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/platinoff/poolai/memory-managementnpx skills add platinoff/poolAI --skill memory-managementgit clone --depth 1 https://github.com/platinoff/poolAIWhat 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 | $0.00054 | $0.02206 |
| Opus 5 | $0.00027 | $0.01103 |
| Sonnet 5 | $0.00011 | $0.00441 |
| Haiku 4.5 | $0.00005 | $0.00221 |
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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- memory-management — 97% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 324 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.
- 3d ago First seen · 324 lines · 54 tokens per session scan A ad42fd09cbab
memory-management is a skill published in the GitHub repository platinoff/poolAI (4 stars, last pushed 9d ago), licensed MIT. It adds 54 tokens to every session and 2,206 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
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Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…