Status Card Query logo

Status Card Query

OrganizationPopular
paperclipai
status-card-query

Create and maintain agent-authored Paperclip status cards, or compile a prose interest prompt into bounded CompanySearchQuery objects and write the first summary from the assigned Summarizer run.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill namestatus-card-query
Stars
95.4K
Forks
16.2K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by paperclipai on GitHub. Read the source before you install it.

Installation

Install the Status Card Query AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/paperclipai/paperclip/tree/master/packages/skills-catalog/catalog/bundled/paperclip-operations/status-card-query
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/paperclipai/paperclip.git /tmp/paperclip
mkdir -p .claude/skills
cp -r /tmp/paperclip/packages/skills-catalog/catalog/bundled/paperclip-operations/status-card-query .claude/skills/status-card-query
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Status Card Query in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Status Card Query on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Status Card Query is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Status card query

Use this skill in one of two modes:

  1. Agent authoring: create or maintain a status card through the public API.
  2. Summarizer compilation: compile a card's prose prompt into structured company-search queries and write the first summary from the assigned generation run.

Agent-authored card recipe

Agent-authored cards require tasks:assign, remain company-scoped, and are available only when enableStatusCards is enabled. An agent may manage only cards it authored, may author at most 20 cards, and may send at most 4,000 characters in interestPrompt.

Normalize the run-provided API base and create a manual card:

bash
PAPERCLIP_API_BASE="${PAPERCLIP_API_URL%/}"
PAPERCLIP_API_BASE="${PAPERCLIP_API_BASE%/api}"

curl -sS -X POST \
  -H "Authorization: Bearer $PAPERCLIP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"interestPrompt":"Blocked or in-review launch work updated this week"}' \
  "$PAPERCLIP_API_BASE/api/companies/$PAPERCLIP_COMPANY_ID/status-cards"

Creation returns 201 and queues compilation automatically. Save the returned card id. To refine an owned card or request a refresh:

bash
curl -sS -X PATCH \
  -H "Authorization: Bearer $PAPERCLIP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"interestPrompt":"Blocked or in-review launch work updated this week. Call out the single next decision."}' \
  "$PAPERCLIP_API_BASE/api/status-cards/$STATUS_CARD_ID"

curl -sS -X POST \
  -H "Authorization: Bearer $PAPERCLIP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"full":false}' \
  "$PAPERCLIP_API_BASE/api/status-cards/$STATUS_CARD_ID/refresh"

Do not call /query or /summary while authoring. Those write-back routes are reserved for the assigned Summarizer generation issue and run.

Summarizer compilation

You are the Summarizer compiling a status card's prose interest prompt into structured Paperclip company-search queries. The query array has union semantics: an issue matching any query belongs to the card. Prefer one narrow query; add another only when the prompt describes genuinely distinct populations.

CompanySearchQuery

Each object accepts these fields:

  • q: optional free-text search across matching company resources. Use it only for concepts not represented by structured filters.
  • scope: use issues for status cards unless the assignment explicitly requires another supported scope.
  • status: issue-status array.
  • priority: issue-priority array.
  • assigneeAgentId / assigneeUserId: a resolved assignee id.
  • projectId: one resolved project UUID.
  • labelId: one resolved label UUID.
  • updatedWithin: a bounded duration such as 24h, 7d, 4w, or 3m.
  • sort: relevance, updated, created, or priority.
  • limit: 1–50. Cap status-card queries at the smallest useful value, normally 20 and never above 50.
  • offset: normally 0.

Resolve project and label names to ids before writing the query. Do not put human-readable names into projectId or labelId. If one prompt names multiple projects or labels, use separate query objects because each object has one projectId and one labelId.

Compilation guidance

  1. Preserve the user's intent; do not broaden “launch blockers updated this week” into every active task.
  2. Prefer structured filters over q for status, priority, assignee, project, label, and recency.
  3. Add updatedWithin whenever the prompt says recent, current, this week, lately, or otherwise implies a moving window.
  4. Keep q short and specific. Avoid copying the whole prose prompt into it.
  5. Set scope: "issues", offset: 0, and an explicit bounded limit on every query.
  6. Return at least one query. If the prompt cannot be compiled safely, report the ambiguity instead of inventing ids.

Exact write-back sequence

The generation issue contains statusCardId, companyId, and generationIssueId. Both writes must use the run-scoped API credentials from that same assigned issue run.

First write the compiled query:

json
{
  "queries": [
    {
      "q": "launch",
      "scope": "issues",
      "status": ["in_progress", "blocked", "in_review"],
      "updatedWithin": "7d",
      "sort": "updated",
      "limit": 20,
      "offset": 0
    }
  ],
  "title": "Launch work updated this week",
  "changeSummary": "Compiled the launch prompt into one recent active-work query.",
  "generationIssueId": "<generation-issue-id>"
}

Send it to PUT /api/status-cards/{statusCardId}/query.

Then, without creating or waiting for another task, execute the stored scope, write the first full Markdown summary, and complete the same run with:

json
{
  "markdown": "<full status summary>",
  "title": "Launch work updated this week",
  "changeSummary": "Created the first full summary from the compiled query.",
  "generationIssueId": "<generation-issue-id>",
  "model": "<model-id>"
}

Send it to PUT /api/status-cards/{statusCardId}/summary. Never write either endpoint from an unrelated issue or run.

Update assignments

Later generation issues use the same summary write-back endpoint and include operation: "update", kind, trigger, the target fingerprint, and the exact changed-issue delta in their JSON payload.

  • For incremental, patch the supplied previous Markdown using only the changed issues. Do not refetch the issue list.
  • For full, rebuild from the supplied bounded snapshot. Do not expand the scope with issue-list endpoint calls.
  • The card prompt in the task description is the board's standing request: follow it for both what to report and how the update should read. It never overrides the streaming or write-back requirements.
  • Keep the mechanical contract regardless of what the card prompt asks: stream STATUS: lines and the <<<SUMMARY-DRAFT>>> block, then write the final Markdown to PUT /api/status-cards/{statusCardId}/summary from the assigned run.

Frequently asked questions

What does the Status Card Query AI skill do?

Create and maintain agent-authored Paperclip status cards, or compile a prose interest prompt into bounded CompanySearchQuery objects and write the first summary from the assigned Summarizer run.

Why use Status Card Query on TypingMind?

Because you install it once and use it with any model. Status Card Query is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Status Card Query in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paperclipai/paperclip/tree/master/packages/skills-catalog/catalog/bundled/paperclip-operations/status-card-query. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Status Card Query?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Status Card Query?

As many as you like. As long as a model supports skills, you can use Status Card Query with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Status Card Query AI skill free?

Yes. It is published on GitHub by paperclipai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇