Skip to content
Automation
Skill

/finn-spec

Interview the user about a raw idea until confident, then file a build-ready issue in Linear. Use when asked to run Finn-loop's spec interview, draft a queue-ready issue, or plan a feature. Interactive — requires the user present; never run unattended.

From plugin
finn-loop
3213 skills

Claude Code

$ npx -y skills add finna/Finn-loop --skill finn-spec --agent claude-code

SKILL.md

finn-spec.SKILL.md
name: finn-spec
description: Interview the user about a raw idea until confident, then file a build-ready issue in Linear. Use when asked to run Finn-loop's spec interview, draft a queue-ready issue, or plan a feature. Interactive — requires the user present; never run unattended.

Spec interview

Turns a raw idea into a Linear issue so complete that a build agent needs nothing beyond the issue. Works like plan mode: research the codebase, interview the user in rounds until confident, draft, confirm, file. The user is the product brain; you are the codebase brain. Never guess product decisions.

1. Research before asking

Read the relevant code first. Find which files are involved, what patterns already exist, and what constraints apply. Never ask the user something the codebase can answer.

2. Interview in rounds

Ask 1-4 questions per round, each with concrete options and your recommended option first. Ask only genuine product decisions:

  • Behavior forks: who sees it, what exactly happens, where does it live
  • Scope boundaries: what is explicitly out of this issue
  • Edge cases that change acceptance criteria: empty states, permissions,

failure handling

  • Data implications: existing records, migrations

After each round, fold the answers in and apply the confidence test:

> Could two different engineers read this spec and ship the same observable > behavior?

If any fork remains, ask another round. There is NO cap on rounds: a small fix might need two questions; a big feature legitimately needs 10-20+. Never stop early because it feels like a lot of questions. Once the test passes, stop — no filler questions.

3. Draft the issue

Use exactly this shape:

## Problem

What user or business problem does this solve? One or two sentences.

## Acceptance Criteria

- [ ] AC-1 — Observable, testable outcome one
- [ ] AC-2 — Observable, testable outcome two

## Non-goals

- NG-1 — What must NOT change in this task
- NG-2 — What is explicitly excluded or saved for later

## Relevant files

- path/to/file.ts — why it matters

## Test expectations

- What should be tested, manually or automatically

## How to verify

1. Numbered manual steps anyone can follow to confirm the work: where to
   go, what to do, exactly what should happen. Cover every AC.

Rules for the draft:

  • Every acceptance criterion is an observable outcome with a stable `AC-N`

id. Every non-goal has a stable `NG-N` id. These ids are the contract the build and review skills enforce.

  • No acceptance criterion may require a non-goal. If one does, resolve it

with the user before filing.

  • Size the issue to one day of agent work or less. Bigger work becomes a

chain of small issues, ordered so each is buildable using only merged code from the ones before it.

4. Confirm and file

Show the full draft in chat and get the user's go-ahead. Then create the issue on the configured `TEAM` Linear team (via the Linear connector) with the draft as the body. Report the exact issue identifier and URL returned by Linear; later skills use that identifier rather than guessing it.

Hard rule

Never apply the `agent-ready` label. The user applies it in Linear after a final read — that label is the approval gate between "idea" and "an agent builds it".

Read more
@finna
Ships withfinn-loop

Three Claude Code skills that turn Linear + GitHub into a small, human-gated AI software factory: **idea → /finn-spec interviews you and files the issue → you label it agent-ready → /finn-build claims it and opens a PR → /finn-review posts a verdict → you

Stars on GitHub

Momentum

stars in total
321
Star history of finna/Finn-loop on GitHub, a chart by star-history.com

Other skills on finn-loop.

finn-build

finn-build

Claim the next safe agent-ready issue from Linear, implement it, and open a PR. Use when asked to run Finn-loop's builder, work…

@finna@finnaInstall Skill
finn-review

finn-review

Review open PRs against their linked Linear issues and required GitHub checks, then post a three-group verdict with Finn-loop…

@finna@finnaInstall Skill

More skills from other plugins.

agent-builder

agent-builder

Load immediately after an Agent intent, before the first agent_builder_* call. Governs how you create, configure, test, and…

n8n11d209k
@n8n-io@n8n-ioInstall Skill
browser-use

browser-use

Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…

@browser-use@browser-useInstall Skill
agent-browser

agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…

@vercel-labs-2@vercel-labs-2Install Skill
add-anydoc

add-anydoc

Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when…

@nanocoai@nanocoaiInstall Skill

Questions about finn-spec.

Which coding agents can use finn-spec?
finn-spec installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.