Connected Apps
  • ✅ Personal & Shared AI Accounts
  • ✅ Shared Agents Use Personal GitHub Identities
  • ✅ Skill Version History & Restore
  • ✅ Document Comments & Revision History
  • ✅ Company-Wide Search
  • ✅ Multi-Model & Multi-Harness Teams
  • 🟡 Memory / Knowledge
  • ⚪ MAXIMIZER MODE
  • ⚪ Work Queues
  • ⚪ Self-Organization
  • ⚪ Automatic Organizational Learning
  • 🟡 Agent Chat
  • 🟡 Cloud deployments
  • ⚪ Desktop App
  • ⚪ Bring-your-own-ticket-system (Asana / Linear / Jira as on-ramps)

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.

We're hiring


Community


License

MIT © 2026 Paperclip Labs, Inc

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