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aeoess

agent-passport-system-mcp

by aeoess

create_artifact_provenance

Ensure trust in AI outputs by tagging generated artifacts with provenance metadata: content hash, risk class, and authoring agent.

Instructions

Tag an agent-generated artifact with provenance metadata (content hash, risk class, authoring agent).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe artifact content (used for hash, not stored)
risk_classYes
trust_epochNo
valid_untilYes
intended_useYes
artifact_typeYese.g. email_draft, code_script, database_query
delegation_refYes
requires_human_executionNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions hashing content and recording risk class and authoring agent, but does not explain side effects, persistence, reversibility, permissions, or any other behavioral traits. The schema's note that content is not stored is not reflected in the description.

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?

The description is a single, concise, front-loaded sentence that states the tool's purpose without extraneous words. It is appropriately sized for the high-level information it conveys.

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

Completeness2/5

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

The tool has 8 parameters, 6 required, no output schema, and no annotations. The one-sentence description is far too thin to give an agent adequate context for required fields, expected behavior, or return values. It is inadequate for a tool of this complexity.

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

Parameters2/5

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

Schema description coverage is only 25% (2 of 8 parameters have descriptions). The description mentions content hash, risk class, and authoring agent, but the latter is not a schema parameter, and the remaining required fields (delegation_ref, intended_use, artifact_type, valid_until) are left unexplained. The description adds minimal value beyond the sparse schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tags an agent-generated artifact with provenance metadata, using the specific verb 'Tag' and a clear resource. It lists metadata types (content hash, risk class, authoring agent), but does not explicitly contrast with sibling tools like create_derivation_receipt or aps_create_attribution_receipt, so it lacks explicit differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance about when to use this tool versus alternatives, no prerequisites, and no exclusions. An agent receives no context for selecting it among the many provenance-related sibling tools.

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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