Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add tzachbon/smart-ralph/plugin install ralph-specumWrote 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.
[](https://agentmods.dev/skills/tzachbon/smart-ralph/interview-framework)<a href="https://agentmods.dev/skills/tzachbon/smart-ralph/interview-framework"><img src="https://agentmods.dev/badge/skills/tzachbon/smart-ralph/interview-framework/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tzachbon/smart-ralph/interview-framework"><img src="https://agentmods.dev/badge/skills/tzachbon/smart-ralph/interview-framework.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01749 |
| Opus 5.5 | $0.00018 | $0.00700 |
| Sonnet 5.5 | $0.00009 | $0.00350 |
| Haiku 4.5 | $0.00004 | $0.00175 |
Grade A, and why
interview-framework 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Framework
Treat every normal-mode interview governed by this framework as a grill. Run the approval-gated interview for start, triage, research, requirements, design, and tasks. Treat this skill and its references as the single source of truth for interview behavior. Phase commands supply exploration territory and artifact context; they do not redefine the algorithm.
Quick mode bypasses interview questions only. It still requires current discovery, contract loading, bypass receipts, delegation checks, and artifact-agent load parity.
Entry Contract
Before each new or resumed interview:
- Complete the applicable skill discovery pass from
${CLAUDE_PLUGIN_ROOT}/references/normal-mode-gates.md. - Reload this entire
SKILL.md,references/algorithm.md,references/domain-modeling.md, every selected skill body, and every selected skill resource required for the current work. Loadreferences/examples.mdonly when an example is needed. - Record the load manifest with
phase_gate.py record-skill-load. - Begin or resume the interview with the matching phase, interview ID, discovery revision, and context digest.
Block when this skill or the core algorithm reference cannot be loaded. Warn and continue when a domain skill fails to load. Put unresolved material conflicts in the first critical frontier.
Critical Decision Test
Grill only a decision that meets both conditions:
- The answer cannot be established by inspecting the project, prior artifacts, configuration, or selected skill contracts.
- Different answers would materially change scope, observable behavior, architecture, risk acceptance, delivery sequencing, or the acceptance standard.
Inspect facts with read-only tools or an Explore agent. Exclude setup choices, administrative preferences, status questions, facts the repository can answer, and low-impact polish. Treat a prescribed task action in a loaded domain skill as reference material during preload; do not execute it until the phase has approval and delegation begins.
What ships with it
3 files 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.
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.
- 1mo ago First seen · 136 lines · 44 tokens per session scan A a7dca262779f
interview-framework is a skill published in the GitHub repository tzachbon/smart-ralph (559 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,749 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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