isa-instruction-lookup

isa-instruction-lookup is a skill for Claude Code from sisibeloved/cpython-optimize-skill. It costs 135 tokens per session (1,288 once invoked), scanned A, original, MIT.

A reference tool for official ARM A64 and x86-64 processor instruction specifications. These specifications describe instruction encoding, syntax, behavior, and hardware requirements.

In plain words
What is it for?
Use it when reading JIT output, checking disassembly, choosing replacement instructions, comparing ARM and x86 instructions, or verifying processor feature support.
Why use it?
It reduces the risk of designing machine-code optimizations from incorrect or incomplete instruction details.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the cpython-optimize-skill plugin — 35 skills, 2 hooks, 1 MCP server shipped together

Good fit Use it when reading JIT output, checking disassembly, choosing replacement instructions, comparing ARM and x86 instructions, or verifying processor feature support.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup
Install

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.

Any agent
npx skills add sisibeloved/cpython-optimize-skill --skill isa-instruction-lookup
Clone the repo
git clone --depth 1 https://github.com/sisibeloved/cpython-optimize-skill

Made for: Claude Code.

Or install cpython-optimize-skill, the plugin that ships this one along with the rest of its 35 skills, 2 hooks, 1 MCP server.

Wrote 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.

agentmods badge for isa-instruction-lookup

README.md
[![agentmods](https://agentmods.dev/badge/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup/github.svg)](https://agentmods.dev/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup)
Your own site
<a href="https://agentmods.dev/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup"><img src="https://agentmods.dev/badge/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup/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.

agentmods 80×15 button for isa-instruction-lookup

Your own site · 80×15
<a href="https://agentmods.dev/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup"><img src="https://agentmods.dev/badge/skills/sisibeloved/cpython-optimize-skill/isa-instruction-lookup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,288 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00135 $0.01288
Opus 5 $0.00068 $0.00644
Sonnet 5 $0.00027 $0.00258
Haiku 4.5 $0.00014 $0.00129

Measured 8d ago against content hash 57c81fc70bb6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

isa-instruction-lookup 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 8d 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.

plugins/cpython-optimize-skill/skills/isa-instruction-lookup/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ISA Instruction Lookup

查询官方 ISA 规格的统一入口。数据只来自权威来源,经离线 ingest 进入 mcp/isa-reference/data/isa.db,通过 MCP 工具只读查询。

当前库覆盖

  • a64(2259 条,ARM-official XML 2026-06):编码/伪代码/FEAT_xxx 全量
  • x86_64(854 条 = Intel-SDM 771 + AMD-APM 特有 83):opcode 表/伪代码/ CPUID:XXX feature(Intel opcode 表 feature 列 + AMD 页内声明双源,约 1700 行)

何时用

  • 读 JIT/反汇编机器码,要确认某助记符的编码、操作数约束或执行语义
  • codegen 优化:找"做某件事"的指令(如条件选择、位反转、批量内存操作)
  • 判断某指令依赖哪个 FEAT_xxx,目标环境(Kunpeng 等)是否实现
  • 跨平台比对:某 A64 指令在 x86 侧的等价候选(或反向)

三层检索流程

按顺序降级,不要跳层:

  1. 意图映射:查询是优化意图(如"用条件选择取代比较和分支")时,先读 references/optimization-intent-map.md 把意图翻译成功能术语(→ "conditional select")。 已知助记符(如反汇编输出里的 CSEL)跳过此层。
  2. 功能检索find_instruction_by_function(description="conditional select") — FTS 匹配 brief/authored,返回候选列表。描述用英文功能术语。 候选检索跨 category/feature 不设限——优化替换经常跨执行域(base 需求 用 SIMD 指令满足、SVE 替换 base 序列),分类和 feature 只是可用性维度, 不是过滤条件。
  3. 精确查询与查证:候选定位后 lookup_instruction(mnemonic, verbose=True)查证主体与必做动作
    • operation_pseudocode——方案的每条语义假设("无条件写 Rd")逐行比对, 不一致即方案错误;
    • asm_templates——合法语法形态,写汇编/lowering 的依据;
    • operand_docs——操作数约束(宽度限制、内存源语义、编码位要求), 编码陷阱在这里暴露;
    • bitfields——具体编码位。 category 只用于同名消歧,features 只用于环境部署判定——这两者不是 语义查证的输出,只回答"是 base 类/无 feature 依赖"不构成查证。

跨平台等价:find_equivalent_instruction(mnemonic, from_arch, to_arch)。返回的是 词面候选(如 CMOVcc 的 a64 侧候选会混入 MOV 族)——先查 references/optimization-intent-map.md 的跨平台族映射(权威答案),机器候选用于 发现遗漏,精确等价性必须比对双方 operation_pseudocode 后下结论

环境可用性判定

  1. 环境侧 feature 列表:a64 来自 /proc/cpuinfoID_AA64* 系统寄存器解读 (环境审计走 cinderx-env-validate);x86_64 来自 CPUID flag 名(如 BMI2SSE2),传入时带 CPUID: 前缀或由工具直接匹配 flag 名。
  2. filter_by_environment(env_features=[...], arch=...) 返回 available / conditional / unavailable。conditional 表示该指令可用性还依赖 操作数取值(如 sz 字段),必须读该指令 bitfields 后人工判读。
  3. 同名指令跨执行域变体(ABS 有 base/SIMD/SVE 三版)靠返回的 category 消歧。

硬规则

  • 库内 source_authority 只允许官方来源白名单,规则见 references/source-authority-policy.md。非官方来源数据一律不入库。
  • 指令的微架构性能(吞吐/延迟)不在本库——ISA 手册不含性能数据, 性能结论走 perf/TRM 路径(cinderx-isa-microarch-compare)。
  • 引用指令规格时必须带上来源(source_doc + page_start),便于回溯。
  • 数据更新(新版本手册/新架构)只跑 mcp/isa-reference/scripts/ingest_*.py 重建,不手改 isa.db。

Read the full file on GitHub · 70 lines

Files

What ships with it

2 files 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.

Changes

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.

  1. 8d ago First seen · 70 lines · 135 tokens per session scan A 57c81fc70bb6

Subscribe to this mod's changes

isa-instruction-lookup is a skill published in the GitHub repository sisibeloved/cpython-optimize-skill (2 stars, last pushed 10d ago), licensed MIT. It adds 135 tokens to every session and 1,288 once invoked, about $0.0007 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.

Related

Other skills, from other repositories

gke-compute-classes

Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…

google/skills · 83 tokens

jetson-diagnostic

Read-only Jetson health snapshot for identity, memory, GPU, thermal, power, storage, services, and top processes.

NVIDIA/skills · 30 tokens

doca-socket-relay

Use this skill when the operator is driving the DOCA Socket Relay to bridge a socket-oriented host application onto a BlueField DPU peer without rewriting it — picking the deployment shape (in-process, sidecar, or BlueField service container), configuring the host-side socket and the DPU-side forwarding endpoint…

NVIDIA/skills · 236 tokens

offensive-z-wave

Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting…

SnailSploit/Claude-Red · 113 tokens

hsb-flash

Flash the FPGA on an HSB board connected to an NVIDIA devkit. Supports HSB Lattice boards (FPGA versions 2407, 2412, 2507, 2510) and Leopard Imaging VB1940 "all-in-one" cameras (FPGA versions 2507, 2510). Uses release-specific YAML manifests and board-type-specific program commands. Lattice and VB1940 commands must…

NVIDIA/skills · 94 tokens

jetson-validate-image

Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.

NVIDIA/skills · 50 tokens