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Bulk upsert parameters

model_upsert_parameters

Create or patch many catalog rows (cap 400). Same body shape as model_upsert_parameter. continueOnError returns per-row errors; otherwise one transaction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
parametersYesCatalog rows (parameterId + same fields as model_upsert_parameter)
continueOnErrorNo

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of disclosing effects. It reveals the batch cap, the transaction behavior when continueOnError is false, and the per-row error behavior when true. It does not fully explain failure responses or cap-violation handling, but the core operational behavior is clear.

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?

Three compact sentences with no filler. The cap is front-loaded in the first sentence, the body-shape reference is brief, and the error-mode distinction is presented in one clause. Every sentence earns its place.

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?

The description captures the essential contract: batch size cap, payload shape, and the two error-handling modes. Given there is no output schema and no annotations, this is reasonably complete, though a description of the id parameter and the exact success response shape would make it fully self-contained.

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?

The description adds meaning for continueOnError ('per-row errors' vs 'one transaction'), which is not in the schema. However, the optional id parameter is left unexplained, and the 'same body shape' reference depends on another tool's documentation. With only 33% schema description coverage, this is partial compensation.

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 states the action ('Create or patch'), the resource ('many catalog rows'), and an important constraint ('cap 400'). It clearly distinguishes this bulk endpoint from the singular model_upsert_parameter via the word 'many' and the cap.

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 phrase 'many catalog rows' plus the 400-row cap makes it clear this is for batch operations, and the sibling tool name model_upsert_parameter implies the single-row alternative. It does not explicitly say 'use model_upsert_parameter for one row' or state when not to use this tool, so it stops short of a 5.

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

B3.2/5.0
Disambiguation2/5

Many tools are mirrored across `artifacts_*` and `roadflow_*` with near-identical names and behavior, and within each family `get`, `export_json`, and `export_markup` overlap in what they return. Descriptions identify the target workspace, but an agent must carefully inspect prefixes and formats to avoid misselection.

Naming Consistency4/5

The set consistently uses lowercase snake_case with a domain prefix and predictable verbs like get, list, create, open, export, and apply. Minor deviations are bare commands (`new`, `discard`, `status`) and the parallel `artifacts_*`/`roadflow_*` prefixes, which make names look duplicated.

Tool Count3/5

At 23 tools, the surface lands in the heavy 16-25 range and feels padded because many operations are duplicated for two workspace types. Each subsystem alone would have a reasonable count, but combined the set is bloated.

Completeness4/5

The toolset covers the full workspace lifecycle: create, read, update via apply, discard, share, version, status, and multiple export formats. Missing cloud deletion and fine-grained element editing are minor gaps that can be worked around with full-state apply/export.

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