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/v0idos/performance-deity/memory-deitynpx skills add v0idOS/performance-deity --skill memory-deitygit clone --depth 1 https://github.com/v0idOS/performance-deityWrote 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/v0idos/performance-deity/memory-deity)<a href="https://agentmods.dev/skills/v0idos/performance-deity/memory-deity"><img src="https://agentmods.dev/badge/skills/v0idos/performance-deity/memory-deity.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 | $0.00000 | $0.00360 |
| Opus 5 | $0.00000 | $0.00180 |
| Sonnet 5 | $0.00000 | $0.00072 |
| Haiku 4.5 | $0.00000 | $0.00036 |
Grade A, and why
memory-deity scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Memory Deity: The Leak Hunter
Description
This skill enforces a rigorous approach to tracking down and eliminating memory leaks and excessive garbage collection (GC) pauses. Do not guess where the leak is; prove it with memory profiling.
Triggers
Activate when the user mentions:
- "memory leak"
- "high RAM usage"
- "out of memory" or "OOM"
- "garbage collection"
- Or explicitly runs
/plugin performance-deity:memory
Core Directives
Phase 1: Isolation
- Identify the target code suspected of leaking memory.
- Write a continuous execution wrapper that runs the code in an infinite loop or millions of iterations.
Phase 2: Instrumentation
- Inject memory tracking into the wrapper:
- Node.js: Use
process.memoryUsage().heapUsedbefore and after. - Python: Use
tracemalloc. - PowerShell: Use
[System.GC]::GetTotalMemory($false).
- Node.js: Use
- Run the wrapper and plot the memory delta. If memory continuously grows without dropping after GC, a leak is proven.
Phase 3: Excision
- Identify the uncollected references (e.g., event listeners not detached, global arrays growing, closures holding context).
- Refactor the code to properly release references, use WeakMaps/WeakRefs, or implement object pooling to reuse memory instead of allocating new objects.
Phase 4: Proof
- Re-run the instrumented wrapper.
- Present a report showing:
- Original Memory Growth (e.g., +50MB / 10k ops)
- New Memory Growth (e.g., +0MB / 10k ops)
- Explanation of the fix.
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 · 37 lines · 0 tokens per session scan A 6cad68ab846f
memory-deity is a skill published in the GitHub repository v0idOS/performance-deity (2 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 360 tokens. 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.
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