Paperclip is a Node.js server and React application for coordinating AI agents as a business team, with goals, organizational roles, budgets, governance, and work tracking in one interface. It is used by people managing multiple agents or autonomous agent organizations across tools such as OpenClaw, Claude Code, Codex, and Cursor. The catalogue includes skills, agents, an MCP add-on, and an instruction for working with Paperclip.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add paperclipai/paperclip --skill github-pr-workflowgit clone --depth 1 https://github.com/paperclipai/paperclipWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/paperclipai/paperclip/github-pr-workflow)<a href="https://agentmods.dev/skills/paperclipai/paperclip/github-pr-workflow"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/github-pr-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/paperclipai/paperclip/github-pr-workflow"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/github-pr-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.00871 |
| Opus 5.5 | $0.00016 | $0.00348 |
| Sonnet 5.5 | $0.00008 | $0.00174 |
| Haiku 4.5 | $0.00004 | $0.00087 |
Grade A, and why
github-pr-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Pull Request Workflow
Ship a PR a reviewer can land without follow-up clarifying questions. The aim is high signal in the title and body, evidence the change works, and clean replies when feedback comes in.
When to use
- You are about to open a PR for a change that is functionally complete.
- A reviewer left comments and you need to respond and push fixes.
- A PR has been open more than a day and needs to be brought back into shape (stale conflicts, missing description, missing verification).
When not to use
- The change is not yet functionally complete. Finish the work first; draft PRs that bounce on review are noise.
- The repository uses a non-GitHub forge. Adjust to that forge's conventions; do not force GitHub-isms.
Branch hygiene before opening
- Rebase or merge from the target base so the diff is current.
- Squash WIP commits into reviewable units. Prefer one commit per logical change; do not force one-commit-per-PR if the work is genuinely multi-step.
- Confirm tests, typecheck, and lint pass locally. Note any deliberate skips in the PR body.
- Remove debug prints, commented-out code, and
TODOmarkers that are not tracked.
PR title
- Imperative mood, under 70 characters.
- Lead with the user-visible change, not the file touched.
Allow CSV export from reports tablebeatsUpdate reports.tsx. - If the repo uses an issue prefix convention (
PAP-1234:,[security]), follow it. - No trailing period.
PR body
Use this structure:
## Summary
- 1–3 bullets describing what changed and why.
## Implementation notes
- Anything non-obvious in the diff: trade-offs, dropped alternatives, gotchas.
- Migration or config implications.
## Verification
- The exact commands or steps you ran.
- Screenshots or short clips for UI changes (required if pixels moved).
- Edge cases you exercised by hand.
## Risk and rollback
- What breaks if this is reverted, and how to revert cleanly.
Skip the Risk and rollback section only for clearly trivial PRs (typos, docs).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 94 lines · 39 tokens per session scan A f498ec4ebb17
github-pr-workflow is a skill published in the GitHub repository paperclipai/paperclip (103,753 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 871 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
github-automation
GitHub workflow automation, PR management, issue tracking, and code review coordination. Integrates with GitHub Actions and repository management. Use when: PR creation, code review, issue management, release automation, workflow setup. Skip when: local-only changes, non-GitHub repositories.
merge-queue
Process the Refinery merge queue - collect agent work, detect and resolve conflicts, merge in dependency order, and verify integration.
github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management.
cc-autopilot
Run cc-autopilot, a perpetual autonomous AUDIT/GENERATE→TRIAGE→BATCH→FIX→VERIFY→REVIEW→COMMIT loop that holds every change to a configured quality bar through a judge panel. Its fixers each own a file-disjoint slice of the tree so no two can ever touch the same file, and nothing unverified reaches git. Works on a web…
agentic-jujutsu
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination.
agent-swarm-pr
Agent skill for swarm-pr - invoke with $agent-swarm-pr.