specout

An interview workflow for finding missing information in a specification file. A specification describes what a project or feature must do.

In plain words
What is it for?
Use it with a SPEC.md file to check its problem statement, data model, requirements, rules, exclusions, acceptance checks, and risks.
Why use it?
It turns unclear or incomplete requirements into questions that can be answered before implementation begins.

Command

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 commands/alleneubank/claude-code/specout
Clone the repo
git clone --depth 1 https://github.com/alleneubank/claude-code
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 577 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 $0.00008 $0.00577
Opus 5 $0.00004 $0.00289
Sonnet 5 $0.00002 $0.00115
Haiku 4.5 $0.00001 $0.00058

Measured 2d ago against content hash d9a56f1907aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

specout 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 2d 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.

commands/specout.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Load the spec-best-practices skill before proceeding.

Spec File Selection

A spec file path is required. Check the argument provided: $ARGUMENTS

If no argument was provided (empty or blank):

  1. Search for existing SPEC.md files in the project (root, apps/, packages/, src/lib/*/)
  2. Present any found files to the user and ask which to use
  3. If none found, determine the correct colocated path for a new SPEC.md and propose it
  4. Do not proceed until a spec file is confirmed

If argument provided:

  • If the filename is not SPEC.md and is not a supporting file linked from an existing SPEC.md TOC, suggest the correct SPEC.md path instead
  • If the file doesn't exist, ask if you should create it at that path

Once the spec file is confirmed, read it using the Read tool.

Gap Analysis

Before interviewing, check the spec for required elements from spec-best-practices:

  • Problem/Solution narrative
  • Domain model (types, relationships)
  • Requirements with REQ-{DOMAIN}-{NNN} IDs
  • Invariants
  • Non-goals
  • Acceptance criteria (checklistable)
  • Risk tags (if high-risk items exist)

Note which elements are missing or incomplete. Focus the interview on filling these gaps.

Interview Process

Interview me using AskUserQuestionTool to fill gaps and clarify ambiguities. Ask about:

  • Types, schemas, and data models (what are the core domain types? what invariants do they encode?)
  • Technical implementation details and constraints
  • UI/UX decisions and user flows
  • Edge cases and error handling
  • Tradeoffs and alternatives considered
  • Integration points and dependencies
  • Security, performance, and scalability concerns
  • Non-goals and explicit scope boundaries
  • Risk classification for high-risk items (schema migrations, auth, public APIs, infra)

<question_quality> Avoid surface-level questions I've likely already considered. Dig into:

  • Second-order effects and unintended consequences
  • Assumptions that haven't been validated
  • Contradictions or tensions in the spec
  • Missing success/failure criteria
  • Operational concerns (monitoring, debugging, rollback)
  • Invariants that should be explicitly stated
  • Scope boundaries that need to be drawn as non-goals </question_quality>

Read the full file on GitHub · 64 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. 2d ago First seen · 64 lines · 8 tokens per session scan A d9a56f1907aa

Subscribe to this mod's changes

specout is a command published in the GitHub repository alleneubank/claude-code (52 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 577 once invoked, about $0.0000 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.