SkillsAdd

stackbone/stackbone-skills

stackbone-coder

>- Use this skill to GENERATE a new Stackbone piece from a clean idea through a guided interview: first decide what to build — a deep agent, a durable workflow, or a workflow-agent (a workflow that calls an agent) — then scaffold it with the stackbone CLI and interview the user surface by surface. For an agent you ask for its tools and its system prompt; for a workflow you ask for the input data and the output data (the inputSchema / outputSchema); then you walk the capability checklist ONE AT …

First seen Jun 26, 2026

Installation

$ npx skills add stackbone/stackbone-skills --skill stackbone-coder
View on skills.sh ↗ GitHub repository ↗

Also in this package

Other skills from stackbone/stackbone-skills.

npx skills add stackbone/stackbone-skills
stackbone-debug 81 stackbone-cli 80 stackbone 80

Browse all from stackbone/stackbone-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 1
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.2.0
LicenseMIT
More metadata
author
stackbone
version
1.2.0
organization
Stackbone
date
July 2026

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,693 B
  • docs SUMMARY.md 1,335 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 60 installs

SKILL.md

Stackbone coder — generate a piece by interview

This skill turns "I want to build X" into a scaffolded, wired-up Stackbone piece. It is an interview + scaffolding orchestrator: it picks the right shape, runs stackbone CLI to lay down the files, then asks the user exactly what each surface needs and wires in only those. It does not replace the other skills — it calls them:

  • stackbone skill → the SDK code (tools, workflow steps, the ambient stackbone client, every capability deep-dive).
  • stackbone-cli skill → the commands (init, add, dev, login, publish).
  • stackbone-debug skill → triage when a run misbehaves.

Golden rules

  • One question at a time. Never dump the whole interview at once. Ask, get the answer, move on. Use a structured question tool (e.g. AskUserQuestion) when you have one.
  • Default to the minimal piece. Only add a capability the user says yes to. A tool-only agent or a single-step workflow is a perfectly good answer.
  • Never ask for injected env. DATABASEURL, OPENROUTERAPIKEY, HMACSECRET, WORKFLOWREDISURL, etc. are platform-managed — the runtime injects them. Don't ask for connection strings or keys.
  • You orchestrate; the other skills implement. When it's time to write code, follow the stackbone skill. When it's time to run a command, follow the stackbone-cli skill.

The flow (5 steps)

1. Pick the piece type

Ask one question first — what are we building?

Type What it is Pick it when
agent A deepagents agent: model + system prompt + tools, holds a conversation. A human (or another agent) talks to it and it reasons/acts with tools.
workflow Durable, replayable code: input → steps → output, no conversation. A background job, ETL, a scheduled task, multi-step orchestration with checkpoints.
workflow-agent A durable workflow that calls a deep agent in one of its steps (callDeepAgent). You need both: deterministic orchestration and a reasoning agent in the loop.

Then detect the workspace: if the cwd already has package.json + deep-agents/ (or workflows/), you'll add to it; otherwise you'll init a new one.

2. Scaffold with the CLI

Drive stackbone (see the stackbone-cli skill for the full surface):

  • New workspace: stackbone init <name> --with <agent|workflow|workflow-agent>
  • Existing workspace: stackbone add <deep-agent|workflow|workflow-agent> <name>
  • workflow-agent and add workflow --calls <agent> wire the workflow→agent step for you.

Network: every add kind is fully offline (the pieces are members of the already-linked workspace). Only init needs a signed-in session (stackbone login) — it links the workspace to the org.

3. Type-specific interview

Open the matching reference and run its interview:

Building… Read & run
an agent [references/agent.md](references/agent.md) — its tools and its system prompt
a workflow [references/workflow.md](references/workflow.md) — its input and output data → the schemas
a workflow-agent [references/workflow-agent.md](references/workflow-agent.md) — both, plus the workflow→agent wiring

4. Capability checklist — one at a time

Open [references/capabilities.md](references/capabilities.md) and walk every capability with the user, one question each: do we need a database? storage? an LLM call? RAG? human-in-the-loop? a connector? prompts? config? secrets? a schedule? to call another agent? For each yes, the reference tells you the surface, where it's reachable from (tool vs. workflow step), what to add (a schema.ts, a line in an optional agent.yaml, a config.schema.ts…), and which stackbone-skill deep-dive to follow for the code.

5. Wire & verify

Write the code with the stackbone skill, then boot the emulator with stackbone dev (see stackbone-cli) and exercise the piece — chat the agent, start the workflow, check a run — before you call it done.

Reference files

File What it holds
[references/agent.md](references/agent.md) The agent interview: role, system prompt, the tools (name / description / inputs / behaviour), model choice.
[references/workflow.md](references/workflow.md) The workflow interview: trigger, input data, output data, the steps; how answers map to inputSchema / outputSchema and 'use step'.
[references/workflow-agent.md](references/workflow-agent.md) The combined interview + the workflow step that calls the agent via callDeepAgent.
[references/capabilities.md](references/capabilities.md) The full capability checklist — every surface, when it applies, what it adds, and the deep-dive pointer.