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 G1Joshi/Agent-Skills --skill assemblygit clone --depth 1 https://github.com/G1Joshi/Agent-SkillsWrote 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/g1joshi/agent-skills/assembly)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/assembly"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/assembly/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/g1joshi/agent-skills/assembly"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/assembly.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 | $0.00041 | $0.01330 |
| Opus 5.5 | $0.00016 | $0.00532 |
| Sonnet 5.5 | $0.00008 | $0.00266 |
| Haiku 4.5 | $0.00004 | $0.00133 |
Grade A, and why
assembly 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 22d 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.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assembly
Low-level language with a very strong correspondence between the instruction in the language and the architecture's machine code instructions.
When to Use
- Low-Level Hardware & OS Kernel Programming: Writing bootloaders, CPU context switches, interrupt handlers, and page table setup.
- Micro-Architectural SIMD Vector Optimization: Crafting hand-tuned AVX-512, Neon, or SSE assembly kernels for game physics and matrix multiplication.
- Reverse Engineering & Exploit Analysis: Disassembling binary executables to audit firmware, analyze malware, or debug compiler crashes.
- Embedded Bare-Metal Firmware: Direct CPU register manipulation on microcontrollers without operating system abstractions.
Quick Start
section .data
msg db "Hello, World!", 0xa
len equ $ - msg
section .text
global _start
_start:
mov rax, 1 ; write syscall
mov rdi, 1 ; stdout
mov rsi, msg ; buffer
mov rdx, len ; length
syscall
mov rax, 60 ; exit syscall
xor rdi, rdi ; exit code 0
syscall
Core Concepts
CPU Registers & Memory Addressing Modes (x86-64 / ARM64)
Registers hold immediate state for execution; addressing modes compute memory operands:
; x86-64 NASM: Moving data and base-index-scale-displacement addressing
mov rax, 42 ; Immediate to register
mov rbx, [rsp + 16] ; Base + displacement
mov rcx, [rdi + rsi * 8 + 32] ; Base + index * scale + displacement
The System V AMD64 Calling Convention
Governs how functions receive parameters and return values in Linux and macOS:
| Register | Argument Role |
|---|---|
rdi |
1st function argument |
rsi |
2nd function argument |
rdx |
3rd function argument |
rcx |
4th function argument |
r8, r9 |
5th and 6th function arguments |
rax |
Function return value (and syscall number) |
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.
- 22d ago Changed 5b781ac3df57
- 26d ago Changed · +73 lines · +23 tokens per session fe2095e4de6b
- 1mo ago First seen · 69 lines · 18 tokens per session scan A fa92e15adc2e
assembly is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 22d ago), licensed MIT. It adds 41 tokens to every session and 1,330 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 2026-09-03.
Other skills, from other repositories
esp32-arduino-embedded-c
Guidance for production-grade ESP32 Arduino and Embedded C/C++ development. Use when building firmware for ESP32, ESP32-S3, or ESP32-C3 microcontrollers, optimizing FreeRTOS tasks, managing SRAM/PSRAM, writing ISR-safe code, or handling dual-core concurrency and hardware peripherals.
raspberry-pi-rust-embedded
Production-grade embedded Rust guidelines for Raspberry Pi (bare-metal nostd and Linux embedded std/rppal/embedded-hal). Use when developing low-latency hardware control apps, embedded Rust drivers, Linux GPIO/SPI/I2C/UART software, real-time interrupt handlers, and memory-safe hardware abstractions.
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…
observability-and-instrumentation
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
performance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.