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 kyopark2014/agent-plugins --skill memory-managementgit clone --depth 1 https://github.com/kyopark2014/agent-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/kyopark2014/agent-plugins/memory-management)<a href="https://agentmods.dev/skills/kyopark2014/agent-plugins/memory-management"><img src="https://agentmods.dev/badge/skills/kyopark2014/agent-plugins/memory-management/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/kyopark2014/agent-plugins/memory-management"><img src="https://agentmods.dev/badge/skills/kyopark2014/agent-plugins/memory-management.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 | $0.00054 | $0.02199 |
| Opus 5.5 | $0.00022 | $0.00880 |
| Sonnet 5.5 | $0.00011 | $0.00440 |
| Haiku 4.5 | $0.00005 | $0.00220 |
Grade A, and why
memory-management 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.
This is a copy
97% identical to memory-management — 1 line 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Management
Memory makes Claude your workplace collaborator - someone who speaks your internal language.
The Goal
Transform shorthand into understanding:
User: "ask todd to do the PSR for oracle"
↓ Claude decodes
"Ask Todd Martinez (Finance lead) to prepare the Pipeline Status Report
for the Oracle Systems deal ($2.3M, closing Q2)"
Without memory, that request is meaningless. With memory, Claude knows:
- todd → Todd Martinez, Finance lead, prefers Slack
- PSR → Pipeline Status Report (weekly sales doc)
- oracle → Oracle Systems deal, not the company
Architecture
CLAUDE.md ← Hot cache (~30 people, common terms)
memory/
glossary.md ← Full decoder ring (everything)
people/ ← Complete profiles
projects/ ← Project details
context/ ← Company, teams, tools
CLAUDE.md (Hot Cache):
- Top ~30 people you interact with most
- ~30 most common acronyms/terms
- Active projects (5-15)
- Your preferences
- Goal: Cover 90% of daily decoding needs
memory/glossary.md (Full Glossary):
- Complete decoder ring - everyone, every term
- Searched when something isn't in CLAUDE.md
- Can grow indefinitely
memory/people/, projects/, context/:
- Rich detail when needed for execution
- Full profiles, history, context
Lookup Flow
User: "ask todd about the PSR for phoenix"
1. Check CLAUDE.md (hot cache)
→ Todd? ✓ Todd Martinez, Finance
→ PSR? ✓ Pipeline Status Report
→ Phoenix? ✓ DB migration project
2. If not found → search memory/glossary.md
→ Full glossary has everyone/everything
3. If still not found → ask user
→ "What does X mean? I'll remember it."
This tiered approach keeps CLAUDE.md lean (~100 lines) while supporting unlimited scale in memory/.
File Locations
- Working memory:
CLAUDE.mdin current working directory - Deep memory:
memory/subdirectory
Working Memory Format (CLAUDE.md)
Use tables for compactness. Target ~50-80 lines total.
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 · 323 lines · 54 tokens per session scan A 165c4083833a
memory-management is a skill published in the GitHub repository kyopark2014/agent-plugins (4 stars, last pushed 17d ago), licensed MIT. It adds 54 tokens to every session and 2,199 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to memory-management, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
remember
Review the current conversation and capture valuable knowledge — best practices, coding conventions, architecture decisions, workflows, and user feedback — into persistent memory (AGENTS.md) or reusable skills. Use when the user says: (1) remember this, (2) save what we learned, (3) update memory, (4) capture…
coding-prefs
Read the user's coding preferences from /memory/coding-prefs.md before making non-trivial style decisions, and append new preferences when the user gives durable feedback.
project-wiki
A system for creating and maintaining a project wiki: a set of organized documents that explain a software project's plans, rules, references, and progress.
mindos-zh
A local knowledge-base assistant for storing and finding decisions, meeting notes, procedures, troubleshooting lessons, and preferences across conversations and coding agents. It works only with the MindOS knowledge base.
mindos
MindOS: local knowledge assistant & shared KB. Keeps decisions, notes, SOPs, debugging lessons, research findings, preferences across sessions/agents. Core: save notes, search KB, organize files, run workflows, review, append CSV, hand off context, distill lessons. NOT for app source or paths outside KB. Triggers…
mindos-max
MindOS: local knowledge assistant & global memory layer. Keeps decisions, notes, SOPs, debugging lessons, architecture choices, research findings, preferences, conversation summaries for all connected agents. PROACTIVE: (1) search MindOS first for past context, (2) offer to save after valuable work, (3) persist key…