AI Agent: Design Principles and Engineering Practice is an open-source book that explains how AI agents combine language models, context, and tools, with accompanying experiments and code. It is intended for readers studying the principles and engineering of AI agents, from fundamentals through production use. The catalogue skills support coding-agent work related to the book's subject matter.
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 agentmods add skills/bojieli/ai-agent-book/data_analysisnpx skills add bojieli/ai-agent-book --skill data_analysisgit clone --depth 1 https://github.com/bojieli/ai-agent-bookWrote 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/bojieli/ai-agent-book/data_analysis)<a href="https://agentmods.dev/skills/bojieli/ai-agent-book/data_analysis"><img src="https://agentmods.dev/badge/skills/bojieli/ai-agent-book/data_analysis.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.00125 |
| Opus 5 | $0.00010 | $0.00063 |
| Sonnet 5 | $0.00004 | $0.00025 |
| Haiku 4.5 | $0.00002 | $0.00013 |
Grade A, and why
data_analysis 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 5d 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.
What it actually says
Data Analysis Skill
你是数据分析专家。只使用共享历史中已经给出且有来源的数据；调用 calculate
或 descriptive_stats，并在结果中写出表达式、单位和假设。若数据不足，明确
指出缺口并请求切换到 research，不要猜测。
计算完成后，若用户需要面向特定读者的成稿，请求切换到 writing；否则直接回答。
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.
- 5d ago First seen · 13 lines · 19 tokens per session scan A 77a5dc00baa4
data_analysis is a skill published in the GitHub repository bojieli/ai-agent-book (44,721 stars, last pushed today), licensed Apache-2.0. It adds 19 tokens to every session and 125 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
acontext-installer
Install Acontext, Login & Init Acontext Project, Add Skill Memory to Agent.
tura
Work in the Tura agent-runtime repository. Use for Tura architecture, Rust backend, GUI/TUI, prompts, commands, providers, sessions, documentation, tests, packaging, and release work in this directory.
remem-mcp
Long-term memory for coding agents. Auto-applies at the start of any coding task — recall past context before answering, capture decisions/learnings/fixes after work, use CodeGraph instead of grep for symbol lookup. Invoke when you see [remem-mcp] in your context or when starting any non-trivial coding work.
kayba-stage-5-action-plan
Triage each insight into discard/code-fix/prompt-fix and produce a prioritized action plan with specific recommendations. Trigger when the user says "run stage 5", "make action plan", "triage skills", or when invoked by the kayba-pipeline orchestrator. Requires eval outputs from stages 1-4.
kayba-stage-2-domain-context
Gather domain context about the repository and agent — system prompt, tool definitions, domain docs, and behavior patterns from traces. Trigger when the user says "run stage 2", "gather context", "domain context", or when invoked by the kayba-pipeline orchestrator.
kayba-stage-7-fixer
Implement the approved fixes from the action plan and log all changes. Trigger when the user says "run stage 7", "implement fixes", "apply action plan", or when invoked by the kayba-pipeline orchestrator. Requires eval/actionplan.md to exist.