Get AB 2013 (California) + EU AI Act Article 53 compliance manifests for dataset usage. FREE. (FREE)
| Name | Required | Description | Default |
|---|---|---|---|
| dataset_id | No | Dataset ID | alexandria-aeternum |
| regulation | No | Filter: ab2013, eu_ai_act, or all | all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds no behavioral context beyond noting it is free. No disclosure of rate limits, data freshness, or error states.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short at two sentences, but 'FREE. (FREE)' is redundant and wastes space. Could be more concise without the repetition, but overall not bloated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explain the content or structure of a compliance manifest. It does not mention default parameter values or what 'all' regulation means for output. Leaves significant gaps for a tool dealing with legal documents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes both parameters. The description adds minimal value by vaguely hinting at dataset usage but does not explain defaults, formats, or provide concrete semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The verb 'Get' clearly indicates retrieval, and the resource is specified as 'compliance manifests for dataset usage' with specific regulations (AB 2013 and EU AI Act Article 53). It distinguishes from siblings as no other tool deals with compliance manifests.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, nor any prerequisites or when-not-to-use scenarios. The 'FREE' label is present but does not provide actionable usage direction.
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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Each tool targets a distinct operation—artwork retrieval, image processing, asset management, watermarking, etc.—with clear descriptions that prevent confusion. Even similar tools like enrich_metadata and get_artwork_oracle are differentiated by depth and purpose.
Tool names follow a consistent verb_noun pattern in snake_case (e.g., get_artwork, remove_background, register_hash). The few non-verb-starting names (compliance_manifest) are standard and do not break the overall pattern.
27 tools is slightly above the typical range but justifiable given the broad domain covering artwork access, image processing, and digital rights. Each tool serves a unique purpose without redundancy.
The tool set covers the full lifecycle: search, retrieve, analyze, edit, save, and verify assets. Gaps are minimal—e.g., no metadata deletion tool—but the core workflows are fully supported, and the inclusion of compliance and provenance tools adds value.