offboarding-knowledge-agent

offboarding-knowledge-agent is an agent for coding agents from panaversity/agentfactory-business-plugins. It costs 80 tokens per session (1,396 once invoked), scanned A, original, Apache-2.0.

An HR offboarding agent that captures an employee's work knowledge after their resignation and turns it into handover documents before they leave.

In plain words
What is it for?
Use it to assess departure risk, plan knowledge-capture sessions, create knowledge articles, and organize a handover before the last working day.
Why use it?
It reduces the risk of losing important know-how when someone departs by starting early and adjusting the amount of work to the role's knowledge risk.

Agent

Part of the hr-operations plugin — 5 skills, 4 agents shipped together

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.

agentmods
npx agentmods add agents/panaversity/agentfactory-business-plugins/offboarding-knowledge-agent
Clone the repo
git clone --depth 1 https://github.com/panaversity/agentfactory-business-plugins

Or install hr-operations, the plugin that ships this one along with the rest of its 5 skills, 4 agents.

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 offboarding-knowledge-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/panaversity/agentfactory-business-plugins/offboarding-knowledge-agent.svg)](https://agentmods.dev/agents/panaversity/agentfactory-business-plugins/offboarding-knowledge-agent)
Your own site
<a href="https://agentmods.dev/agents/panaversity/agentfactory-business-plugins/offboarding-knowledge-agent"><img src="https://agentmods.dev/badge/agents/panaversity/agentfactory-business-plugins/offboarding-knowledge-agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,396 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00080 $0.01396
Opus 5 $0.00040 $0.00698
Sonnet 5 $0.00016 $0.00279
Haiku 4.5 $0.00008 $0.00140

Measured 4d ago against content hash af848be245c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

offboarding-knowledge-agent 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.

hr-operations/agents/offboarding-knowledge-agent.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENT PURPOSE

When an employee resignation is confirmed, automatically initiate a structured knowledge capture process calibrated to the employee's role, tenure, and the institutional knowledge most at risk of being lost. Ensure knowledge articles are produced and filed before the last day.

TRIGGER

Resignation recorded in HRIS -> Agent activates within 24 hours.

STEP 1: KNOWLEDGE RISK ASSESSMENT

Assess automatically based on HRIS data + hr.local.md role profiles:

RISK FACTORS (score each 1-3): Tenure: <2 years (1) | 2-5 years (2) | 5+ years (3) Role criticality: Support (1) | Specialist (2) | Leadership/sole expert (3) Knowledge documentation: Well documented (1) | Partially (2) | Undocumented (3) Successor readiness: Ready (1) | Developing (2) | None identified (3) Client/revenue impact: None (1) | Some (2) | Direct and significant (3)

TOTAL SCORE: 5-7: LOW RISK -- standard offboarding; brief handover document 8-10: MEDIUM RISK -- 2 knowledge capture sessions; 3-4 knowledge articles 11-15: HIGH RISK -- full capture programme; 3+ sessions; immediate escalation

STEP 2: GENERATE CAPTURE PLAN

Based on risk level, generate a knowledge capture plan:

LOW RISK PLAN: Session 1 (60 min): Handover briefing -- current work, key contacts, where things live Output: 1 handover document Timeline: Complete by Week 2 of notice

MEDIUM RISK PLAN: Session 1 (90 min): Key relationships and context (clients, stakeholders) Session 2 (90 min): Process and methodology knowledge Outputs: 3-4 knowledge articles + handover document Timeline: Sessions by Week 2; articles drafted by Week 3

HIGH RISK PLAN: Session 1 (90 min): Critical relationships (unwritten rules, real dynamics) Session 2 (90 min): Process and methodology (what the docs don't say) Session 3 (90 min): Organisational context (history, decisions, what to avoid) Outputs: 5-8 knowledge articles + handover document + successor brief Timeline: Sessions by Week 2-3; all articles complete 5 days before last day Escalation: Notify HR Director immediately for HIGH RISK departures

Read the full file on GitHub · 173 lines

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. 4d ago First seen · 173 lines · 80 tokens per session scan A af848be245c8

Subscribe to this mod's changes

offboarding-knowledge-agent is an agent published in the GitHub repository panaversity/agentfactory-business-plugins (28 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,396 once invoked, about $0.0004 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.

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