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DanFashauer

SignalGrid MCP

by DanFashauer

signalgrid_software_updates

Read-onlyIdempotent

Audit macOS update posture: check auto-update settings, last check date, and cached available updates to identify patch-hygiene risks. Optionally trigger a live softwareupdate scan.

Instructions

Software update posture: auto-update settings, last successful check, cached count of available updates, and optionally a live check.

LastUpdatesAvailable > 0 or a stale LastSuccessfulDate is a patch-hygiene red flag. Values are null when a preference is unset or unreadable.

Args: check_online: run a live softwareupdate -l (slow) in addition to the cached state.

Returns: dict with keys: settings (dict of SoftwareUpdate preferences incl. AutomaticCheckEnabled, AutomaticallyInstallMacOSUpdates, CriticalUpdateInstall, LastSuccessfulDate, LastUpdatesAvailable, AppStoreAutoUpdate), and live_check (str, only when check_online=true).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
check_onlineNoIf true, also query Apple's update servers live via `softwareupdate -l` (slow: 30-120s). If false (default), report only cached preference state, which is instant.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context: values are null when unreadable, the difference between cached and live state, and the performance implication of the live check. This goes beyond the annotation flags.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary, a usage note, args, and returns. While somewhat verbose, every sentence carries useful information, including the return keys and the red-flag interpretation. It is front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given one parameter, a rich output schema, and read-only annotations, the description is complete. It covers return values, null semantics, performance, and decision-making context (patch-hygiene red flag). No significant gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description for check_online is thorough, covering default behavior and timing (30-120s). The description's Args section only repeats this information without adding additional meaning, so the baseline of 3 applies since schema coverage is 100%.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's resource: software update posture, including auto-update settings, last check, and available updates. It distinguishes from sibling posture tools by focusing specifically on software updates, though it lacks an explicit verb like 'get' or 'query'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool, such as checking for patch-hygiene red flags (LastUpdatesAvailable > 0 or stale LastSuccessfulDate). It also explains the trade-off between cached (instant) and live (slow) checks, guiding parameter selection. It does not explicitly name alternative tools, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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