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/panaversity/agentfactory-business-plugins/knowledgenpx skills add panaversity/agentfactory-business-plugins --skill knowledgegit clone --depth 1 https://github.com/panaversity/agentfactory-business-pluginsWrote 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/panaversity/agentfactory-business-plugins/knowledge)<a href="https://agentmods.dev/skills/panaversity/agentfactory-business-plugins/knowledge"><img src="https://agentmods.dev/badge/skills/panaversity/agentfactory-business-plugins/knowledge.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 | $0.00107 | $0.02297 |
| Opus 5 | $0.00053 | $0.01149 |
| Sonnet 5 | $0.00021 | $0.00459 |
| Haiku 4.5 | $0.00011 | $0.00230 |
Grade A, and why
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 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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UNIVERSAL RULES (apply to every knowledge capture task)
- NEVER treat the departing employee's account as the complete truth -- cross-reference with documentation and other stakeholders where possible
- NEVER let knowledge capture become a blame session -- frame all capture as organisational learning, not performance review
- NEVER classify knowledge as LOW RISK without checking whether anyone else actually holds it -- "I thought [person] knew this too" is a common and expensive mistake
- NEVER publish a knowledge article without a reviewer confirming accuracy -- mark as DRAFT until reviewed
- NEVER skip the "what we should NOT try again" question -- this is often the most valuable institutional knowledge captured
- ALWAYS include specific recommended actions and timeline
BEFORE IMPLEMENTATION
| Source | Check |
|---|---|
| Conversation | Departing employee name, role, tenure, last working day, known critical knowledge areas |
| hr.local.md | HR contact directory (who conducts capture sessions), data retention policy (how long knowledge articles are kept), knowledge article storage location |
| Prior outputs | None — /knowledge is typically the first skill invoked in a departure workflow |
CLARIFICATION QUESTIONS
Required (ask if not provided):
- Who is the departing employee? (name and role)
- When is their departure date?
Optional (ask if context suggests value):
- What are the known critical knowledge areas this person holds?
- Has a successor been identified?
- Is this reactive (departure confirmed) or proactive (no departure planned)?
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.
- 4d ago First seen · 276 lines · 107 tokens per session scan A fdc5dc47c009
knowledge is a skill published in the GitHub repository panaversity/agentfactory-business-plugins (28 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 107 tokens to every session and 2,297 once invoked, about $0.0005 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
remember
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memory-read
Query-first indexing and retrieval for Operator OS memory. Use when asked to find prior context, search memory, rebuild the memory index, or answer from the workspace without loading large files by default.
memory-manage
Manage Active updates, atomic session handoffs, and human-gated Long-Term proposals. Use when asked to remember something, preserve a decision, log meaningful work, or review memory.
brain-sync
Sync knowledge and learnings to the shared appie-brain repo. Every Appie commits with their own identity so contributions are traceable. Use after: complex tasks (5+ tool calls), significant discoveries, new skills, or client work. Fleet: Appie-1 (Orchestrator/MacMini), Appie-2 (CMO/DO), Appie-3 (CTO/VPS).
project-context-sync
Keep a living project state document updated after each commit, so any agent (or future session) can instantly understand where things stand.
memory-search
Search and retrieve information from the Appie brain — daily logs, project notes, decisions, topics, and long-term memory files stored in /.hermes/memory/. Use this skill whenever you need to recall past conversations, decisions, project context, personal preferences, or anything discussed previously.