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Interview Framework Codex

Community
tzachbon
interview-framework-codex

Internal Ralph Specum contract for Codex phase interviews, skill manifests, approval, and delegation gates. Phase coordinators load this skill directly; users do not invoke it as a workflow phase.

Overview

Publishertzachbon
Repositorysmart-ralph
Skill nameinterview-framework-codex
Stars
559
Forks
50
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tzachbon on GitHub. Read the source before you install it.

Installation

Install the Interview Framework Codex AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/interview-framework-codex
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tzachbon/smart-ralph.git /tmp/smart-ralph
mkdir -p .claude/skills
cp -r /tmp/smart-ralph/plugins/ralph-specum-codex/skills/interview-framework-codex .claude/skills/interview-framework-codex
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Interview Framework Codex in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Interview Framework Codex on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Interview Framework Codex is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Codex interview framework

Run every normal-mode start, triage, research, requirements, design, and tasks phase through references/algorithm.md and references/domain-modeling.md.

Completion criterion

Delegate only after all of these conditions hold for one identity tuple:

  • phase, interviewId, discoveryRevision, and contextDigest match in state and in the delegation packet.
  • The selected skill manifest has status complete or partial_warned.
  • The phase interview has status complete or skipped after explicit final approval.
  • phase_gate.py check-delegation succeeds.

Hard-transition invariant

Run the current check-delegation immediately before each affected phase transition or child dispatch. A failed check-delegation in either mode stops this invocation before state transition, child dispatch, or target-artifact write. After a normal-mode failure, the next explicit invocation uses a fresh manifest/interview identity. After an exact --quick delegation failure, the next explicit invocation reruns discovery, records a fresh phaseSkillLoad and interview identity, and does not reuse a terminal bypassed_quick interview or its discovery revision. Only a matching in-progress collecting or awaiting_confirmation interview is resumable. A matching in-progress interview that has not reached a failed delegation boundary remains valid for resume.

Exact --quick preserves discovery, manifest, parent-delegation provenance, check-delegation, receipt recording, and check-agent-write. Quick mode bypasses interview questions only. Exact --quick separately bypasses final approval. It still runs check-delegation immediately before dispatch, uses the same identity tuple, requires a current complete or partial_warned manifest plus an interview receipt with status bypassed_quick and quickAuthorization.source: "--quick", and has no other bypass.

Hard boundaries

  • Ask only critical user decisions that can change phase scope, externally visible behavior, acceptance, architecture, sequencing, or material risk.
  • Inspect code, configuration, state, prior artifacts, and selected skill contracts for facts. Do not ask the user for discoverable facts or setup and administration choices.
  • Ask the whole currently unblocked critical frontier. Split a frontier only when Codex's native user-input tool limit requires another batch. The current limit is three questions per call.
  • Put the recommended option first and state its tradeoff. Offer only viable alternatives.
  • Persist each partial answer before asking the next frontier.
  • Treat control-only replies such as apply the changes, continue, proceed, and go ahead as no answer to an active interview question.
  • Treat bare skip during an active question as an instruction to finish the remaining interview with stated defaults and assumptions. Present the final approval gate before delegation.
  • Delegate in the same turn after the user explicitly chooses approve and delegate.
  • During artifact review, treat apply the changes as a revision request. Delegate the revision and remain at the artifact approval gate.
  • Apply domain-language modeling during the grill. Challenge conflicting or vague terms, use concrete boundary scenarios, and record resolved domain terms without creating an ADR.

Preload boundary

Load selected skill bodies and required current-work references as contracts. During preload, collect constraints, vocabulary, checks, and conflicts. Start no task action prescribed by a loaded domain skill until the phase interview is approved and the delegation gate passes.

If this core skill, its algorithm reference, or its domain-modeling reference cannot be read and hashed, record phaseSkillLoad.status: "core_failed", report the failure, and stop. Record domain-skill load failures in warnings and failures, use partial_warned, and continue. Turn unresolved material conflicts between loaded contracts into first-layer interview decisions.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Interview Framework Codex AI skill do?

Internal Ralph Specum contract for Codex phase interviews, skill manifests, approval, and delegation gates. Phase coordinators load this skill directly; users do not invoke it as a workflow phase.

Why use Interview Framework Codex on TypingMind?

Because you install it once and use it with any model. Interview Framework Codex is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Interview Framework Codex in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/interview-framework-codex. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Interview Framework Codex?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Interview Framework Codex?

As many as you like. As long as a model supports skills, you can use Interview Framework Codex with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Interview Framework Codex AI skill free?

Yes. It is published on GitHub by tzachbon under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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