Borrowing it
Nothing to install: this file belongs to albumentations-team/albucore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/albumentations-team/albucore/main/.codex/skills/performance-optimization/SKILL.mdgit clone --depth 1 https://github.com/albumentations-team/albucoreWrote 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/albumentations-team/albucore/performance-optimization)<a href="https://agentmods.dev/skills/albumentations-team/albucore/performance-optimization"><img src="https://agentmods.dev/badge/skills/albumentations-team/albucore/performance-optimization/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/albumentations-team/albucore/performance-optimization"><img src="https://agentmods.dev/badge/skills/albumentations-team/albucore/performance-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00814 |
| Opus 5.5 | $0.00024 | $0.00326 |
| Sonnet 5.5 | $0.00012 | $0.00163 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
performance-optimization 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 yesterday.
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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimization
Benchmark Albucore changes through Core public operations only, including their Core-owned dispatch, conversions, allocations and memory use. AX functional/transform/Compose performance checks require an explicit user request and are not an automatic gate for Core changes. Follow the benchmark scope in the canonical guide below.
Read ../../../docs/performance-optimization.md completely before inspecting or changing runtime code. That document
is the canonical shared workflow for Albucore and AlbumentationsX.
For final correctness, speed, and memory acceptance, use Python 3.11 with the latest stable dependencies available
for Python 3.11 and the target platform. The current recorded profile uses PyTorch 2.15.0, including the CPU wheel on
Linux. Check resolved versions and imported source paths; a newer Python or stale uv.lock is not a substitute.
When the sibling AlbumentationsX checkout is available, verify the fallback copy with
cmp -s docs/performance-optimization.md ../AlbumentationsX/.codex/skills/performance-optimization/references/performance-optimization.md.
A mismatch blocks completion.
Workflow
- Establish correctness and public-router performance baselines before editing.
- Run every stage of the canonical optimization pass. Do not stop after finding the first plausible improvement.
- Treat delete-first, vectorization, LUT, random generation,
bincount, backend selection, routing thresholds, and explicit output aliasing as benchmark questions. Internal mutation is limited to owned working buffers. - Compare the complete public path, including dispatch, dtype conversion, contiguity, allocation, clipping, and shape repair.
- Read
../albucore-benchmarks/SKILL.mdcompletely before measuring. Extend the matrix along the dimension that controls the candidate. - Add or preserve correctness tests for every accepted route and its boundary cases.
- Update benchmark evidence and route documentation when public routing changes.
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.
- yesterday Changed · +11 lines a4a2c791ff47
- 4d ago Changed · +4 lines · +1 tokens per session 116240d5b69c
- 2mo ago First seen · 56 lines · 60 tokens per session scan A 42a7da0dfd99
performance-optimization is a skill published in the GitHub repository albumentations-team/albucore (124 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 814 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.
performance-optimization compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| performance-optimizationalbumentations-team/albucore | Skill | 124 | yesterday | MIT | A | 61 | Codex |
| smart-explorethedotmack/claude-mem | Skill | 114k | yesterday | Apache-2.0 | A | 41 | Claude Code |
| developing-with-streamlitstreamlit/streamlit | Skill | 46k | yesterday | Apache-2.0 | A | 146 | Claude Code |
| code-taskopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 322 | Claude Code, Codex |
| potpie-clipotpie-ai/potpie | Skill | 5.8k | 7d ago | Apache-2.0 | A | 60 | Codex |
| stack-trace-js-probeopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 43 | Claude Code |
| potpie-debug-memorypotpie-ai/potpie | Skill | 5.8k | 7d ago | Apache-2.0 | A | 41 | Claude Code, Codex |