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 DeepLink-org/probing --skill memory_leakgit clone --depth 1 https://github.com/DeepLink-org/probingWrote 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/deeplink-org/probing/memory_leak)<a href="https://agentmods.dev/skills/deeplink-org/probing/memory_leak"><img src="https://agentmods.dev/badge/skills/deeplink-org/probing/memory_leak/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/deeplink-org/probing/memory_leak"><img src="https://agentmods.dev/badge/skills/deeplink-org/probing/memory_leak.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 | $0.00014 | $0.00277 |
| Opus 5.5 | $0.00006 | $0.00111 |
| Sonnet 5.5 | $0.00003 | $0.00055 |
| Haiku 4.5 | $0.00001 | $0.00028 |
Grade A, and why
memory_leak 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.
What it actually says
GPU memory leak detection
检测 python.torch_trace 中 allocated 是否随 step 单调上涨， 并结合 gpu.utilization 看设备级显存趋势。
Parameters
min_steps(integer, default10): Minimum steps required for trend analysisstep_skip(integer, default2): Skip first N steps (discovery / warmup)
Related skills
- 某模块 delta 大 → 检查是否 cache 了 tensor / 未 detach
- 仅 torch_trace 涨而 gpu.utilization 平稳 → 可能是统计口径问题
- Linux OOM → SELECT * FROM process.kmsg WHERE message LIKE '%oom%'
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 31 lines · 14 tokens per session scan A d2826896c720
memory_leak is a skill published in the GitHub repository DeepLink-org/probing (10 stars, last pushed 2d ago), licensed Apache-2.0. It adds 14 tokens to every session and 277 once invoked, about $0.0001 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.
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