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/techwolf-ai/ai-first-toolkit/kb-importnpx skills add techwolf-ai/ai-first-toolkit --skill kb-importgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWrote 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/techwolf-ai/ai-first-toolkit/kb-import)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/kb-import"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/kb-import.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 | $0.00042 | $0.01365 |
| Opus 5 | $0.00021 | $0.00682 |
| Sonnet 5 | $0.00008 | $0.00273 |
| Haiku 4.5 | $0.00004 | $0.00136 |
Grade A, and why
kb-import 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 4d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KB Import Workflow
Import knowledge from existing documents into your knowledge base.
When to Use
- Adding knowledge from existing documentation
- Converting unstructured docs into structured KB entries
- Bulk-importing content into a new KB
Modes
- Single-document mode (default): one source document is split into one or more KB entries. Use Steps 1 to 6 below.
- Bulk mode: many source documents are ingested at once from a directory or a list of files. Use when the user points at a folder or provides a list longer than ~3 files. See Bulk Mode at the bottom.
Step 1: Understand the KB Structure
Read the KB config to understand available categories:
kb/.kb-config.yaml
Read the index to see what already exists:
kb/index.md
Step 2: Read the Source Document
Read the source file provided by the user. Supported formats:
- Markdown (.md)
- PDF (.pdf, use the Read tool with page ranges for large files)
- Plain text (.txt)
Step 3: Plan the Extraction
Analyze the document and propose a plan to the user:
- How many KB entries should be created?
- What categories do they belong to?
- Suggested titles for each entry
Present this as a table:
| # | Title | Category | Source Section |
|---|-------|----------|---------------|
| 1 | ... | ... | ... |
Wait for user confirmation before proceeding.
Step 4: Create KB Entries
For each planned entry, create a markdown file with YAML frontmatter:
---
title: "Entry Title"
description: "Brief one-liner for index lookup"
category: {category}
tags: [{tag1}, {tag2}]
sources: ["{source_filename}"]
last_updated: "{today's date}"
related:
- {category}/{related-file}.md
---
## Section Title
Content here. Write clear, quotable statements.
Each fact should be a self-contained sentence that can be cited as evidence.
Content Guidelines
- Preserve specifics: Keep exact numbers, dates, names, versions. Keep concrete customer/product examples by name (e.g., "Acme Corp", "Globex") — they make abstract concepts tangible and shouldn't be stripped "for neutrality".
- One topic per entry: Don't create catch-all files
- Quotable statements: Write so that individual sentences can be cited as evidence
- Capture the easily-missed content types when the source covers them: stakeholders (one entry per key person with role + ownership + contact pattern), projects (goal/owner/status), repositories (purpose/ownership). These are the most commonly skipped in first-pass imports.
- No opinions or speculation: Only include facts from the source document
- Use markdown structure: Headers, bullet points, tables for structured data
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.
- 4d ago First seen · 159 lines · 42 tokens per session scan A a4a8a6e4e82e
kb-import is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (98 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 1,365 once invoked, about $0.0002 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
yuque
Read and write Yuque (语雀) documents on the user's own account — list knowledge bases (知识库), read a document, publish Markdown, and update or delete one. Works with either the user's browser login (free) or a personal access token. Use when the user wants to publish Markdown to 语雀, list their 语雀 knowledge bases, or…
citra
Skill "citra" from SylphxAI/pdf-reader-mcp, covering citra — pdf evidence for agents, install, or, tools and sdk.
mathodology-award-gates
Use when running Mathodology award-workflow phase gates, judge panels, structured handoffs, figure QA, or rendered-PDF QA in a contest run.
wrap
Session end - document updates, commit.
product-implement
Generate a full Product Requirements Document (PRD.md) from accepted PDRs using multi-agent DAG orchestration. Reads individual PDR files, generates PRD sections from templates, validates output, and promotes accepted PDRs to memory. Use after /product-clarify.
paper2xhs
把学术论文 PDF 转成小红书多图帖(标题 + 正文 + 标签 + 封面 + 论文主图/主实验结果配图)。你主导设计的协调式:机械活(MinerU 解析 PDF、生成封面与配图、半自动发布)交给 scripts/ 下的小工具,论文理解、选题角度、文案撰写由你亲自完成并在关键点与用户确认。当用户说“论文转小红书”、“paper2xhs”、“把这篇论文发小红书”、“论文转社交媒体”、“PDF 转小红书帖子”时触发。.