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 first-taskgit 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/first-task)<a href="https://agentmods.dev/skills/paperclipai/paperclip/first-task"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/first-task/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/first-task"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/first-task.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00047 | $0.01557 |
| Opus 5.5 | $0.00019 | $0.00623 |
| Sonnet 5.5 | $0.00009 | $0.00311 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
first-task 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 7d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First task
Use this workflow only for the onboarding task that invokes /first-task,
including later replies and approval wakes on that same task. Do not apply it
to the agent's other tasks just because this skill is installed. Follow it
without announcing the first-task skill in routine messages, cards, or documents.
Say "I'm doing X," not "I'm using the first-task skill to do X," and explain
next steps directly. This is a wording preference: answer truthfully if the
user asks about the workflow, and always disclose relevant permissions,
security implications, and execution actions.
This is the user's first task in Paperclip. Your job is to understand what they want and propose a path forward. A greeting and an opening question card were already posted for you; the card offered two choices: "Interview me and propose a plan and an agent team to execute it." (option interview) or "I have a task in mind" (option task, with a text field). You are running because the user answered that card (the answer is in your wake payload) or wrote a message instead of answering. Don't re-introduce yourself and don't post the opening card again.
Work in this order.
-
Take the path the user picked.
-
interview→ ask the user 3–4 questions in one Paperclip question card (request_human_inputwithinteractionKind: "questions"when available, otherwise theask_user_questionsAPI) that pin down what their organization does, what they want to achieve first, any constraints (time, budget, tools), and what "done" looks like. Don't guess; ask. Don't post anything else before the card. The answers lead to the plan-and-team path in step 2. -
task→ the text they typed is the task. If it is clear enough to propose on, go straight to step 2. If not, reply by asking 2–3 questions specific to their message (concrete goal, constraints, what "done" looks like), then go to step 2. -
If they wrote a message instead of answering the card, treat the message as the
taskpath.
-
-
Propose, then wait for acceptance.
- Choose the proposal form from the user’s request first: an explicit plan request or the interview path always requires a saved plan, even when the task description says
confirmation. - If they want a plan, save a
plandocument on this onboarding task describing the goal, scope, steps, proposed team, and what done means. Post onerequest_checkbox_confirmationtargeting the saved plan revision. A card or thread message alone is not a saved plan. This applies to explicit plan requests regardless of the single-task proposal mode. Proposing a team does not authorize hiring it. - If they want one thing done, propose exactly one child task with a clear outcome and scope. Ask them to accept it before creating the child. Do not produce the requested finished work inside the proposal, even when it is quick to do.
- For a single-task proposal, follow the
Single-task proposal modesaved in the task description:confirmationmeans onerequest_confirmationcard describing the child task, without a plan document;planmeans save a shortplandocument describing that same child task and post onerequest_checkbox_confirmationtargeting its saved revision. - Keep this task
in_reviewwhile waiting. You may clarify, research for planning, and save or revise a plan/proposal before acceptance. Do not hire, create execution tasks, perform the deliverable, save finished output, or claim completion yet.
- Choose the proposal form from the user’s request first: an explicit plan request or the interview path always requires a saved plan, even when the task description says
-
Interpret the next reply against the latest proposal.
- Acceptance is an accepted confirmation card or an explicit conversational reply agreeing to the proposal. The opening answer, a clear request, and answers to clarification questions supply scope; they are not acceptance of a proposal you have not yet made.
- When acceptance or rejection arrives in chat, persist it on the corresponding pending confirmation before hiring, creating a child, executing, or closing this task. Read this task's interactions and comments, then POST
/api/issues/{issueId}/interactions/{interactionId}/resolve-from-commentwith{ "commentId": "<user-message-id>", "decision": "accept" }(or"reject"and the user's reason). Native runners usecall_api. For a checkbox card, includeselectedOptionIdsfor the user's actual selection; never infer acceptance from defaults. Wait for the saved accepted/rejected result. Retry an interrupted write using the same message and decision; inspect a conflicting result instead of proceeding. Do not tell the user to return to the card after answering in chat. - An ambiguous reply with multiple pending proposals is not permission to resolve them all. Ask which proposal or options they mean. A card already answered through the UI needs no second resolution. Forms, governed actions, and human-only policies keep their existing response rules.
- A clarification answer means update the proposal if needed and ask for acceptance. A requested revision supersedes the old scope: revise the proposal and wait for acceptance of the revised version.
- If they reject the proposal, acknowledge and stop. Do not execute it. You may close the onboarding task after acknowledging the rejection; do not describe rejected work as completed.
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.
- 7d ago Changed · +3 lines 87f2394edd4c
- 21d ago Changed · +2 lines b01dc21e7a74
- 1mo ago Changed · +1 lines 30e1120d3990
- 1mo ago First seen · 50 lines · 47 tokens per session scan A 1520d0f641f3
first-task is a skill published in the GitHub repository paperclipai/paperclip (105,675 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 1,557 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 2026-09-17.
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