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verify_source

Retrieve the source URL and SHA-256 content hash for any NVIDIA AI concept node to verify content integrity by comparing the hash of the fetched source.

Instructions

Return the source URL and SHA-256 content hash for any NVIDIA AI concept node.

Audit chain: edge answer → graph commit → source_content_hash → source_url (fetch hint).
Verification: curl -s <source_url> | sha256sum  # compare to source_hash

Args:
    concept: Concept label (partial match supported).
    domain:  Domain from list_domains() — e.g. 'nvidia-nim', 'nvidia-tensorrt-triton'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
conceptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are present, so the description carries full burden. It discloses the audit chain (edge answer → graph commit → source_content_hash → source_url) and verification command, providing good insight into the tool's behavior beyond just its output.

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 reasonably concise and well-structured with an audit chain followed by argument descriptions. It could be slightly shorter but every sentence adds value.

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 the tool has an output schema (though not shown) and the description covers inputs and verification guidance, it is fairly complete. The verification steps and audit trail provide sufficient context for appropriate use.

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?

Schema coverage is 0%, so the description must compensate. It explains both parameters: concept (with partial match) and domain (with examples like nvidia-nim). This adds significant meaning beyond the raw schema.

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 explicitly states it returns the source URL and SHA-256 hash for NVIDIA AI concept nodes, using a specific verb and resource. It clearly distinguishes this verification tool from sibling tools like search_concepts and list_domains.

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 an audit chain and explicit verification steps (curl + sha256sum). It implies when to use (for provenance checking) but does not explicitly exclude scenarios or name alternatives.

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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