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.
npx skills add ils15/pantheon-legacy --skill interviewgit clone --depth 1 https://github.com/ils15/pantheon-legacyWrote 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/ils15/pantheon-legacy/interview)<a href="https://agentmods.dev/skills/ils15/pantheon-legacy/interview"><img src="https://agentmods.dev/badge/skills/ils15/pantheon-legacy/interview/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/ils15/pantheon-legacy/interview"><img src="https://agentmods.dev/badge/skills/ils15/pantheon-legacy/interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00822 |
| Opus 5.5 | $0.00008 | $0.00329 |
| Sonnet 5.5 | $0.00004 | $0.00164 |
| Haiku 4.5 | $0.00002 | $0.00082 |
Grade A, and why
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 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview — Idea to Spec
Use this skill to transform a rough idea into a structured spec before implementation. A 5-minute interview prevents hours of rework.
Usage
Invoke via the /sketch command:
/sketch Add a notification system so users get alerted when their order ships
Or trigger Athena directly:
@athena: Interview me about this feature: real-time dashboard for agent cost tracking
Interview Protocol
Phase 1: Discover (3–5 questions, one at a time)
Ask questions in this priority order, stopping after you have enough clarity:
- Scope — "What's the minimum viable version of this feature?"
- Users — "Who uses this and what's their primary workflow?"
- Constraints — "Are there tech, time, or integration constraints?"
- Success criteria — "How will you know this is working correctly?"
- Non-goals — "What should this explicitly NOT do?"
Rules:
- Ask one question at a time — never batch questions
- Wait for the answer before asking the next
- Stop asking when you have answers to at least 3 questions
- If the user is unsure, offer 2–3 concrete options to choose from
Phase 2: Confirm Understanding
Before writing the spec, summarize your understanding in 2–3 sentences and ask: "Does this match what you have in mind, or did I miss anything?"
Phase 3: Write the Spec
Produce the spec only after getting confirmation.
Spec Output Format
# Feature Spec: <Feature Name>
**Date:** YYYY-MM-DD
**Status:** Draft
## Overview
<2–3 sentence description of the feature and its purpose>
## Goals
- <Goal 1>
- <Goal 2>
- <Goal 3>
## Non-Goals
- <What this feature explicitly does NOT cover>
- <Scope boundary 1>
- <Scope boundary 2>
## Functional Requirements
### Must Have (MVP)
- [ ] <Requirement 1>
- [ ] <Requirement 2>
- [ ] <Requirement 3>
### Should Have (v1.1)
- [ ] <Requirement 4>
### Won't Have (out of scope)
- <Explicitly excluded>
## Technical Constraints
- **Stack:** <relevant tech>
- **Integrations:** <APIs, services>
- **Performance:** <latency, throughput requirements if any>
- **Security:** <auth, data sensitivity>
## Success Criteria
- [ ] <Measurable outcome 1>
- [ ] <Measurable outcome 2>
## Open Questions
- [ ] <Unresolved decision 1>
- [ ] <Unresolved decision 2>
## Suggested Implementation Phases
1. **Phase 1:** <database/schema>
2. **Phase 2:** <backend API>
3. **Phase 3:** <frontend>
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 · 139 lines · 21 tokens per session scan A 0e4e35ed0fe2
interview is a skill published in the GitHub repository ils15/pantheon-legacy (12 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 822 once invoked, about $0.0001 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 2026-08-31.
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