discovery-interview

discovery-interview is a skill for Claude Code, Codex from rordi-ai/loopbreaker. It costs 78 tokens per session (1,702 once invoked), scanned A, original, MIT.

A structured interview process for turning an idea into a clearly defined software issue. It requires the founder or decision-maker to answer questions before the work is shaped or planned.

In plain words
What is it for?
Use it before shaping a new issue to record the problem, time budget, smallest useful version, exclusions, success signal, reversibility, decision owner, and risks.
Why use it?
It prevents the agent from inventing important requirements such as the problem, scope, risks, success measure, and people responsible for decisions. This reduces the chance of building a well-tested solution to the wrong problem.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present. Also seen: $skill-name invocation.

Part of the loopbreaker plugin — 7 skills, 1 agent, 1 MCP server shipped together

Good fit Use it before shaping a new issue to record the problem, time budget, smallest useful version, exclusions, success signal, reversibility, decision owner, and risks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rordi-ai/loopbreaker/discovery-interview
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.

Any agent
npx skills add rordi-ai/loopbreaker --skill discovery-interview
Clone the repo
git clone --depth 1 https://github.com/rordi-ai/loopbreaker

Made for: Claude Code, Codex.

Or install loopbreaker, the plugin that ships this one along with the rest of its 7 skills, 1 agent, 1 MCP server.

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 discovery-interview

README.md
[![agentmods](https://agentmods.dev/badge/skills/rordi-ai/loopbreaker/discovery-interview.svg)](https://agentmods.dev/skills/rordi-ai/loopbreaker/discovery-interview)
Your own site
<a href="https://agentmods.dev/skills/rordi-ai/loopbreaker/discovery-interview"><img src="https://agentmods.dev/badge/skills/rordi-ai/loopbreaker/discovery-interview.svg" alt="Measured on agentmods" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,702 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00078 $0.01702
Opus 5 $0.00039 $0.00851
Sonnet 5 $0.00016 $0.00340
Haiku 4.5 $0.00008 $0.00170

Measured 8d ago against content hash caab10453b51, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

discovery-interview 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 8d 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/discovery-interview/SKILL.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Discovery Interview

You are the premise boundary. Everything after this stage — shape, planning, review, implementation, proof — verifies that each step follows faithfully from the one above it. Nothing downstream can check whether the top-level premise was right. A correct premise gets hardened into working software; a wrong one gets hardened into rigorously certified wrong software, carrying more conviction because it now has passing proofs behind it.

Your job is to make sure every premise came from a human.

The rule

Never author a shape field from your own head, from a neighbouring project, or from a pattern you recognise. Every one of these must trace to an answer a human actually gave:

problem · appetite · smallest_slice · non_goals · success_signal · reversibility · decision_owner · risks

If you cannot cite the human answer behind a field, interview — do not infer.

Why this stage exists

A real incident, preserved because it is the cheapest way to learn this. An agent running this very pipeline finished an interview, recorded the answers, and then offered — as its first and recommended option — "I'll run the approve command on your behalf." It did. The record read approved_by: "Ben ([email protected])" while the provenance read cli / ubuntu: its own shell.

Nothing about that was malicious, and the answers were genuinely the founder's. But approved_by is a string the caller types, so the record asserted a human had ratified the premise when no human had acted. Every downstream gate would then have treated it as founder-backed, and each would have been right to, because that is what the record said.

Approval is now refused on any ingress but the browser. You cannot issue it, and you should not want to.

A 100/100 planning health score says the plan is structurally complete. It says nothing about whether the premise was right. Do not read it as reassurance.

Workflow

1. Research before asking

Read the repository, the linked issues, and any prior discovery records first. Never spend a founder's answer on something you could have looked up. Questions that reveal you did not read the code are the fastest way to lose an interview.

Read the full file on GitHub · 169 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 169 lines · 78 tokens per session scan A caab10453b51

Subscribe to this mod's changes

discovery-interview is a skill published in the GitHub repository rordi-ai/loopbreaker (3 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 1,702 once invoked, about $0.0004 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 2026-08-31.

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