026bdcd046 perf(ci): run the verifier's bundled-dependency installs concurrently (#15868)
## Thinking Path

> - Paperclip is the open source app people use to manage AI agents for
work
> - Every pull request runs the `Build` check. Its last step is the
public npm install verifier, `scripts/verify-grok-npm-install.mjs`,
which stages the eighteen public packages and installs them in a clean
consumer.
> - The verifier stages the packages in one serial loop. Three packages
bundle dependencies (`@paperclipai/server`,
`@paperclipai/adapter-utils`, `@paperclipai/db`). Each one runs a
host-side `npm install` of its bundled closure in-process, one after the
other, and nothing in the loop overlaps anything else. The staging phase
took 102-116s on recent `Build` jobs.
> - `Build` at 433-530s is the slowest check in most PR runs once the
server shards drop, so its staging phase sets the wall-clock time of the
run.
> - The three installs write only their own directories and read nothing
from each other. There is no reason to run them one after the other.
> - This pull request starts the three installs together as child
processes and copies the other fifteen packages while they run. Packing
stays serial and in order.
> - The benefit is a shorter `Build` job, and a timing line that reports
each install, so the saving is measured on this PR's own run instead of
estimated.

## Linked Issues or Issue Description

Refs #15861. This branch is stacked on the branch of #15861 because the
same execution branch holds that open PR. The diff here is this PR's
three commits. After #15861 merges, this PR is retargeted to `master`
and rebased.

**What existing behavior does this improve?**

The `Build` PR check. Its public npm install verifier stages the
eighteen public packages in one serial loop.

**Subsystem affected**

CI and release scripts (`scripts/verify-grok-npm-install.mjs`,
`scripts/prepare-bundled-package.mjs`, `scripts/prefetch-child.mjs`,
`scripts/prefetch-supervisor.mjs`).

**Current behavior**

The staging loop calls `prepareBundledPackage` in-process for the three
packages that bundle dependencies. Each call runs a host-side `npm
install` of that package's bundled closure, applies the repo patches,
and rewrites the manifest, before the loop moves to the next package.
The timing line reports the whole staging phase as one number, 102-116s
on recent runs. The three installs are the only network work in that
phase.

**Proposed behavior**

Stage the three bundled packages' sources first, start their installs at
the same time as children of the script's own CLI entry (the same path
`release.sh` uses), copy the other fifteen packages while the installs
run, join the installs, and then pack every package in dependency order
as before. Report `stage_sources_ms`, `stage_bundled_ms`,
`stage_pack_ms`, `bundled_wait_ms` and one `stage_bundled_<package>_ms`
per install on the timing line.

**Reason and benefit**

The staging phase shortens by the two shorter installs. Measured on this
PR's first run (below): the three installs sum to 25.9s and take 16.4s
of wall time together, so the overlap removes about 9.5s from the phase,
and the timing line now shows that packing (35.8s) and the
standalone-package build before the loop (about 27s) are the larger
remaining costs. The original estimate of 30-50s was too high because it
assumed the installs were about half of the phase; they are a quarter.

**Breaking changes**

None. The packed tarballs are produced by the same script, in the same
order, and are checked the same way.

## What Changed

- `scripts/stage-bundled-packages.mjs` (new): `startBundledInstalls`
starts one child per bundled package through the prefetch helper from
#15849, with the child's output in a log file. `bundledInstallTimings`
reads each child's wall time for the timing line. `bundledPackageSlug`
maps a package name to its log and timing key.
- `scripts/verify-grok-npm-install.mjs`: the staging loop is split. The
bundled packages' sources are staged first and their installs start
together. The other packages are copied while the installs run. The
install handles are pushed into the `prefetches` list at once, so an
earlier failure stops any install still running before the scratch root
is removed. The join comes before the first `npm pack`. The pack loop
walks every package in `needed` order and checks each tarball as before.
`prepareBundledPackage` is no longer imported.
- Timing line: `stage_sources_ms`, `stage_bundled_ms`, `stage_pack_ms`,
`bundled_wait_ms` and `stage_bundled_server_ms`,
`stage_bundled_adapter_utils_ms`, `stage_bundled_db_ms` are added.
`stage_packages_ms` and the download keys are unchanged, so the before
and after numbers compare directly.
- `scripts/__tests__/stage-bundled-packages.test.mjs` (new): five tests
with local Node children and no network. The slug mapping; the children
run the CLI entry `release.sh` runs and never an in-process call; two
installs run at the same time, each with its own source and target, and
their logs and timing keys are correct (each child exits only after the
other has started, so serial children would fail); a failed install
rejects with its own log tail while the other is still running and is
then stopped; and stopping the installs after one fails also stops the
stand-in npm process the other wrapper is blocked on.
- `scripts/__tests__/grok-public-install-sandbox.test.mjs`: one guard
test on the verifier source. The bundled sources are staged before the
installs start, the installs are registered for cleanup before the other
packages are copied, the join comes before the pack loop, the pack loop
is in order, there is still exactly one package pack loop, and the
timing keys are reported.
- `package.json`: the new test file is in `test:release-registry`.

### Review fix (second commit): stop a prefetch's whole process tree

Greptile pointed out that `stopPrefetches` signalled only the Node
wrapper of each install, while the wrapper is blocked in
`execFileSync('npm', ['install', ...])`. After one install failed, the
other wrapper died and its npm process kept writing into the scratch
root the verifier was about to remove.

- `scripts/prefetch-child.mjs`: on POSIX every prefetch child is started
`detached`, so it leads its own process group. `stopPrefetches` signals
the group (`process.kill(-pid, ...)`) and waits until no member of the
group exists, with `SIGKILL` after the grace period and a second grace
period before it gives up so cleanup cannot hang. On Windows the child
is signalled directly as before.
- `scripts/__tests__/prefetch-child.test.mjs`: two tests. A stopped
prefetch's grandchild is gone after `stopPrefetches` returns, and a
`SIGINT` to a separate parent process reaches the grandchild while the
parent still exits with `SIGINT`. Both are skipped on Windows.
- `scripts/__tests__/stage-bundled-packages.test.mjs`: one test, the
cancellation case Greptile asked for. The stand-in
`prepare-bundled-package` blocks in `execFileSync` on a stand-in npm
that announces its pid; after the other install fails, `stopPrefetches`
must leave that pid gone.

All three new tests fail against the previous helper (`grandchild <pid>
outlived stopPrefetches`, `outlived the parent's SIGINT`, `stand-in npm
<pid> outlived stopPrefetches`) and pass with the fix.

### Review fix (third commit): the parent runs no signal handler

Greptile pointed out that the second commit forwarded the terminal's
signals to the detached groups through a JavaScript handler in the
parent. The verifier spends most of its time blocked in `execFileSync`
(the standalone builds, every `npm pack`), where no handler can run, and
installing the handler also replaced the parent's immediate default
termination. So a Ctrl-C during a synchronous phase did nothing until
that command returned, and the detached installs and downloads kept
running meanwhile. Confirmed with the new test against the second
commit's helper: the parent survived the `SIGINT`, exited with code 1
once the synchronous command had died, and its handler never ran.

- `scripts/prefetch-supervisor.mjs` (new): every prefetch command now
runs under this small Node script as the leader of its own process
group. The supervisor holds a pipe from the parent on stdin (which the
parent writes to only to request a stop where it cannot signal the
group; see the fourth commit). The kernel closes it when the parent
exits for any reason, including a signal delivered while the parent is
blocked, or `SIGKILL`, and the supervisor then stops its group
(`SIGTERM`, `SIGKILL` after the grace period) and says so in the log. It
passes group-wide signals on to the command and stays alive until the
command exits, so its own exit reports the command's exit code or
signal. Run by hand with a terminal or `/dev/null` on stdin it watches
nothing.
- `scripts/prefetch-child.mjs`: `startPrefetch` spawns the supervisor
with the command, with stdin as the pipe. The forwarding handlers are
gone; the parent installs no signal handler, so its default termination
stays immediate. `stopPrefetches` is unchanged.
- `scripts/__tests__/prefetch-child.test.mjs`: the first test asserts
the parent has no `SIGINT`/`SIGTERM`/`SIGHUP` listener after a prefetch
starts. The "signal to the parent" test now runs for `SIGINT` and
`SIGKILL` and checks the supervisor's log line. One new test gives a
separate parent its own process group, blocks it in `execFileSync` on a
20s command, and sends `SIGINT` to that group the way a terminal sends
Ctrl-C: the parent must die of `SIGINT` within two seconds and the
prefetch's grandchild must be gone. Against the previous helper the
parent exits with code 1 instead, the grandchild outlives `SIGKILL`, and
the handler-count assertion fails.

### Review fix (fourth commit): a deliberate stop on Windows goes
through the pipe

Greptile pointed out that on Windows, where `startPrefetch` now returns
the supervisor, `stopPrefetches` called `child.kill('SIGTERM')` on it.
Windows has no process groups and `kill` there ends a process outright,
so the supervisor died without running its handler and its command kept
running after cleanup returned.

- `scripts/prefetch-child.mjs`: without process groups, the graceful
stop no longer signals the supervisor. `stopPrefetches` writes a stop
request to the pipe the supervisor already watches for the parent's exit
(`stdin.end('stop\n')`). Only the `SIGKILL` escalation targets the
supervisor itself, after it has had its grace period. POSIX keeps the
group signal, so `stopPrefetches` and the existing stop and failure
tests are unchanged there.
- `scripts/prefetch-supervisor.mjs`: data on stdin is a stop request and
EOF is the parent's exit; both end the group the same way (`SIGTERM`,
`SIGKILL` after the grace period) and the log line names which one it
was.
- `scripts/__tests__/prefetch-child.test.mjs`: one new test writes the
stop request to a running prefetch's pipe instead of calling
`stopPrefetches`. The supervisor must exit with `SIGTERM`, the command's
grandchild must be gone, and the log must say `stop requested` and not
`parent exited`. The previous supervisor fails it on the log line, since
it treated the request as the parent's exit. The Windows kill itself
cannot be reproduced on the Linux runners, so the Windows branch of
`signalTree` is verified by that supervisor test plus reading its two
lines. The stand-in that ignores `SIGTERM` is now skipped on Windows,
where `kill` cannot be ignored.

## Verification

- `node --test scripts/__tests__/stage-bundled-packages.test.mjs
scripts/__tests__/grok-public-install-sandbox.test.mjs
scripts/__tests__/prefetch-child.test.mjs`: 30 tests pass (was 19 before
this PR, 24 after the first commit, 27 after the second, 29 after the
third). The three files pass three consecutive runs.
- `node --check` passes on all four scripts.
- The verifier itself needs Docker and a network, which this workspace
does not have. This PR's own `Build` job runs the branch's verifier.
Measured on all four commits' runs
([38132868803](https://github.com/paperclipai/paperclip/actions/runs/38132868803):
`Build` 428s, `pnpm build` 112s, verifier step 214s;
[38136912842](https://github.com/paperclipai/paperclip/actions/runs/38136912842):
`Build` 447s;
[38139871529](https://github.com/paperclipai/paperclip/actions/runs/38139871529):
`Build` 432s;
[38142762538](https://github.com/paperclipai/paperclip/actions/runs/38142762538):
`Build` 457s, `pnpm build` 123s, verifier step 231s):

| Key | Run 1 | Run 2 | Run 3 | Run 4 | Before |
| --- | --- | --- | --- | --- | --- |
| `stage_packages_ms` | 80.4s | 84.9s | 81.5s | 89.6s | 102-116s on
master runs 38112764439, 38111191543, 38110932348, 38110914319,
38110897745, 38127611057; 84.5s on #15849's run on a runner as fast as
these |
| `stage_sources_ms` | 1.4s | 0.7s | 0.9s | 0.9s | (inside the number
above) |
| `stage_bundled_server_ms` / `adapter_utils` / `db` | 16.3s / 5.0s /
4.6s | 14.9s / 3.6s / 3.3s | 16.4s / 5.2s / 4.7s | 17.1s / 4.4s / 3.8s |
ran one after another, 21.8-25.9s together |
| `stage_bundled_ms` (wall, all three) | 16.4s | 15.0s | 16.5s | 17.2s |
21.8-25.9s |
| `bundled_wait_ms` | 15.3s | 14.7s | 16.1s | 16.7s | — |
| `stage_pack_ms` | 35.8s | 37.1s | 35.6s | 37.9s | (inside the number
above) |
| `consumer_install_ms` | 94.4s | 97.8s | 95.7s | 99.8s | 97-134s |
| `image_prefetch_ms` / `image_wait_ms` | 33.7s / 0ms | 31.8s / 0ms |
34.7s / 0ms | 33.7s / 0ms | unchanged |
| `grok_prefetch_ms` / `grok_wait_ms` | 2.1s / 0ms | 2.1s / 0ms | 2.0s /
0ms | 2.1s / 0ms | unchanged |

The overlap removed about 7-10s from the staging phase on each of the
four runs (21.8-25.9s of installs in 15.0-17.2s of wall time). The third
and fourth commits changed no timing: both waits stay at 0ms and the
staging phase sits inside the band of the first two runs. The rest of
the phase is the standalone-package build and the server UI dist prep
before the loop (about 27-32s) and the eighteen serial `npm pack` plus
`tar -tzf` checks (36-37s).

- `docker-runner-check.yml` runs the same script after `pnpm build` and
needs no change.

## Risks

- Three `npm install` processes share the host npm cache at the same
time. npm's cache (`cacache`) is designed for concurrent writers, and
the three installs have disjoint target directories. If a shared-cache
race appears, the failing install's log tail is in the error and the fix
is to serialize again. The first CI run showed none.
- The install output moves from the CI log into per-install log files in
the scratch root. A failure reports the last 2000 characters of the
failing install's log; a successful install's output is discarded with
the scratch root.
- Memory: three concurrent installs on the `Build` runner instead of
one. The closures are small (the server's eight bundled packages are the
largest), so this stays well under the runner's memory.
- Process groups: a detached child no longer receives the terminal's
signals on its own. The supervisor stops its group when the parent is
gone, which it learns from the kernel closing the stdin pipe, so this
holds for a Ctrl-C while the parent is blocked in synchronous work and
for `SIGKILL` alike. The parent keeps Node's default signal handling. If
the supervisor itself is killed with `SIGKILL` before its command, the
command is orphaned and finishes on its own (each install ends within
seconds; the image pull within a minute), the same as any orphaned
grandchild before this PR.
- One extra Node process per prefetch (five per verifier run). Each
costs about 40ms to start, inside the time the parent spends staging
anyway.
- Low risk otherwise. Packing, the tarball checks, the consumer install,
and every probe are unchanged.

> For core feature work, check [`ROADMAP.md`](ROADMAP.md) first and
discuss it in `#dev` before opening the PR. Feature PRs that overlap
with planned core work may need to be redirected — check the roadmap
first. See `CONTRIBUTING.md`.

## Model Used

- Claude Fable 5.1 (Anthropic), model ID `claude-fable-5-1`, run as a
Paperclip agent through the Claude Code local adapter with tool use
(shell, file edits, GitHub CLI). Reasoning mode: extended thinking.

## 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 on all four commits
- [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
(on the fourth commit Greptile reviewed 8 files and added no comments;
all three earlier threads are resolved)
- [x] I will address all Greptile and reviewer comments before
requesting merge

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

---------

Co-authored-by: Bender (Fable) <bender-fable@users.noreply.github.com>
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
Co-authored-by: devinfoley <139239+devinfoley@users.noreply.github.com>
2026-10-11 11:19:44 -07:00
2026-03-07 02:57:28 +09:00

Paperclip is the app people use to manage AI agents for work.

Quickstart · Docs · GitHub · Discord · Twitter · Website

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Star History Rank


Sign up for the Paperclip Cloud waitlist →


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 and experimental pipelines 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, 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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