Agent skill

Jlink

J-Link 下载与在线调试工具，用于探测设备、烧录固件、读写内存、查看寄存器、复位目标、读取 RTT/SWO 日志，以及在线调试（暂停/恢复/单步/断点运行/调用栈/变量查看）。

MITAuto-check passed

Install Jlink

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/jlink .claude/skills/jlink && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .claude/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/zhinkgit/embeddedskills/tree/main/jlink

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/jlink .agents/skills/jlink && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .agents/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/jlink .cursor/skills/jlink && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .cursor/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/zhinkgit/embeddedskills.git --path jlink

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/jlink .gemini/skills/jlink && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .gemini/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .github/skills && cp -r skills-src/jlink .github/skills/jlink && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .github/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add zhinkgit/embeddedskills --skill jlink -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install zhinkgit/embeddedskills jlink --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zhinkgit/embeddedskills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/jlink .opencode/skills/jlink && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "jlink" agent skill from https://github.com/zhinkgit/embeddedskills/tree/main/jlink into .opencode/skills/jlink/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jlink", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: jlink
GitHub stars: 734
Token cost: ~2k tokens
SKILL.md length: 313 words
Files: 13 (incl. scripts, references)
Skills in repo: 12
Repo updated: Sep 3, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Works in 10 steps: 读取 skill/config.json，确认 exe 路径有效 → 读取 .embeddedskills/config.json… → 读取 .embeddedskills/state.json 获取历史状态 → …
SKILL.md covers 配置, 子命令, 执行流程 and 脚本调用, plus 4 more sections
Runs Python scripts from its folder; calls python

What it does

Jlink is an agent skill from zhinkgit/embeddedskills. J-Link 下载与在线调试工具，用于探测设备、烧录固件、读写内存、查看寄存器、复位目标、读取 RTT/SWO 日志，以及在线调试（暂停/恢复/单步/断点运行/调用栈/变量查看）。当用户提到 J-Link、JLink、RTT、烧录固件、写内存、读内存、寄存器查看、目标复位、探针连通性检查、在线调试、单步、断点、调用栈时自动触发，也兼容 /jlink 显式调用。即使用户只是说"烧录一下"、"看看 RTT 输出"或"调试一下"，只要上下文涉及 J-Link 探针就应触发此 skill。

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `README.md`, `config.example.json` and `references/common_devices.md`).

The repository describes itself as: An open-source collection of embedded development and debugging skills for Claude Code, Copilot, TRAE, and other AI coding assistants that support the Skill protocol. Once… The licence is MIT.

Example prompts

“看看 RTT 输出”
“/jlink”

Requirements

Python 3

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

读取 skill/config.json，确认 exe 路径有效
读取 .embeddedskills/config.json 获取工程级配置（device/interface/speed）
读取 .embeddedskills/state.json 获取历史状态
参数解析优先级：CLI 显式参数 > .embeddedskills/config.json（工程级）> skill/config.json（环境级）> .embeddedskills/state.json > 默认值/报错
若当前动作需要 device 且仍为空，直接要求用户补充，绝不猜测
多探针场景未指定 serial_no 时，列出探针让用户选择，不自动选择
按 operation_mode 决定是否需要确认后执行
使用模板生成临时 .jlink 命令文件，调用 JLink.exe 时带 -NoGui 1 -ExitOnError 1 -AutoConnect 1
解析输出和返回码，返回结构化结果
成功执行后，将确认过的 device/interface/speed 写回 .embeddedskills/config.json

What it can do on your machine

Read from SKILL.md and the folder at commit 536c1f9. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 6 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jlink loads about 2k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 313 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~63
When it runs · the whole SKILL.md, loaded when a task matches: ~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from zhinkgit/embeddedskills at commit 536c1f9, republished under its MIT licence (© zhinkgit). 313 words, ~1,976 tokens.

Download SKILL.mdSave it as .claude/skills/jlink/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.

name: jlink
description: J-Link 下载与在线调试工具，用于探测设备、烧录固件、读写内存、查看寄存器、复位目标、读取 RTT/SWO 日志，以及在线调试（暂停/恢复/单步/断点运行/调用栈/变量查看）。当用户提到 J-Link、JLink、RTT、烧录固件、写内存、读内存、寄存器查看、目标复位、探针连通性检查、在线调试、单步、断点、调用栈时自动触发，也兼容 /jlink 显式调用。即使用户只是说"烧录一下"、"看看 RTT 输出"或"调试一下"，只要上下文涉及 J-Link 探针就应触发此 skill。
argument-hint: [info|flash|read-mem|write-mem|regs|reset|halt|go|step|run-to|rtt|swo|gdb] ...

J-Link 下载与在线调试

本 skill 提供 J-Link 探针的设备探测、固件烧录、内存读写、寄存器查看、目标复位、RTT 日志读取，以及轻量在线调试和 GDB 源码级调试能力。

配置

环境级配置（skill/config.json）

skill 目录下的 config.json 包含环境级配置（工具路径、端口号等），首次使用前确认 exe 路径正确：

json

{
  "exe": "C:\\Program Files\\SEGGER\\JLink\\JLink.exe",
  "gdbserver_exe": "C:\\Program Files\\SEGGER\\JLink\\JLinkGDBServerCL.exe",
  "rtt_exe": "C:\\Program Files\\SEGGER\\JLink\\JLinkRTTClient.exe",
  "gdb_exe": "C:\\Program Files\\Arm\\GNU Toolchain mingw-w64-x86_64-arm-none-eabi\\bin\\arm-none-eabi-gdb.exe",
  "serial_no": "",
  "rtt_telnet_port": 0,
  "swo_command": [],
  "operation_mode": 1
}

exe：JLink.exe 完整路径（必填）
gdbserver_exe：JLinkGDBServerCL.exe 路径，RTT 和 GDB 调试需要
rtt_exe：JLinkRTTClient.exe 路径
gdb_exe：arm-none-eabi-gdb 路径，GDB 源码级调试需要
serial_no：默认探针序列号，多探针场景下使用
rtt_telnet_port：RTT 端口，0 表示使用工具默认值
swo_command：可选，完整 SWO viewer 命令数组，供 jlink_swo.py 包装
operation_mode：1 直接执行 / 2 输出风险摘要但不阻塞 / 3 执行前确认

工程级配置（.embeddedskills/config.json）

设备参数（device/interface/speed）统一在工作区的 .embeddedskills/config.json 中管理：

json

{
  "jlink": {
    "device": "STM32F407VG",
    "interface": "SWD",
    "speed": "4000"
  }
}

device：芯片型号（如 STM32F407VG、GD32F470ZG）
interface：调试接口，SWD 或 JTAG，默认 SWD
speed：调试速率 kHz，默认 4000

参数解析优先级：CLI 显式参数 > .embeddedskills/config.json（工程级）> skill/config.json（环境级）> .embeddedskills/state.json > 默认值/报错

成功执行后，确认过的 device/interface/speed 会自动写回工程配置。

子命令

基础操作

子命令	用途	风险
`info`	探测探针与目标连通性	低
`flash`	烧录固件（.hex / .bin / .elf）	高
`read-mem`	读取内存区域	低
`write-mem`	写入内存	高
`regs`	查看 CPU 寄存器	低
`reset`	复位目标芯片	高
`rtt`	读取 RTT 日志输出	低
`swo`	包装外部 SWO viewer 为统一事件流	低

在线调试（JLink Commander）

子命令	用途	风险
`halt`	暂停 CPU，返回寄存器状态	低
`go`	恢复 CPU 运行	低
`step`	单步执行（支持指定步数），返回执行的指令和寄存器	低
`run-to`	设置断点并运行，等待命中后返回状态	低

GDB 源码级调试

子命令	用途	依赖
`gdb backtrace/locals`	查看调用栈和局部变量	arm-none-eabi-gdb
`gdb break/continue/next/step/finish/until`	one-shot 控制执行流	arm-none-eabi-gdb
`gdb frame/print/watch/disassemble/threads/crash-report`	one-shot 源码级诊断	arm-none-eabi-gdb

执行流程

读取 skill/config.json，确认 exe 路径有效
读取 .embeddedskills/config.json 获取工程级配置（device/interface/speed）
读取 .embeddedskills/state.json 获取历史状态
参数解析优先级：CLI 显式参数 > .embeddedskills/config.json（工程级）> skill/config.json（环境级）> .embeddedskills/state.json > 默认值/报错
若当前动作需要 device 且仍为空，直接要求用户补充，绝不猜测
多探针场景未指定 serial_no 时，列出探针让用户选择，不自动选择
按 operation_mode 决定是否需要确认后执行
使用模板生成临时 .jlink 命令文件，调用 JLink.exe 时带 -NoGui 1 -ExitOnError 1 -AutoConnect 1
解析输出和返回码，返回结构化结果
成功执行后，将确认过的 device/interface/speed 写回 .embeddedskills/config.json

脚本调用

skill 目录下有四个 Python 脚本，使用标准库实现，无额外依赖。

jlink_exec.py — 基础操作 + 轻量调试

bash

# 探测连通性
python <skill-dir>/scripts/jlink_exec.py info --device GD32F470ZG --json

# 烧录固件
python <skill-dir>/scripts/jlink_exec.py flash --file build/app.hex --device GD32F470ZG --json

# 烧录 .bin（必须提供地址）
python <skill-dir>/scripts/jlink_exec.py flash --file build/app.bin --device GD32F470ZG --address 0x08000000 --json

# 读取内存
python <skill-dir>/scripts/jlink_exec.py read-mem --address 0x08000000 --length 256 --device GD32F470ZG --json

# 写入内存
python <skill-dir>/scripts/jlink_exec.py write-mem --address 0x20000000 --value 0x12345678 --device GD32F470ZG --json

# 查看寄存器
python <skill-dir>/scripts/jlink_exec.py regs --device GD32F470ZG --json

# 复位目标
python <skill-dir>/scripts/jlink_exec.py reset --device GD32F470ZG --json

# 暂停 CPU
python <skill-dir>/scripts/jlink_exec.py halt --device GD32F470ZG --json

# 恢复运行
python <skill-dir>/scripts/jlink_exec.py go --device GD32F470ZG --json

# 单步执行（3 步）
python <skill-dir>/scripts/jlink_exec.py step --device GD32F470ZG --count 3 --json

# 运行到断点地址
python <skill-dir>/scripts/jlink_exec.py run-to --device GD32F470ZG --address 0x08001234 --timeout-ms 3000 --json

通用可选参数：--interface SWD|JTAG、--speed 4000、--serial-no <序列号>、--exe <JLink.exe路径>

jlink_rtt.py — RTT 日志读取

bash

python <skill-dir>/scripts/jlink_rtt.py --device GD32F470ZG --json

可选参数：--serial-no、--channel、--encoding、--rtt-port、--gdbserver-exe <路径>、--rtt-exe <路径>

RTT 工作原理：脚本先通过 JLinkGDBServerCL.exe 建立调试连接，再启动 JLinkRTTClient.exe 读取 RTT 数据。--json 模式输出 JSON Lines。

jlink_swo.py — SWO 事件流包装

bash

# 使用 config.json 里的 swo_command
python <skill-dir>/scripts/jlink_swo.py --json

# 或显式传入 viewer 命令
python <skill-dir>/scripts/jlink_swo.py \
  --viewer-cmd JLinkSWOViewerCL.exe -device GD32F470ZG -itf SWD -speed 4000 \
  --json

jlink_swo.py 不直接实现 SWO 协议，而是把外部 viewer 的 stdout/stderr 统一包装成 JSON Lines，便于上层 workflow 或 AI 继续消费。

jlink_gdb.py — GDB 源码级调试（需要 arm-none-eabi-gdb）

bash

# 执行自定义 GDB 命令序列
python <skill-dir>/scripts/jlink_gdb.py run \
  --gdbserver-exe <路径> --gdb-exe <arm-none-eabi-gdb路径> \
  --device GD32F470ZG --elf build/app.elf \
  --commands "break main" "continue" "backtrace" "info locals" --json

# 快捷：获取调用栈
python <skill-dir>/scripts/jlink_gdb.py backtrace \
  --gdbserver-exe <路径> --gdb-exe <路径> \
  --device GD32F470ZG --elf build/app.elf --json

# 快捷：查看局部变量
python <skill-dir>/scripts/jlink_gdb.py locals \
  --gdbserver-exe <路径> --gdb-exe <路径> \
  --device GD32F470ZG --elf build/app.elf --json

GDB 调试需要 ELF 文件才能进行源码级调试（断点到函数名、查看变量）。没有 ELF 时仍可使用地址级调试。

输出格式

所有脚本以 JSON 格式返回，基础字段为 status（ok/error）、action、summary、details，并可能附带 context、artifacts、metrics、state、next_actions、timing。流式观测命令使用 JSON Lines，并统一输出 source、channel_type、stream_type。

成功示例：

json

{
  "status": "ok",
  "action": "halt",
  "summary": "已暂停，PC=0x08049ABC",
  "details": {
    "device": "GD32F470ZG",
    "registers": { "PC": "0x08049ABC", "R0": "0x00000004", "..." : "..." }
  }
}

step 示例（包含执行的指令）：

json

{
  "status": "ok",
  "action": "step",
  "summary": "单步3次，PC=0x08049AB4",
  "details": {
    "steps": [
      { "address": "0x08049AB8", "opcode": "80 1B", "instruction": "SUBS R0, R0, R6" },
      { "address": "0x08049ABA", "opcode": "A8 42", "instruction": "CMP R0, R5" },
      { "address": "0x08049ABC", "opcode": "FA D3", "instruction": "BCC #-0x0C" }
    ],
    "registers": { "PC": "0x08049AB4", "..." : "..." }
  }
}

run-to 示例（断点命中）：

json

{
  "status": "ok",
  "action": "run-to",
  "summary": "断点命中 @ 0x08049AB4，PC=0x08049AB4",
  "details": {
    "bp_address": "0x08049AB4",
    "bp_hit": true,
    "registers": { "PC": "0x08049AB4", "..." : "..." }
  }
}

核心规则

不自动猜测 device 芯片型号，缺失时必须询问用户
多探针场景不自动选择探针，必须让用户指定序列号
参数解析优先级为：CLI 显式参数 > .embeddedskills/config.json（工程级）> skill/config.json（环境级）> .embeddedskills/state.json > 默认值/报错
.bin 文件必须显式提供烧录地址，缺失时报错
连接失败时给出排查建议（检查连线、供电、接口类型、速度），不自动尝试更激进参数
烧录、写内存、复位在参数完整且用户意图明确时直接执行
run-to 的断点在单次 JLink 会话内完成设置和清除，不存在跨会话 handle 问题
结果回显中始终包含目标芯片、接口类型和执行动作
产物路径（elf/file）不进入工程配置，仍只依赖 state.json
last_flash/last_debug 等运行状态继续写入 state.json

调试典型工作流

快速排查（JLink Commander）

halt → regs → read-mem → step → go

适合查看当前执行位置、寄存器状态、内存值，无需 ELF 和 GDB。

断点调试（JLink Commander）

run-to(address) → regs → read-mem → go

在指定地址设置断点并等待命中，查看此时的状态。

源码级调试（GDB）

gdb run --elf app.elf --commands "break main" "continue" "backtrace" "info locals"

需要 ELF 文件和 arm-none-eabi-gdb，支持函数名断点和变量查看。

参考

遇到芯片型号问题时可查阅 references/common_devices.md。

Files

SKILL.md and 12 other files (scripts, references) in jlink of zhinkgit/embeddedskills.

SKILL.md
README.md
config.example.json
references/common_devices.md
scripts/jlink_exec.py
scripts/jlink_gdb.py
scripts/jlink_gdb_common.py
scripts/jlink_rtt.py
scripts/jlink_runtime.py
scripts/jlink_swo.py
templates/flash.jlink
templates/read_mem.jlink
templates/reset.jlink

Open the folder on GitHubat commit 536c1f9

Compare with similar skills

Jlink next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Jlink compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Jlink this skillzhinkgit/embeddedskills	734	—	~2k	Automated safety check: Pass	MIT	1 mo ago
Internal Linksthedaviddias/Front-End-Checklist	74k	—	~770	Automated safety check: Pass	MIT	2 days ago
External Linksthedaviddias/Front-End-Checklist	74k	—	~773	Automated safety check: Pass	MIT	2 days ago
Invalid Linksthedaviddias/Front-End-Checklist	74k	—	~806	Automated safety check: Pass	MIT	2 days ago
SEO Aeo Internal Linkingsickn33/agentic-awesome-skills	47k	1 repos	~2.3k	Automated safety check: Pass	MIT	today
Link Checkerthedaviddias/Front-End-Checklist	74k	—	~408	Automated safety check: Pass	MIT	2 days ago

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Link Checker
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Questions about Jlink

What does Jlink do?

J-Link 下载与在线调试工具，用于探测设备、烧录固件、读写内存、查看寄存器、复位目标、读取 RTT/SWO 日志，以及在线调试（暂停/恢复/单步/断点运行/调用栈/变量查看）。. Jlink is an agent skill from zhinkgit/embeddedskills.

How do I install Jlink in Claude Code?

Run `npx skills add zhinkgit/embeddedskills --skill jlink -a claude-code`. Or copy the skill folder (jlink in zhinkgit/embeddedskills) into .claude/skills/jlink in your project. Claude Code loads it when a task matches its description.

How do I install Jlink in Codex?

Run `npx skills add zhinkgit/embeddedskills --skill jlink -a codex`. Or copy the skill folder (jlink in zhinkgit/embeddedskills) into .agents/skills/jlink in your project. Codex loads it when a task matches its description.

Can I use Jlink in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zhinkgit/embeddedskills --skill jlink -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jlink, .gemini/skills/jlink, .github/skills/jlink and .opencode/skills/jlink in your project.

What does Jlink need to run?

Going by SKILL.md and its folder, Jlink needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Jlink access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Jlink safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Jlink use?

Jlink is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jlink use?

About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 460 tokens, read only when the agent opens those files.

What are the alternatives to Jlink?

Skills that share tags, products or a category with Jlink: Internal Links (thedaviddias/Front-End-Checklist, 74k stars), External Links (thedaviddias/Front-End-Checklist, 74k stars), Invalid Links (thedaviddias/Front-End-Checklist, 74k stars) and SEO Aeo Internal Linking (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jlink?

zhinkgit (a GitHub user) maintains it in zhinkgit/embeddedskills, which has 734 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 3, 2026.

Source: zhinkgit/embeddedskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Jlink

Facts

At a glance

What it does

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

J-Link 下载与在线调试

配置

环境级配置（skill/config.json）

工程级配置（.embeddedskills/config.json）

子命令

基础操作

在线调试（JLink Commander）

GDB 源码级调试

执行流程

脚本调用

jlink_exec.py — 基础操作 + 轻量调试

jlink_rtt.py — RTT 日志读取

jlink_swo.py — SWO 事件流包装

jlink_gdb.py — GDB 源码级调试（需要 arm-none-eabi-gdb）

输出格式

核心规则

调试典型工作流

快速排查（JLink Commander）

断点调试（JLink Commander）

源码级调试（GDB）

参考

Files

Compare with similar skills

Similar skills

More from zhinkgit/embeddedskills

Questions about Jlink