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 mohitmishra786/low-level-dev-skills --skill device-treegit clone --depth 1 https://github.com/mohitmishra786/low-level-dev-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/mohitmishra786/low-level-dev-skills/device-tree)<a href="https://agentmods.dev/skills/mohitmishra786/low-level-dev-skills/device-tree"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/device-tree/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/mohitmishra786/low-level-dev-skills/device-tree"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/device-tree.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 | $0.00934 |
| Opus 5 | $0.00030 | $0.00467 |
| Sonnet 5 | $0.00012 | $0.00187 |
| Haiku 4.5 | $0.00006 | $0.00093 |
Grade A, and why
device-tree 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.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Device Tree (Devicetree)
Purpose
Guide agents through Linux device tree source (DTS): syntax, bindings, phandles, overlays, and how the kernel OF (Open Firmware) layer parses hardware description into platform_device instances.
When to Use
- Platform driver not probing — DT mismatch
- Adding a new board
.dtsor fragment overlay - Understanding
compatible,reg,interrupts,clocksproperties - Cross-checking hardware with
skills/kernel-dev/platform-device-model
Workflow
1. DTS structure
/dts-v1/;
#include "soc.dtsi"
/ {
model = "My Board";
compatible = "vendor,my-board", "vendor,soc-family";
soc {
uart0: serial@40011000 {
compatible = "vendor,uart";
reg = <0x40011000 0x400>;
interrupts = <GIC_SPI 38 IRQ_TYPE_LEVEL_HIGH>;
clocks = <&clk_uart0>;
status = "okay";
};
};
};
2. Key properties
| Property | Meaning |
|---|---|
compatible |
Driver match string (most specific first) |
reg |
MMIO address + length ( #address-cells, #size-cells ) |
interrupts |
IRQ specifier (interrupt parent defines cells) |
clocks / clock-names |
phandle to clock provider |
status |
"disabled" skips probe |
3. Phandles
clk_uart0: clock-uart {
compatible = "vendor,clk";
#clock-cells = <0>;
};
serial@... {
clocks = <&clk_uart0>; /* phandle reference */
};
4. Kernel parsing
OF core reads DTB at boot
├── of_platform_populate() creates platform_devices
└── driver `.of_match_table` matches `compatible`
static const struct of_device_id my_of_match[] = {
{ .compatible = "vendor,uart" },
{ }
};
MODULE_DEVICE_TABLE(of, my_of_match);
5. Compile and inspect
dtc -I dts -O dtb -o board.dtb board.dts
dtc -I fs -O dts /proc/device-tree 2>/dev/null | less
ls /sys/firmware/devicetree/base/
Bindings live at devicetree.org — always cite binding name in commits.
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.
- 8d ago First seen · 122 lines · 61 tokens per session scan A 4c683b215ea5
device-tree is a skill published in the GitHub repository mohitmishra786/low-level-dev-skills (203 stars, last pushed 2mo ago), licensed MIT. It adds 61 tokens to every session and 934 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
gke-ai-troubleshooting-tpu-dynamic-slices-monitoring
Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use…
gke-ai-troubleshooting-tpu-vbar-oom
Diagnoses and prevents vbarcontrolagent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbarcontrolagent crashes, memory cgroup OOMs in serial console…
doca-flow
Build and debug DOCA Flow applications on supported NVIDIA NICs/DPUs: define match/action pipes, initialize ports and representors, choose forwarding targets, validate pipes before hardware programming, read counters, match the Flow version to the installed DOCA release, and diagnose Flow API errors. Trigger on DOCA…
diagnose-driver-install
Diagnose NVIDIA driver installation failures on DeepOps-managed nodes — nvidia-smi errors, "No devices were found", DKMS build failures, or GPU pods crash-looping. Use before reinstalling anything.
ipfabric
Skill: /ipfabric MCP Server: ipfabric-mcp (remote HTTP via mcp-remote) Tools: 10 (health, path lookups, diagrams, API discovery).
gtrace-path-analysis
Network path tracing and monitoring — traceroute with MPLS/ECMP/NAT detection, continuous MTR monitoring, and distributed GlobalPing probes from 500+ worldwide locations. Use when tracing the path to a destination, diagnosing slow network routes, detecting MPLS or ECMP load balancing, running MTR for intermittent…