ai-agent-dev

ai-agent-dev is a skill for Claude Code, Codex from Snailclimb/interview-guide. It costs 59 tokens per session (391 once invoked), scanned A, original, AGPL-3.0.

A Chinese-language interview-question guide for roles focused on AI-agent development. It covers agent design, language-model calls, tool integration, MCP, retrieval-augmented generation, context management, and multiple agents working together.

In plain words
What is it for?
Use it to prepare interview questions and evaluate candidates for AI-agent engineering positions.
Why use it?
It helps interviewers assess both an applicant’s understanding of AI-agent concepts and their ability to build and troubleshoot working systems.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to prepare interview questions and evaluate candidates for AI-agent engineering positions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/snailclimb/interview-guide/ai-agent-dev
About the project

InterviewGuide is an AI-assisted interview platform that analyzes résumés, runs text and voice mock interviews, manages interview schedules, and provides a retrieval-augmented knowledge-base question system. It is intended for job seekers, HR teams, and training organizations, and the catalogue skills and instructions support work with this project.

Snailclimb/interview-guide · 3,380 stars · on GitHub · javaguide.cn

Install

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.

Any agent
npx skills add Snailclimb/interview-guide --skill ai-agent-dev
Clone the repo
git clone --depth 1 https://github.com/Snailclimb/interview-guide

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ai-agent-dev

README.md
[![agentmods](https://agentmods.dev/badge/skills/snailclimb/interview-guide/ai-agent-dev/github.svg)](https://agentmods.dev/skills/snailclimb/interview-guide/ai-agent-dev)
Your own site
<a href="https://agentmods.dev/skills/snailclimb/interview-guide/ai-agent-dev"><img src="https://agentmods.dev/badge/skills/snailclimb/interview-guide/ai-agent-dev/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.

agentmods 80×15 button for ai-agent-dev

Your own site · 80×15
<a href="https://agentmods.dev/skills/snailclimb/interview-guide/ai-agent-dev"><img src="https://agentmods.dev/badge/skills/snailclimb/interview-guide/ai-agent-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 391 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.00391
Opus 5.5 $0.00024 $0.00156
Sonnet 5.5 $0.00012 $0.00078
Haiku 4.5 $0.00006 $0.00039

Measured 1mo ago against content hash 943dc133d83c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-agent-dev 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.

app/src/main/resources/skills/ai-agent-dev/SKILL.md · 19 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

2 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.

Changes

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.

  1. 1mo ago First seen · 19 lines · 59 tokens per session scan A 943dc133d83c

Subscribe to this mod's changes

ai-agent-dev is a skill published in the GitHub repository Snailclimb/interview-guide (3,380 stars, last pushed 10d ago), licensed AGPL-3.0. It adds 59 tokens to every session and 391 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 2026-08-30.