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industrial-aiops

OT-AIops Energy

asset_inventory

Read-only

Actively fingerprint OT endpoints to build an asset register with vendor, model, firmware, serial, and reachability status.

Instructions

[READ][risk=low] Actively fingerprint endpoints into an asset register.

Connects to each target with our own protocol client and reads its identity
call (S7 CPU info, EtherNet/IP controller info, OPC-UA server build info,
Modbus device identification FC43, Mitsubishi CPU type, MTConnect device
model), aggregating vendor/model/firmware/serial per device.

Honest scope: ACTIVE fingerprinting (we connect to each device), NOT passive
SPAN/tap discovery. Only finds devices we are configured to reach.

Args:
    endpoints: Endpoint names to fingerprint; omit to fingerprint ALL
        configured endpoints.

Returns dict: {asset_count, reachable_count, unreachable_count, method:
    'active_fingerprint', assets:[{endpoint, protocol, address, vendor, model,
    firmware, serial, reachable, last_seen, error}]}.

Example: asset_inventory(endpoints=["press1","cell5"]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endpointsNo
Behavior5/5

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

Annotations already mark readOnlyHint=true and destructiveHint=false, but the description adds meaningful context: the tool connects to endpoints via its own protocol client and reads identity calls. It also warns about reachability constraints and labels risk as low, going beyond the structured annotations.

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

Conciseness5/5

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

Information is front-loaded with [READ][risk=low], followed by a concise explanation, an honest scope note, parameter guidance, return structure, and example. Every sentence adds value and the format is easily scannable.

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 output schema, the description fully specifies the return dict including all fields such as asset_count, reachable_count, method, and asset details. It covers scope, parameters, example, and edge cases (unreachable endpoints), making it complete for invocation.

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

Parameters5/5

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

Although schema description coverage is 0%, the text fully explains the only parameter: 'endpoints: Endpoint names to fingerprint; omit to fingerprint ALL configured endpoints.' The example further clarifies usage.

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 opens with a specific verb+resource: 'Actively fingerprint endpoints into an asset register.' It then lists concrete protocol identity calls and explicitly distinguishes active fingerprinting from passive SPAN/tap discovery, clearly separating it from sibling tools.

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 scope boundaries: 'ACTIVE fingerprinting (we connect to each device), NOT passive SPAN/tap discovery' and 'Only finds devices we are configured to reach.' It also explains the optional endpoints parameter, giving the agent clear guidance on when to omit it.

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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