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 LGDiMaggio/predictive-maintenance-mcp --skill signal-managementgit clone --depth 1 https://github.com/LGDiMaggio/predictive-maintenance-mcpWrote 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/lgdimaggio/predictive-maintenance-mcp/signal-management)<a href="https://agentmods.dev/skills/lgdimaggio/predictive-maintenance-mcp/signal-management"><img src="https://agentmods.dev/badge/skills/lgdimaggio/predictive-maintenance-mcp/signal-management/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/lgdimaggio/predictive-maintenance-mcp/signal-management"><img src="https://agentmods.dev/badge/skills/lgdimaggio/predictive-maintenance-mcp/signal-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00091 | $0.01917 |
| Opus 5.5 | $0.00036 | $0.00767 |
| Sonnet 5.5 | $0.00018 | $0.00383 |
| Haiku 4.5 | $0.00009 | $0.00192 |
Grade A, and why
signal-management 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 1mo 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Signal Management
Load, generate, inspect, and manage vibration signals in the
predictive-maintenance-mcp in-memory repository. Supports CSV, TXT, NPY, WAV,
MAT (MATLAB), and Parquet formats, plus headerless raw binary (.bin, .raw,
.dat) with a declared decode contract. The signal_id returned by loading is
the single handle every analysis, diagnosis, report, and prognostics tool
accepts.
Prerequisite: The predictive-maintenance-mcp MCP server must be connected.
Core Operations
List Available Signals
- On disk:
list_signals(scope="disk")— files under data/signals/ that load_signal can open (this is also the default scope). - In memory:
list_signals(scope="memory")— signals currently loaded, with their signal_id, sampling rate, and declared unit.
Load a Signal
Call load_signal(filepath="real_train/baseline_1.csv", signal_unit="g").
- filepath: path relative to data/signals/ or an absolute path
- signal_id (optional): custom handle. Default: the relative path with
separators replaced by underscores —
real_train/baseline_1.csvbecomesreal_train_baseline_1, so same-named files in different folders never collide silently - sampling_rate (optional): Hz — overrides the companion metadata file.
Required if no
_metadata.jsondeclares it (ask the user; never guess) - signal_unit (optional):
"g","m/s2","mm/s", or"m/s"— declare it if known. ISO severity verdicts are REFUSED for signals without a declared unit; units are never guessed from amplitude - overwrite: re-loading a path whose signal_id already exists is an
explicit error unless
overwrite=True - Asset identity: a companion whose
measurementobject declaresasset_id,measurement_point_idandacquired_at(optionallyrpmin rev/min,load,operating_state,sensor_id,direction,declared_by) is validated on load, and the measurement is then recorded in the local asset ledger; the returnedmeasurementblock reportsledger_status,snapshot_statusand the comparability grade against the point. An invalid object is refused with every problem named; a companion without the object loads exactly as before
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.
- 1mo ago Changed · +24 lines 5b7d59239e08
- 2mo ago First seen · 140 lines · 91 tokens per session scan A 48519f9f2b7e
signal-management is a skill published in the GitHub repository LGDiMaggio/predictive-maintenance-mcp (109 stars, last pushed yesterday), licensed MIT. It adds 91 tokens to every session and 1,917 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.
signal-management compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| signal-managementLGDiMaggio/predictive-maintenance-mcp | Skill | 109 | yesterday | MIT | A | 91 | Claude Code |
| machine-vibration-monitoringLGDiMaggio/claude-stwinbox-diagnostics | Skill | 10 | 7mo ago | Apache-2.0 | A | 107 | Claude Code, Codex |
| vibration-fault-diagnosisLGDiMaggio/claude-stwinbox-diagnostics | Skill | 10 | 7mo ago | Apache-2.0 | A | 117 | Claude Code, Codex |
| ruview-applicationsruvnet/RuView | Skill | 103k | yesterday | MIT | A | 79 | Claude Code |
| lab-hardware-cadK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 108 | Claude Code |
| pylabrobotK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 49 | Claude Code |
| pybammK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 70 | Claude Code, Codex |