Wonderwhy-er/DesktopCommanderMCP is an MCP server that lets AI clients search and edit files, run terminal commands, and manage computer processes. It is used to give coding agents practical control over a local development environment through chat. The catalogue add-ons extend or configure this server and its agent workflows.
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 wonderwhy-er/DesktopCommanderMCP --skill computer-health-checkgit clone --depth 1 https://github.com/wonderwhy-er/DesktopCommanderMCPWrote 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/wonderwhy-er/desktopcommandermcp/computer-health-check)<a href="https://agentmods.dev/skills/wonderwhy-er/desktopcommandermcp/computer-health-check"><img src="https://agentmods.dev/badge/skills/wonderwhy-er/desktopcommandermcp/computer-health-check/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/wonderwhy-er/desktopcommandermcp/computer-health-check"><img src="https://agentmods.dev/badge/skills/wonderwhy-er/desktopcommandermcp/computer-health-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Privilege Escalation · line 16 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00209 | $0.02090 |
| Opus 5 | $0.00105 | $0.01045 |
| Sonnet 5 | $0.00042 | $0.00418 |
| Haiku 4.5 | $0.00021 | $0.00209 |
Grade B, and why
computer-health-check scanned grade B with 1 finding 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 11d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
default — it never needs sudo and only performs cleanups the user explicitly approves. Copies of this mod
2 near-identical copies found in the catalogue:
- computer-health-check — 100% identical, 0 lines differ
- computer-health-check — 97% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Computer Health Check
What this skill does
Give the user a fast, trustworthy picture of their computer's health and a short list of actions worth taking — the way a good technician would: look first, explain plainly, fix only with permission.
It runs entirely through Desktop Commander's local shell, gathers a batch of read-only diagnostics, scores each area, prints a concise summary in the chat, and then offers cleanup suggestions the user can approve one by one.
The safety contract (read this first)
This is the part that makes users trust the skill, so honor it strictly:
- Read-only by default. The collection phase only observes (sizes, counts, status). It changes nothing.
- Never use
sudoor elevation. DC blockssudo,shutdown,reboot,dd,mount,mkfs,diskpart, etc. for good reason. Every check below is designed to work without them. If something seems to need elevation, skip it and say so — don't try to work around the block. - Cleanups are opt-in. You may suggest cleanups freely, but only execute one after the user explicitly approves that specific action, and only show the exact command first.
- Prefer reversible, non-destructive actions. Emptying caches that regenerate, clearing a package-manager download cache, or emptying Trash are fine to offer. Deleting user documents, uninstalling apps, or editing system files are not — suggest those, let the user do them.
Workflow
Step 1 — Detect the OS
Determine the platform before doing anything else, because the commands differ.
- Quickest: read Desktop Commander's config (
get_config) and use thesystemInfo.isMacOS/isWindows/isLinuxbooleans (orplatformName) to pick the platform. - Or run
uname(macOS/Linux) — if it fails, assume Windows.
Then open the matching reference file and use its command set:
- macOS →
references/macos.md - Windows →
references/windows.md - Linux →
references/linux.md
What ships with it
3 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.
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.
- 11d ago First seen · 166 lines · 209 tokens per session scan B 7c6c61ac72b7
computer-health-check is a skill published in the GitHub repository wonderwhy-er/DesktopCommanderMCP (9,525 stars, last pushed yesterday), licensed MIT. It adds 209 tokens to every session and 2,090 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
peer-review
Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating…
scientific-critical-thinking
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review…
scientific-schematics
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways…
hypothesis-generation
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for…
paper-lookup
Search 10 academic literature APIs for papers, preprints, citations, and open-access full text, and return results with reproducible provenance. Covers PubMed, PMC (full text), bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall. Use when searching for papers, citations, DOI/PMID/arXiv…
scholar-evaluation
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.