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artifact_generate

Read-only

Generate a governed, tenant-scoped artifact draft with no-fabrication placeholders, analyzer provenance, MASK, brand status, and approval requirements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
laneNo
formatNo
localeNo
audienceNo
tenant_idYes
caller_typeNo
brand_kit_idNo
voice_anchorNo
artifact_typeYes
budget_policyNo
variant_countNo
source_contextNo
idempotency_keyNo
output_languageNo
variant_strategyNo
voice_profile_idNo
analysis_findingsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / voice_anchor
      Added value: +{
      +  "type": "string"
      +}
  2. Added

TDQS

C2.9/5.0
Behavior4/5

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

The description adds meaningful behavioral context beyond the readOnlyHint annotation by mentioning no-fabrication placeholders, analyzer provenance, MASK, brand status, and approval requirements. It does not contradict the annotation because generating a 'draft' suggests an in-memory result rather than a persistent change.

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 a single front-loaded sentence with no filler, and the key action is stated immediately. However, the dense jargon such as MASK, analyzer provenance, and approval requirements is not explained, which slightly reduces overall clarity.

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?

For a 17-parameter tool with no parameter descriptions, this description is far too sparse. It omits when to generate versus refine or save, how format/lane/variant settings interact, and what MASK or approval requirements actually mean. The output schema covers return values, but the invocation and selection context remains incomplete.

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

Parameters1/5

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

With 17 parameters and 0% schema description coverage, the description needed to compensate heavily but does not. It vaguely signals tenant scoping and artifact type, but terms like MASK, analyzer provenance, and approval requirements do not map to any schema property, leaving the agent without useful parameter-level guidance.

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 action ('Generate') and the resource ('governed, tenant-scoped artifact draft'), which distinguishes it from siblings like artifact_save, artifact_refine, and artifact_export. The word 'draft' helps differentiate it from persistence-oriented tools, though no alternative is named explicitly.

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?

There is no guidance on when to use this tool versus artifact_refine, artifact_save, or other generation-related siblings. The description implies a draft-generation use case but never states when it should be preferred or what to do after generation.

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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TDQS

C2.6/5.0
Disambiguation1/5

Several tools are exact duplicates (talent_scout_my_profile_status and talent_scout_profile_status have identical descriptions), and eight estimator_estimate_* tools share the same generic description with no differentiation. This will cause misselection.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern, but there are inconsistencies: the duplicate profile tools have different naming (my_profile vs profile), and `fetch`/`search` are single-word verbs. Predictability is hampered by these deviations.

Tool Count2/5

65 tools is excessive for a coherent set, especially with many tools covering overlapping actions across multiple unrelated domains (AI receptionist, estimator, talent scout, GrowthOS). The count could be trimmed significantly.

Completeness3/5

The tool surface is broad and covers many lifecycle operations (create, read, export, record), but the duplicate tools and identical descriptions for estimator operations make it unclear whether all needed operations are present. Some expected operations like delete/update are missing for certain resources.

Resources