io.github.yamaru-eu/hardware-probe
NPM · @YAMARU-EU/HARDWARE-PROBE · SCANNED AUG 6
Hardware probe for performance diagnostics, thermal monitoring, and LLM optimization.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →
Supply Chain Security87
- No malware found by supply-chain analysis.Pass
- Known CVEs were checked across the 95 of 99 dependencies we could resolve, so this covers what we could see, not the whole tree.Partial
- No install/post-install scripts declared.Pass
- Dependency health was assessed across the 95 of 99 dependencies we could resolve, so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency32
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: no license is declared. See how to fix → Fail
- Actively maintained (last published 86 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability75
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 459 tokens (~41/item across 11 items; 11 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management33
- Stability observed for 10 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
npm · @yamaru-eu/hardware-probe
claude mcp add yamaru-eu-hardware-probe -- npx -y @yamaru-eu/hardware-probe
codex mcp add yamaru-eu-hardware-probe -- npx -y @yamaru-eu/hardware-probe
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"yamaru-eu-hardware-probe": {
"type": "local",
"command": [
"npx",
"-y",
"@yamaru-eu/hardware-probe"
],
"enabled": true
}
}
} openclaw mcp add yamaru-eu-hardware-probe --command npx --arg -y --arg @yamaru-eu/hardware-probe
mcp_servers:
yamaru-eu-hardware-probe:
command: "npx"
args: ["-y", "@yamaru-eu/hardware-probe"] {
"mcpServers": {
"yamaru-eu-hardware-probe": {
"command": "npx",
"args": [
"-y",
"@yamaru-eu/hardware-probe"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 5 Aug 26 +2
- CVE-2026-69207 no longer affects this package ▲ security
- Known CVEs: fail → partial ▲ security
- 4 Aug 26 −1
- CVE-2026-69207 affects this package: medium ▼ security
- Known CVEs: partial → fail ▼ security
- 3 Aug 26 +3
- Stability: unverified → 0.23 ▲ functional
- 2 Aug 26 +58
- Provenance: unverified → fail ▼ security
- Install scripts: unverified → pass ▲ security
- Known CVEs: unverified → partial ▲ security
- Malware scan: unverified → pass ▲ security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- License: unverified → fail ▼ functional
- Maintenance: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Tool coverage: unverified → 100 ▲ functional
- 1 Aug 26 −2
- Dependency health: partial → unverified ▼ functional
- 31 Jul 26 −33
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 30 Jul 26 −36
- Install scripts: pass → unverified ▼ security
- Malware scan: pass → unverified ▼ security
- Known CVEs: partial → unverified ▼ security
- Provenance: fail → unverified ▼ security
- Dependency health: partial → unverified ▼ functional
- License: fail → unverified ▼ functional
- Maintenance: pass → unverified ▼ functional
- 27 Jul 26 +51
- Provenance: unverified → fail ▼ security
- Known CVEs: unverified → partial ▲ security
- Install scripts: unverified → pass ▲ security
- Security disclosure: unverified → fail ▼ functional
- License: unverified → fail ▼ functional
- Maintenance: unverified → pass ▲ functional
- Tool coverage: unverified → 100 ▲ functional
- First check of Tool coverage: 100 functional
- First check of Schema quality: good functional
- First check of Schema quality: pass functional
- First check of Schema quality: fail functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 6 Aug 2026 · Analysed npm/@yamaru-eu/[email protected]
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Dependencies 95 packages
| Packages resolved | 95 |
|---|---|
| Deprecated | 95 |
| Stale | 29 |
| Tree resolution | Partial |
The dependency tree was only partially resolved, so these counts may be incomplete.
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
analyze_inference_config ~45
Performs a deep scan for LLM inference optimization: GPU details, real memory bandwidth benchmark, ML runtimes (Ollama, Docker, WSL), and environment variables.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
analyze_local_system ~32
Reads the hardware specifications of the local machine: CPU, RAM, motherboard and OS. Returns a structured JSON object.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
analyze_performance ~25
Provides real-time system performance: CPU load, memory usage, and top processes.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
analyze_ram_pressure ~31
Reports current memory pressure: total/used/free/available memory, swap usage, and top processes by RSS.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
check_llm_compatibility ~70
(BETA) Checks if a specific LLM model can run on this machine. Returns optimal quantization and estimated tokens per second. Requires remote API connection.
| Name | Type | Req | Description |
|---|---|---|---|
| model_name | string | yes | LLM model name (e.g., 'Llama 3.1 70B') |
No output schema declared.
No examples provided.
check_storage_health ~34
Reports per-disk health: type (NVMe/SSD/HDD), vendor, temperature, SMART status, and firmware.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
diagnose_antivirus_impact ~31
Detects running antivirus/EDR products and reads their exclusion rules. Checks dev hot paths coverage.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_inference_expert_knowledge ~42
Returns the expert instructions and rules for optimizing LLM inference on this specific hardware. Call this to learn HOW to interpret analyze_inference_config results.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_llm_recommendations ~56
(BETA) Recommends the best LLM models that can run locally on this machine. Requires remote API connection.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | number | – | Max recommendations |
| use_case | string | – | Use case |
No output schema declared.
No examples provided.
monitor_system_health ~67
Monitors system metrics (CPU, RAM, Thermal) over a specified duration and returns statistical summary. Useful for diagnosing transient issues during high-load tasks.
| Name | Type | Req | Description |
|---|---|---|---|
| duration_seconds | number | – | Monitoring duration in seconds (max 60) |
| interval_seconds | number | – | Sampling interval in seconds |
No output schema declared.
No examples provided.
thermal_profile ~26
Reports current CPU and GPU thermal and frequency state: temperature, utilization, and fan speed.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.