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/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
2953 skills
Install
$ npx -y skills add finna/Finn-loop --skill finn-spec --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/finn-spec

Context preview

The summary Claude sees to decide when to auto-load this skill.

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.

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
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

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Maintenance
JavaScript
Language
MIT
License
18d ago
Last commit
18d ago
Created

Repo: finna/Finn-loop