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 fanfan-de/anybox --skill search-company-knowledgegit clone --depth 1 https://github.com/fanfan-de/anyboxWrote 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/fanfan-de/anybox/search-company-knowledge)<a href="https://agentmods.dev/skills/fanfan-de/anybox/search-company-knowledge"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/search-company-knowledge/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/fanfan-de/anybox/search-company-knowledge"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/search-company-knowledge.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 | $0.00118 | $0.03862 |
| Opus 5 | $0.00059 | $0.01931 |
| Sonnet 5 | $0.00024 | $0.00772 |
| Haiku 4.5 | $0.00012 | $0.00386 |
Grade A, and why
search-company-knowledge 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 11d 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.
This is a copy
100% identical to search-company-knowledge — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 576 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Company Knowledge
Keywords
find information, search company knowledge, look up, what is, explain, company docs, internal documentation, Confluence search, Jira search, our documentation, internal knowledge, knowledge base, search for, tell me about, get information about, company systems, terminology, find everything about, what do we know about, deployment, authentication, infrastructure, processes, procedures, how to, how does, our systems, our processes, internal systems, company processes, technical documentation, engineering docs, architecture, configuration, search our docs, search internal docs, find in our docs
Overview
Search across siloed company knowledge systems (Confluence, Jira, internal documentation) to find comprehensive answers to questions about internal concepts, systems, and terminology. This skill performs parallel searches across multiple sources and synthesizes results with proper citations.
Use this skill when: Users ask about internal company knowledge that might be documented in Confluence pages, Jira tickets, or internal documentation.
Workflow
Follow this 5-step process to provide comprehensive, well-cited answers:
Step 1: Identify Search Query
Extract the core search terms from the user's question.
Examples:
- User: "Find everything about Stratus minions" → Search: "Stratus minions"
- User: "What do we know about the billing system?" → Search: "billing system"
- User: "Explain our deployment process" → Search: "deployment process"
Consider:
- Main topic or concept
- Any specific system/component names
- Technical terms or jargon
Step 2: Execute Parallel Search
Search across all available knowledge sources simultaneously for comprehensive coverage.
Option A: Cross-System Search (Recommended First)
Use the search tool (Rovo Search) to search across Confluence and Jira at once:
search(
cloudId="...",
query="[extracted search terms]"
)
When to use:
- Default approach for most queries
- When you don't know which system has the information
- Fastest way to get results from multiple sources
What ships with it
1 file 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.
- 11d ago First seen · 576 lines · 118 tokens per session scan A 580f5c5f5b66
search-company-knowledge is a skill published in the GitHub repository fanfan-de/anybox (57 stars, last pushed 28d ago), licensed MIT. It adds 118 tokens to every session and 3,862 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to search-company-knowledge, differing in 34 lines, and is treated as a copy.
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