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parse_devices_from_project

Extract exact device object models from KNX project files (.knxproj/.knxprod) to build a local catalog of vendor communication objects, including order numbers, app versions, and per-channel blocks.

Instructions

Extract exact device object models from a .knxproj / .knxprod application programs.

Reads the manufacturer application programs (M-*) embedded in an ETS `.knxproj`
(devices actually used) or a `.knxprod` product database, and returns each device's
order number, app-program version, object counts and detected per-channel blocks —
the EXACT vendor comm-object model, not a generic recipe. Read-only and PII-safe: it
reads only vendor catalog data, never the client project (P-*/0.xml).

Use this to build/grow the local device catalog that `decompose_device` consumes
(set NICKOL_KNX_CATALOG to the catalog dir). If `output_path` is given, the full
catalog is written into the workspace as device-library YAML; the return value is
always a compact per-device summary + coverage manifest (the full object lists are
not inlined). DPT `unverified` = the vendor app-program declares none (never guessed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
passwordNo
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses behavior: read-only, PII-safe, reads only vendor data, never client project. It explains what 'unverified' DPT means and that the return value is a summary not full object lists. No contradictions.

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?

Single paragraph is efficient and front-loaded with purpose, but somewhat lengthy. Every sentence adds value, though could be structured with bullet points for readability.

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

Completeness4/5

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

Given 3 parameters, no annotations, and output schema exists, the description covers purpose, usage, return value summary, and limitations. Lacks details on error cases or prerequisites but is largely complete.

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?

Schema description coverage is 0%, so description must compensate. It indirectly explains path (file type) and output_path (catalog writing), but password parameter is not explained. Adds value beyond schema but could be more complete.

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?

The description clearly states it extracts exact device object models from .knxproj/.knxprod files, specifying the resource (vendor application programs) and action (extract). It distinguishes from siblings by contrasting with 'generic recipe' and noting it reads only vendor catalog data, not client projects.

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?

Explicitly states when to use: to build the local device catalog for decompose_device, and mentions setting NICKOL_KNX_CATALOG. Also explains behavior with output_path and the return value format, providing clear context for usage.

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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