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Glama

update_configuration

Destructive

Modify specific fields of an existing experiment configuration while leaving omitted settings unchanged. Pass null to detach dataset or model references.

Instructions

Update fields on an existing configuration. Only the fields you pass are sent to the API and changed -- omitted fields keep their current value (the backend uses exclude_unset semantics). Do not pass a field just to keep it the same. Pass null for dataset_id, clean_dataset_id, or model_id to detach that reference.

Input Schema

NameRequiredDescriptionDefault
nameNo
seedNo
deviceNo
cv_modelNo
lr_gammaNo
model_idNo
momentumNo
n_groupsNo
nesterovNo
config_idYes
optimizerNo
scoring_kNo
batch_sizeNo
dataset_idNo
lr_scheduleNo
num_workersNo
target_classNo
total_epochsNo
weight_decayNo
learning_rateNo
phase_i_zscoreNo
clean_dataset_idNo
threshold_methodNo
training_settingNo
batch_level_epochsNo
model_architectureNo
poisoning_thresholdNo
sample_level_epochsNo
confidence_thresholdNo
batch_level_start_epochNo
sample_level_start_epochNo
phase_ii_feature_importanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

The description adds substantial context beyond annotations: exclude_unset partial-update semantics, the fact that omitted fields retain current values, and that null detaches dataset_id, clean_dataset_id, or model_id. Annotations already disclose readOnly=false and destructive=true, so the remaining gap is minor.

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?

Four sentences, front-loaded with the core action, followed by the non-obvious partial-update and null-detach rules. Every sentence carries operational value and there is no filler.

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

Completeness3/5

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

The description covers the mutation model well and there is no output schema to explain. For a 32-parameter update tool with no parameter descriptions, though, it is incomplete: an agent still lacks semantic guidance for most domain-specific fields.

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?

With 0% schema description coverage across 32 parameters, the description compensates for the three nullable reference fields and the overall partial-update semantics. It still leaves most domain-specific parameters (e.g., phase_i_zscore, batch_level_epochs, poisoning_threshold) undocumented beyond their type and range constraints.

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 opens with a specific verb and resource: 'Update fields on an existing configuration.' This clearly distinguishes it from create_configuration and get_configuration by name alone, though it never explicitly contrasts itself with those siblings.

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

Usage Guidelines3/5

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

It gives useful usage rules for partial updates ('Only the fields you pass are sent... Do not pass a field just to keep it the same') and null-detach behavior. However, it never says when to choose this tool over create_configuration or get_configuration, so guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.