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Simba MCP Server

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by getsimba-ai

set_run_pinned

Pin or unpin a saved optimizer or scenario run to control its status. Idempotent operation ensures re-running the same state has no effect, making scripts safe to execute.

Instructions

Pin or unpin a saved optimizer or scenario run.

Declarative and idempotent: setting the current state again is a no-op, so scripts can safely re-run it.

Args: artifact: "optimizer" (run_id "opt_...") or "scenario" ("scn_..."). model_hash: Hash of the model the run belongs to. run_id: The run's stable id from run history. pinned: Desired pin state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pinnedYes
run_idYes
artifactYes
model_hashYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly reveals the key safety property: setting the current state again is a no-op and safe to re-run. It also explains run_id prefix conventions (opt_/scn_) and parameter roles, which adds meaningful behavior context beyond the schema.

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 front-loaded with the purpose, followed by the idempotence note, then a compact and structured Args list. Every sentence contributes useful information, with no filler or repetition of schema content.

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?

Given four required parameters, no schema descriptions, no annotations, and no output schema, the description covers the essential invocation details and the main behavioral guarantee. It could mention return behavior or error cases, but as a simple setter tool the provided information is sufficient for correct use.

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

Parameters5/5

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

Schema description coverage is 0%, so the Args section is the only explanation of parameters. It fully describes all four parameters: artifact with allowed values and id prefixes, model_hash, run_id, and pinned. This goes well beyond the bare schema and gives agents everything needed to populate the arguments correctly.

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 opens with a specific verb and resource: 'Pin or unpin a saved optimizer or scenario run.' It clearly identifies the action and the two artifact types, and this is distinct from sibling tools such as run_scenario, get_scenario_results, and update_run. It is not a tautology and names the exact operation being performed.

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 description gives clear usage context by stating the tool is 'declarative and idempotent' and that 'scripts can safely re-run it,' which helps agents decide when repeated invocation is safe. It does not explicitly name alternatives or state when not to use this tool versus update_run, 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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