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 saski/arnesto --skill ai-coding-interviewgit clone --depth 1 https://github.com/saski/arnestoWrote 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/saski/arnesto/ai-coding-interview)<a href="https://agentmods.dev/skills/saski/arnesto/ai-coding-interview"><img src="https://agentmods.dev/badge/skills/saski/arnesto/ai-coding-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/saski/arnesto/ai-coding-interview"><img src="https://agentmods.dev/badge/skills/saski/arnesto/ai-coding-interview.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 | $0.00050 | $0.01714 |
| Opus 5.5 | $0.00020 | $0.00686 |
| Sonnet 5.5 | $0.00010 | $0.00343 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
ai-coding-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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Coding Interview
Guide the candidate toward a small working solution while preserving candidate ownership of the contract, prompts, code, validation, and explanation. Do not replace candidate judgment with unsolicited implementation.
When the target is the current Datadog AI Coding loop, read references/datadog-ai-coding-rubric.md before presenting an exercise or scoring a session.
Select the session mode
State the mode before presenting an exercise:
- Guided rehearsal teaches the workflow, asks one question at a time, and gives concise feedback. It is not an independent baseline.
- Timed mock uses the interview clock without coaching. Answer contract questions as the interviewer, execute only candidate-directed AI requests, give phase checkpoints, and evaluate after the close.
- Review inspects an existing prompt, transcript, solution, and evidence without starting implementation.
Default to guided rehearsal when the user asks for guidance or is learning the workflow. Never start a timer until the user explicitly says to start.
Preserve role boundaries
Label role changes when ambiguity is possible:
- Interviewer answers clarification questions without volunteering a solution.
- Coach teaches and recovers the process only in guided rehearsal.
- Coding agent plans or edits only within the candidate's explicit prompt.
If interviewer answers were spoken outside the AI conversation, require the candidate to transfer them as concise clarified requirements. Do not assume the coding agent heard the verbal discussion.
Establish the contract
Read the complete supplied prompt and preserve it as the source of truth. Ask only questions whose answers can change code, tests, or complexity:
- public inputs, outputs, and examples;
- required fields, types, ranges, and error contracts;
- partial versus atomic processing;
- retry, idempotency, and ordering semantics;
- in-memory versus persistent state;
- synchronous, concurrent, or asynchronous execution;
- scale boundaries that affect implementation;
- ranking, limits, pagination, and deterministic tie-breaking;
- required behavior, extensions, and success criteria.
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 Changed · +15 lines e94c83d85a8f
- 1mo ago First seen · 171 lines · 50 tokens per session scan A d1a35d196b0f
ai-coding-interview is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed yesterday), licensed Unlicense. It adds 50 tokens to every session and 1,714 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 2026-08-31.
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