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Netbrain Integrated Solutions catalogue

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get_product
Read-onlyIdempotent

Full detail for a single Netbrain product or platform, by slug. Use search_products first if you do not already know the slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe catalogue slug, e.g. "siswati-llm".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / slug / enum
      Previous value: -[
      -  "smart-java-kotlin-analyzer",
      -  "intellij-benchmarking",
      -  "spring-boot-monitoring",
      -  "numerai-models",
      -  "compliance-api",
      -  "cross-chain-api",
      -  "siswati-llm",
      -  "veridix-market-prediction-platform"
      -]New value: +[
      +  "smart-java-kotlin-analyzer",
      +  "bugbench",
      +  "spring-boot-monitoring",
      +  "compliance-api",
      +  "cross-chain-api",
      +  "siswati-llm",
      +  "veridix-market-prediction-platform"
      +]
  2. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety and idempotency profile is fully covered by structured fields. The description adds only the slug-discovery workflow hint, and says nothing about return shape or lookup failure behavior beyond what the output schema and annotations provide.

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?

Two short sentences, zero waste, with the core purpose front-loaded and the routing hint second. Nothing could be trimmed without losing guidance.

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?

For a one-parameter, read-only lookup with an output schema and full annotation coverage, the description supplies everything an agent needs: what it returns, how to invoke it, and how to obtain the required slug. No meaningful gap remains.

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 coverage is 100% and the single slug parameter is fully documented with an enum and example in the schema. The description mentions 'by slug' but adds no format, casing, or fallback semantics beyond what the schema already states, so the baseline 3 applies.

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?

States a specific verb and resource: 'Full detail for a single Netbrain product or platform, by slug.' The word 'single' plus 'by slug' scopes it precisely and implicitly separates it from the sibling search_products.

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 names the alternative and the condition selecting it: 'Use search_products first if you do not already know the slug.' This is exactly the when/when-not guidance needed, with no inference required.

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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