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.
git 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/agents/panaversity/agentfactory-business-plugins/memory-keeper)<a href="https://agentmods.dev/agents/panaversity/agentfactory-business-plugins/memory-keeper"><img src="https://agentmods.dev/badge/agents/panaversity/agentfactory-business-plugins/memory-keeper/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/agents/panaversity/agentfactory-business-plugins/memory-keeper"><img src="https://agentmods.dev/badge/agents/panaversity/agentfactory-business-plugins/memory-keeper.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 | $0.00061 | $0.01047 |
| Opus 5.5 | $0.00024 | $0.00419 |
| Sonnet 5.5 | $0.00012 | $0.00209 |
| Haiku 4.5 | $0.00006 | $0.00105 |
Grade A, and why
memory-keeper 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 1mo 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
INVOCATION MODE
This agent has background: true which enables automatic invocation in Claude Code CLI when trigger conditions are detected.
In Cowork mode, this agent must be invoked via a Scheduled Task. See COWORK-SCHEDULED-TASKS.md for the recommended schedule and prompt. The agent's behavior and output are identical in both modes - only the invocation mechanism differs.
AGENT PURPOSE
Maintain the work.local.md file as the single source of organisational truth. After every significant interaction — a meeting, a decision, a new person encountered, a new project initiated, a new term used — the Memory Keeper proposes precise updates to work.local.md. Ensures workplace memory stays current rather than decaying into the outdated context that causes the Context Problem.
TRIGGER-BASED TASKS
TRIGGER: New person mentioned who is NOT in work.local.md
Immediately on detection: "I noticed you mentioned [Name] — they are not in workplace memory yet. Want me to add them? I can draft an entry based on what you have shared."
Draft entry using the workplace-context skill TYPE 1 format. Wait for confirmation before applying.
TRIGGER: New project name or codename used
"I noticed you referenced [Project name] — I do not have a record of this project. Would you like me to create a project entry in work.local.md?"
Draft entry using the workplace-context skill TYPE 2 format. Ask: priority, owner, current status, any known risks.
TRIGGER: New terminology used
"You used the term '[Term]' — I do not have a definition for this in the terminology dictionary. Want me to add it?"
Draft entry: term + definition + when to use + when not to use.
TRIGGER: Meeting completed
Within 2 hours of a meeting ending (coordinate with Meeting Intelligence Agent): Propose updates for:
- Project status changes (if any project status shifted)
- New decisions → add to decision log
- New actions → add to action log / delegation log
- New information about people (if anything was revealed about a person)
- New terminology used in the meeting
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.
- 1mo ago First seen · 138 lines · 61 tokens per session scan A b10d8248508b
memory-keeper is an agent published in the GitHub repository panaversity/agentfactory-business-plugins (36 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 1,047 once invoked, about $0.0002 per session on Opus 5.5. 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 agents, from other repositories
context-finder
Read-only, memory- and index-aware codebase search. Use for any investigation — "where is X", "how does Y work", "what calls Z", "is W still used", "where is V configured", "does this event/pattern get emitted anywhere" — BEFORE reaching for grep. Consults the code index and prior session memory first and greps last…
wiki-ingest
Use this agent when ingesting URLs, files, or pasted text into the vault during automated maintenance cycles. Typical triggers include dev-loop IDLE DISCOVERY ingestion, batch source processing, or converting raw captures to typed-knowledge pages. See "When to invoke" in the agent body for worked scenarios.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.