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Agent skill

Finn Spec

by finna in finna/Finn-loop

Interview the user about a raw idea until confident, then file a build-ready issue in Linear.

MITAuto-check passed

Install Finn Spec

skills CLI
$ npx skills add finna/Finn-loop --skill finn-spec -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install finna/Finn-loop finn-spec --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/finna/Finn-loop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/finn-spec .claude/skills/finn-spec && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
finn-spec
GitHub stars
319
Token cost
~824 tokens
SKILL.md length
390 words
Files
1
Skills in repo
3
Repo updated
First seen
Licence
MIT

At a glance

Interview the user about a raw idea until confident, then file a build-ready issue in Linear.

  • Works in 4 steps: Research before asking → Interview in rounds → Draft the issue → …
  • Asked to run Finn-loops spec interview
  • SKILL.md covers 1. Research before asking, 2. Interview in rounds, 3. Draft the issue and 4. Confirm and file, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Finn Spec is an agent skill from finna/Finn-loop. 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.

Its SKILL.md is about 820 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with GitHub. The repository describes itself as: The Finn-loop: a 3-skill AI software factory for Claude Code — spec, build, review. Humans merge. The licence is MIT.

When your agent uses it

  • Asked to run Finn-loops spec interview
  • Draft a queue-ready issue

Example prompts

  • “/finn-spec”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Research before asking
  2. Interview in rounds
  3. Draft the issue
  4. Confirm and file

What it can do on your machine

Read from SKILL.md and the folder at commit 7941b62. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Finn Spec loads about 824 tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 390 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~824

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from finna/Finn-loop at commit 7941b62, republished under its MIT licence (© finna). 390 words, ~824 tokens.

Download SKILL.mdSave it as .claude/skills/finn-spec/SKILL.md (or your agent's skills folder).
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.

Show full SKILL.md (176 more words)Show less

3. Draft the issue

Use exactly this shape:

md
## 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".

© finna, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/finn-spec of finna/Finn-loop.

Open the folder on GitHubat commit 7941b62

Compare with similar skills

Finn Spec next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Finn Spec compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Finn Spec this skillfinna/Finn-loop319—~824Automated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Diagnosing Superpowers Sessionsobra/superpowers297k3 repos~1.7kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Update V8 Versionopeninterpreter/openinterpreter69k2 repos~845Automated safety check: PassApache-2.0

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More from finna/Finn-loop

  • Finn Build

    finna/Finn-loop

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Works with

Questions about Finn Spec

What does Finn Spec do?

Interview the user about a raw idea until confident, then file a build-ready issue in Linear. Finn Spec is an agent skill from finna/Finn-loop. Interview the user about a raw idea until confident, then file a build-ready issue in Linear.

When should I use Finn Spec?

Finn Spec fits situations like: asked to run Finn-loops spec interview; draft a queue-ready issue.

How do I install Finn Spec in Claude Code?

Run `npx skills add finna/Finn-loop --skill finn-spec -a claude-code`. Or copy the skill folder (skills/finn-spec in finna/Finn-loop) into .claude/skills/finn-spec in your project. Claude Code loads it when a task matches its description.

How do I install Finn Spec in Codex?

Run `npx skills add finna/Finn-loop --skill finn-spec -a codex`. Or copy the skill folder (skills/finn-spec in finna/Finn-loop) into .agents/skills/finn-spec in your project. Codex loads it when a task matches its description.

Can I use Finn Spec in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add finna/Finn-loop --skill finn-spec -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/finn-spec, .gemini/skills/finn-spec, .github/skills/finn-spec and .opencode/skills/finn-spec in your project.

What does Finn Spec need to run?

SKILL.md names no scripts, command-line tools or credentials: Finn Spec is instructions for the agent only.

Does Finn Spec access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Finn Spec safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Finn Spec use?

Finn Spec is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Finn Spec use?

About 824 tokens (SKILL.md is roughly 3.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Finn Spec?

Skills that share tags, products or a category with Finn Spec: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 297k stars), Greploop (onyx-dot-app/onyx, 32k stars) and GitHub Deep Research (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Finn Spec?

finna (a GitHub user) maintains it in finna/Finn-loop, which has 319 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on July 23, 2026.

Source: finna/Finn-loop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.