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get_experiment_runs

Retrieve all runs for an MLflow experiment to analyze metrics, parameters, and performance across different training iterations.

Instructions

Get all runs for an experiment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experiment_idNo226
tokenNo
Behavior2/5

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

With no annotations, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication (implied by 'token' parameter but not explained), rate limits, pagination, or what 'get' entails (e.g., returns list, errors). This leaves significant gaps for agent understanding.

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 extremely concise with a single sentence 'Get all runs for an experiment', which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary elaboration, making it easy to parse quickly.

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?

Given 2 parameters with 0% schema coverage, no annotations, no output schema, and sibling tools, the description is incomplete. It lacks details on parameter usage, return values, error handling, and differentiation from alternatives. For a tool with moderate complexity and poor structured support, this description is insufficient for reliable agent operation.

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 0%, so the description must compensate but adds no parameter information. It doesn't explain 'experiment_id' (e.g., format, source) or 'token' (e.g., authentication token, optional usage). With 2 undocumented parameters and no output schema, the description fails to provide necessary semantic context beyond the schema.

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

Purpose3/5

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

The description 'Get all runs for an experiment' clearly states the action (get) and resource (runs for an experiment), but it's vague about scope and doesn't distinguish from sibling tools like 'get_run' or 'search_experiments'. It specifies 'all runs' but lacks detail on what constitutes a 'run' or how results are presented.

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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites like authentication, compare to 'get_run' for single runs or 'search_experiments' for broader queries, or specify use cases like monitoring or analysis. The description alone offers no contextual 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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