Memorywhale
wuisabel-gif/MemWhale
Query and write durable debugging memory recorded by MemoryWhale.
Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp.
Install Embedded Debugger
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debugger --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/embedded-debugger .claude/skills/embedded-debugger && rm -rf skills-srcUse ~/.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/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .claude/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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 install https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debuggerType 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.
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debugger --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/embedded-debugger .agents/skills/embedded-debugger && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .agents/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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.
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debugger --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/embedded-debugger .cursor/skills/embedded-debugger && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .cursor/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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 https://github.com/Adancurusul/embedded-debugger-mcp.git --path skills/embedded-debugger--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debugger --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/embedded-debugger .gemini/skills/embedded-debugger && rm -rf skills-srcUse ~/.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/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .gemini/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debuggerInstalls 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).
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/embedded-debugger .github/skills/embedded-debugger && rm -rf skills-srcUse ~/.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/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .github/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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.
$ npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Adancurusul/embedded-debugger-mcp embedded-debugger --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Adancurusul/embedded-debugger-mcp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/embedded-debugger .opencode/skills/embedded-debugger && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "embedded-debugger" agent skill from https://github.com/Adancurusul/embedded-debugger-mcp/tree/main/skills/embedded-debugger into .opencode/skills/embedded-debugger/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-debugger", 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
embedded-debugger- GitHub stars
- 200
- Token cost
- ~1.4k tokens
- SKILL.md length
- 702 words
- Files
- 3 (incl. references)
- Skills in repo
- 1
- Repo updated
- First seen
- Licence
- MIT
At a glance
Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp.
- Works in 3 steps: If the user has an MCP client… → If the user wants no MCP install, use… → If hardware access is required, confirm…
- Claude Code needs to inspect debug probes
- SKILL.md covers Entry Decision, CLI Workflow, Backends and MCP Workflow, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Embedded Debugger is an agent skill from Adancurusul/embedded-debugger-mcp. Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp. Use when Codex or Claude Code needs to inspect debug probes, validate embedded debugger setup, start the MCP server, guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows, or operate without installing an MCP client by using the CLI plus prompts.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/default-prompt.md`).
It sits in Agent Workflows, covering MCP servers, Embedded systems and Debugging. It works with Model Context Protocol, ESP32 and Rust. The repository describes itself as: MCP server + CLI + Codex/Claude skill for embedded debugging via probe-rs or OpenOCD — ARM Cortex-M, RISC-V, and Xtensa (ESP32), with AI crash diagnosis. The licence is MIT.
When your agent uses it
- Claude Code needs to inspect debug probes
- Validate embedded debugger setup
- Start the MCP server
- Guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows
Example prompts
- “/embedded-debugger”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- If the user has an MCP client configured, start or verify the server
- If the user wants no MCP install, use CLI-first mode
- If hardware access is required, confirm the probe and target are connected
What it can do on your machine
Read from SKILL.md and the folder at commit 7113ae4. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
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
Embedded Debugger loads about 1.4k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 93 tokens; SKILL.md has 702 words of instructions outside code blocks.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from Adancurusul/embedded-debugger-mcp at commit 7113ae4, republished under its MIT licence (© Adancurusul). 702 words, ~1,438 tokens.
Download SKILL.mdSave it as
.claude/skills/embedded-debugger/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- embedded-debugger
- description
- Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp. Use when Codex or Claude Code needs to inspect debug probes, validate embedded debugger setup, start the MCP server, guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows, or operate without installing an MCP client by using the CLI plus prompts.
Embedded Debugger
Use the local embedded-debugger-mcp binary as the source of truth. Prefer CLI
checks first, then MCP tools when an MCP client is available.
Entry Decision
- If the user has an MCP client configured, start or verify the server:
embedded-debugger-mcp serve - If the user wants no MCP install, use CLI-first mode:
embedded-debugger-mcp doctor,embedded-debugger-mcp probes list, andembedded-debugger-mcp skill print-prompt. - If hardware access is required, confirm the probe and target are connected before destructive actions such as flash erase or program.
CLI Workflow
Run these in order and report the exact outcome:
embedded-debugger-mcp doctor
embedded-debugger-mcp probes list
embedded-debugger-mcp config showUse JSON for automation:
embedded-debugger-mcp doctor --json
embedded-debugger-mcp probes list --jsonBackends
One tool set runs over two interchangeable engines, chosen at connect:
backend: "probe-rs"(default) — native probe-rs; supports flash and RTT.backend: "openocd"(experimental) — talks to an already-runningopenocdover its GDB port viaopenocd_address(default127.0.0.1:3333). Use for chips probe-rs does not cover well (e.g. Xtensa ESP32 via openocd-esp32). Memory access and halt/run/step/reset are validated on real ESP32-S3; flash and RTT are not available on this backend. Register reads currently use ARM gdb register numbers, so PC/SP are wrong on Xtensa (known limitation).diagnose_faultandunwind_exceptionare Cortex-M specific and do not apply to Xtensa targets.- Start openocd with
gdb_memory_map disable, otherwise it probes flash on the GDB connect, fails, and REJECTS the connection. Example:openocd -f board/esp32s3-builtin.cfg -c "gdb_memory_map disable".
- Start openocd with
The AI uses the same tools regardless of backend; only connect differs.
MCP Workflow
Use MCP tools for session-based operations:
list_probesconnect(addbackend: "openocd"andopenocd_addressto use OpenOCD)- Read-only checks such as
probe_info,get_status, andread_memory - On a crash or halt, call
diagnose_fault: it reads the Cortex-M SCB fault registers (CFSR/HFSR/MMFAR/BFAR/SHCSR/CPUID) plus PC/SP/LR and returns a compact structured evidence bundle in one call. Halt the target first for meaningful values; reason over the set fault bits yourself. Then callunwind_exceptionwithelf_pathto map the crash to a source line (full DWARF backtrace on probe-rs; faulting PC/LR on OpenOCD). - Mutating operations only after the user confirms target, file path, and risk:
write_memory,flash_erase,flash_program,run_firmware(probe-rs) - RTT operations after firmware is running:
rtt_attach,rtt_channels,rtt_read,rtt_write,rtt_detach(probe-rs) disconnect
Show full SKILL.md (342 more words)Show less
Fetch authoritative info yourself
You are a capable model: prefer fetching ground truth over relying on memorized or hardcoded chip data. This skill points you to sources; it does not embed register tables. In order of authority:
- The target itself (runtime, most authoritative for this exact chip):
registers are self-described by the GDB target description; memory is read
with
read_memory; core identity from CPUID / the connected target. - The firmware ELF (what is actually running): symbols and source lines come
from DWARF — use
unwind_exception(pasself_path) to map addresses tofile:line. - The chip datasheet / reference manual (external, per-chip): for a peripheral
or fault register, find the peripheral's base in the memory-map chapter, add
the register offset, then
read_memory. Search the vendor document for the exact value; do not guess addresses from memory. CMSIS-SVD files are a machine-readable source for register maps. - ARM Cortex-M architecture registers (SCB fault regs, CPUID) are fixed by the
ARM architecture and identical across vendors —
diagnose_faultreads them. They do not exist on non-Cortex-M targets (e.g. Xtensa ESP32).
Do not hardcode or invent register/peripheral addresses. If a value is not recoverable from the target, the ELF, or a cited datasheet, say so.
Know your versions
Behavior and target support depend on tool versions — check them before concluding something is unsupported or broken:
- probe-rs version determines which chips and architectures are supported
(e.g. Xtensa support is comparatively new). Check
embedded-debugger-mcp doctor. - OpenOCD version and fork matter: the Espressif fork (openocd-esp32) is needed
for Xtensa ESP32, and some targets need flags like
gdb_memory_map disable. Checkopenocd --version. - Probe firmware (ST-Link / J-Link) can affect connectivity;
probes listreports the connected probe.
Safety Rules
- Treat flash erase, flash program, memory write, reset, run, and RTT write as mutating hardware operations.
- Prefer read-only discovery before mutation.
- Respect project configuration limits for file paths, file sizes, memory ranges, and flash erase permissions.
- Do not claim hardware success from command text alone; cite the command or MCP tool result that produced the evidence.
Prompt Reference
For a reusable CLI+Skill prompt, read
references/default-prompt.md.
© Adancurusul, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (references) in skills/embedded-debugger of Adancurusul/embedded-debugger-mcp.
- SKILL.md
- agents/openai.yaml
- references/default-prompt.md
Open the folder on GitHubat commit 7113ae4
Compare with similar skills
Embedded Debugger 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Embedded Debugger this skillAdancurusul/embedded-debugger-mcp | 200 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Memorywhalewuisabel-gif/MemWhale | 154 | — | ~765 | Automated safety check: Pass | MIT | |
| Memorywhale Evidencewuisabel-gif/MemWhale | 154 | — | ~459 | Automated safety check: Pass | MIT | |
| SlintMoosync/Moosync | 259 | — | ~2.4k | Automated safety check: Pass | GPL-3.0 | |
| Memorywhale Debuggingwuisabel-gif/MemWhale | 154 | — | ~370 | Automated safety check: Pass | MIT | |
| Local DevSmilyOrg/photofield | 608 | — | ~2.4k | Automated safety check: Pass | MIT |
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Works with
Categories
Questions about Embedded Debugger
What does Embedded Debugger do?
Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp. Embedded Debugger is an agent skill from Adancurusul/embedded-debugger-mcp. Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp.
When should I use Embedded Debugger?
Embedded Debugger fits situations like: Claude Code needs to inspect debug probes; validate embedded debugger setup; start the MCP server; guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows.
How do I install Embedded Debugger in Claude Code?
Run `npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a claude-code`. Or copy the skill folder (skills/embedded-debugger in Adancurusul/embedded-debugger-mcp) into .claude/skills/embedded-debugger in your project. Claude Code loads it when a task matches its description.
How do I install Embedded Debugger in Codex?
Run `npx skills add Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a codex`. Or copy the skill folder (skills/embedded-debugger in Adancurusul/embedded-debugger-mcp) into .agents/skills/embedded-debugger in your project. Codex loads it when a task matches its description.
Can I use Embedded Debugger 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 Adancurusul/embedded-debugger-mcp --skill embedded-debugger -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/embedded-debugger, .gemini/skills/embedded-debugger, .github/skills/embedded-debugger and .opencode/skills/embedded-debugger in your project.
What does Embedded Debugger need to run?
SKILL.md names no scripts, command-line tools or credentials: Embedded Debugger is instructions for the agent only.
Does Embedded Debugger 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 Embedded Debugger 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. Review the folder before installing.
What licence does Embedded Debugger use?
Embedded Debugger 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 Embedded Debugger use?
About 1.4k tokens (SKILL.md is roughly 5.8k 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 164 tokens, read only when the agent opens those files.
What are the alternatives to Embedded Debugger?
Skills that share tags, products or a category with Embedded Debugger: Memorywhale (wuisabel-gif/MemWhale, 154 stars), Memorywhale Evidence (wuisabel-gif/MemWhale, 154 stars), Slint (Moosync/Moosync, 259 stars) and Memorywhale Debugging (wuisabel-gif/MemWhale, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Embedded Debugger?
Adancurusul (a GitHub user) maintains it in Adancurusul/embedded-debugger-mcp, which has 200 GitHub stars. The repository was last updated on July 16, 2026.
Source: Adancurusul/embedded-debugger-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.