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 curiositech/some_claude_skills --skill interview-loop-strategistgit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/interview-loop-strategist)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/interview-loop-strategist"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/interview-loop-strategist/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/curiositech/some_claude_skills/interview-loop-strategist"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/interview-loop-strategist.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 | $0.00082 | $0.02974 |
| Opus 5 | $0.00041 | $0.01487 |
| Sonnet 5 | $0.00016 | $0.00595 |
| Haiku 4.5 | $0.00008 | $0.00297 |
Grade A, and why
interview-loop-strategist 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 6d 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 — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Loop Strategist
End-to-end orchestrator for senior-level AI/ML interview preparation. Coordinates timelines, story coherence across rounds, mock interview cadence, energy management, and post-interview debrief -- routing each round type to its specialist skill.
When to Use
Use for:
- Building a complete interview prep plan for a specific company
- Generating 2-week, 1-month, or 2-month preparation timelines
- Ensuring story coherence -- the same project told correctly across behavioral, technical, and HM rounds
- Scheduling and tracking mock interview cadence
- Energy management strategy for all-day virtual or onsite loops
- Post-interview debrief analysis and improvement planning
- Coordinating across all 7 round-specific interview skills
NOT for:
- Resume or CV creation (use
cv-creator) - Career narrative extraction (use
career-biographer) - Practicing a single round type in isolation (use the round-specific skill directly)
- Salary negotiation or offer evaluation
- General career counseling
Full Interview Pipeline
flowchart TD
A[Career Biographer] -->|Extracts narrative| B[CV Creator]
B -->|Resume finalized| C[Interview Loop Strategist]
C --> D{Company Target Selected}
D --> E[Generate Prep Timeline]
E --> F[Story Coherence Matrix]
F --> G[Round-Specific Prep]
G --> G1[Recruiter Screen<br/>Self-prep]
G --> G2[CodeSignal / Coding<br/>senior-coding-interview]
G --> G3[Hiring Manager Screen<br/>hiring-manager-deep-dive]
G --> G4[ML System Design<br/>ml-system-design-interview]
G --> G5[Technical Deep Dive<br/>anthropic-technical-deep-dive]
G --> G6[Tech Presentation<br/>tech-presentation-interview]
G --> G7[Values & Behavioral<br/>values-behavioral-interview]
G1 --> H[Mock Interviews<br/>interview-simulator]
G2 --> H
G3 --> H
G4 --> H
G5 --> H
G6 --> H
G7 --> H
H --> I[Debrief & Adjust]
I -->|Iterate| G
I --> J[Interview Day<br/>Energy Protocol]
J --> K[Post-Loop Debrief]
K --> L{Offer?}
L -->|Yes| M[Negotiation Phase]
L -->|No| N[Gap Analysis & Retry]
N -->|Update plan| E
What ships with it
4 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.
- 6d ago First seen · 282 lines · 82 tokens per session scan A 13f296a84c18
interview-loop-strategist is a skill published in the GitHub repository curiositech/some_claude_skills (216 stars, last pushed 3d ago), licensed MIT. It adds 82 tokens to every session and 2,974 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 2026-09-03.
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