finn-spec

finn-spec is a skill for Claude Code, Codex from finna/Finn-loop. It costs 56 tokens per session (752 once invoked), scanned A, original, MIT.

An interactive interview process that turns a rough feature idea into a detailed issue in Linear, a tool for planning and tracking software work.

In plain words
What is it for?
Use it to research the relevant code, ask product questions, and file a build-ready Linear issue with clear scope and acceptance details.
Why use it?
It fills in missing requirements and codebase context before development starts, reducing guesswork for the person who will build the feature.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/finna/finn-loop/finn-spec
Any agent
npx skills add finna/Finn-loop --skill finn-spec
Clone the repo
git clone --depth 1 https://github.com/finna/Finn-loop

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for finn-spec

README.md
[![agentmods](https://agentmods.dev/badge/skills/finna/finn-loop/finn-spec.svg)](https://agentmods.dev/skills/finna/finn-loop/finn-spec)
Your own site
<a href="https://agentmods.dev/skills/finna/finn-loop/finn-spec"><img src="https://agentmods.dev/badge/skills/finna/finn-loop/finn-spec.svg" alt="Measured on agentmods" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 752 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00056 $0.00752
Opus 5 $0.00028 $0.00376
Sonnet 5 $0.00011 $0.00150
Haiku 4.5 $0.00006 $0.00075

Measured 6d ago against content hash 47ce8b36d9d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

finn-spec scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/finn-spec/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 97 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 97 lines · 56 tokens per session scan A 47ce8b36d9d4

Subscribe to this mod's changes

finn-spec is a skill published in the GitHub repository finna/Finn-loop (305 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 752 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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