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tokscale_device_profile

Read-only

Profiles your machine's AI tool setup and activity, showing installed tools, session histories, and usage patterns without leaking local usernames.

Instructions

Device fingerprinting: profiles this machine's AI tool footprint — which AI tools are installed, where their session logs live (paths redacted to ~), how many sessions and messages each has, when the machine was active (daily activity + day-of-week distribution), session concurrency, and longest continuous session. Combines tokscale clients + graph data. All filesystem paths are redacted so no local username leaks. Use this to audit your own machine's AI tool installation and activity pattern. This is local-only — it profiles the current machine, not remote devices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent if tokscale is unavailable
summaryNoCost summary from graph: total_tokens, total_cost, avg_per_day, max_single_day
activityNoDaily activity + day-of-week token distribution
sessionsNoSession metrics: count, total/longest active time, max concurrent
date_rangeNo{ start, end } of the activity data
installed_toolsNoDetected AI tools with redacted session paths and message counts
active_tool_countNoTools whose session path exists on disk
installed_tool_countNo
Behavior5/5

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

Annotations already indicate readOnlyHint=true. Description adds valuable behavioral context: paths are redacted to prevent local username leaks. No contradiction with annotations.

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?

Description is informative but slightly verbose; could be tightened. However, all sentences add value, and key info is front-loaded. Acceptable for a parameterless tool.

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?

With no parameters and an output schema present, the description covers all relevant aspects: purpose, scope, data privacy, and local-only nature. No gaps.

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

Parameters4/5

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

No parameters (0 params, baseline 4). Description correctly notes 'No parameters. Profiles the local machine via tokscale.' The description adds no extra param semantics but is accurate.

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

Purpose5/5

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

Description clearly states it profiles the local machine's AI tool footprint, listing specific data points (installed tools, session logs, activity patterns). The 'local-only' distinction effectively differentiates it from siblings.

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

Usage Guidelines5/5

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

Provides explicit usage guidance: 'Use this to audit your own machine's AI tool installation and activity pattern.' Also clarifies context by stating 'This is local-only — it profiles the current machine, not remote devices,' which helps avoid misuse.

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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