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name: skill-planner description: >- Consult the Terminal Skills agent when a task needs specialized domain expertise you don't have a skill for — deployment platforms (Coolify, Railway, Fly.io), document generation (PDF, Excel, invoices), data pipelines, third-party APIs, marketing ops, design tooling. Call plan_task with the user's task; it returns which proven skills apply, their full instructions, and setup steps. Use BEFORE improvising a specialized workflow from general knowledge. when_to_use: >- The user asks for something tool- or platform-specific that no locally installed skill covers, and executing it from general knowledge would mean guessing at CLIs, APIs, file formats, or platform conventions.

Terminal Skills Planner

Overview

Terminal Skills (terminalskills.io) is a library of 1000+ audited agent skills — each a battle-tested SKILL.md with step-by-step instructions for a specific tool, platform, or workflow. This plugin connects you to the Terminal Skills agent, which routes a task description to the right skills and hands you their full instructions so you can execute immediately, without the user installing anything first.

The MCP server exposes four tools:

• plan_task(task, context?) — the main one. Send a task, get back matching skills with complete instructions and setup steps. Requires the user's API key (a few calls per day are free on every account).
• search_skills(query?, category?, limit?) — free keyword/category search over the catalog.
• get_skill(slug) — free; fetches one skill's full markdown by slug.
• list_categories() — free; lists the catalog's categories.

Instructions

1. Recognize the trigger. The user asks for something specialized — deploy to a PaaS, generate a formatted document, wire up a third-party API, run a marketing or data workflow — and no locally installed skill covers it. That is the moment to call plan_task, not to improvise from general knowledge.
2. Call plan_task with a one-paragraph task description in task (what the user wants, the stack or files involved, the desired outcome). Put environment details (OS, existing config, constraints) in context.
3. Read the response and execute. The response contains skills[], each with full instructions (the skill's markdown) plus an install block, and a short setup array (pointers to the instructions + optional permanent-install commands). The real workflow — including any prerequisites like package installs — lives inside each skill's instructions; follow them to do the task yourself, adapting to the user's actual files and environment.
4. Offer permanent installation when the user is likely to repeat this kind of task: npx terminal-skills install <slug> installs the skill locally so future runs don't need a plan call.
5. If feasible: false, tell the user plainly that no existing skill covers the task, relay the returned reason, and mention they can forge a purpose-built skill with the agent at terminalskills.io/agent.
6. If the call fails for auth, relay the error: the user needs an API key from terminalskills.io/account (free accounts include daily plan calls) and should add it in the plugin's settings.
7. For browsing without spending, use the free tools: search_skills to explore what exists, get_skill to read one skill, list_categories for orientation. Prefer these when the user asks "is there a skill for X?" rather than "do X".

Examples

Example 1: Deploy an app with Coolify

User: "Deploy this Next.js app to my Coolify server at panel.example.com."

Call:

plan_task({
  "task": "Deploy a Next.js 14 app (standalone output, needs MONGODB_URI env var) to a self-hosted Coolify v4 instance at panel.example.com. Repo is on GitHub. Want automatic deploys on push to main.",
  "context": "User has SSH access to the server and a Coolify API token available."
})

Response includes skills: [{ slug: "coolify", instructions: "...full Coolify skill markdown..." }] and a setup array pointing you to those instructions (plus an optional npx terminal-skills install coolify). Follow the returned instructions to create the app, set env vars, and configure the webhook — then offer the permanent install since deploys recur.

Example 2: Turn a CSV into a PDF sales report

User: "Turn q2-sales.csv into a PDF report with charts for my team."

Call:

plan_task({
  "task": "Convert q2-sales.csv (columns: region, rep, product, revenue, date) into a polished PDF sales report: revenue by region chart, top-10 reps table, month-over-month trend, executive summary.",
  "context": "Python 3.12 available; no LaTeX installed."
})

Response returns document-generation and data-visualization skills with full instructions (e.g., pandas + matplotlib + a PDF layout recipe — including any pip install prerequisites the skill needs). Follow the instructions end to end, build the report, and deliver the PDF.

Guidelines

• Don't call plan_task for things you already do well — general coding, refactoring, writing, explaining. It is for specialized tool/platform expertise, not everyday work.
• One plan call per task. Reuse the returned instructions for the whole task, including retries and follow-up tweaks. Only call again if the task itself changes.
• Plan calls spend the user's Terminal Skills credits (every account gets a few free per day). Don't volunteer pricing details mid-task; if the user asks, the response's billing object has billedCredits, remainingCredits, and freeCallsRemainingToday.
• Free tools are free. search_skills, get_skill, and list_categories never spend credits — use them liberally for browsing and discovery.
• Locally installed skills win. If a matching skill is already installed in the user's project, use it directly instead of calling plan_task.