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Simba MCP Server

Official
by getsimba-ai
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Python
Hybrid

List Runs

list_runs
Read-onlyIdempotent

List paginated optimizer or scenario run history for a model, showing status, metrics, and timestamps to locate past simulations.

Instructions

List a model's saved optimizer or scenario run history.

Returns {model_hash, runs, count, limit, offset}. Each run summary has: run_id, name, auto_named, pinned, notes, tags, status, error_details, progress fields while running, key_metrics (optimizer: total_budget, num_periods, gamma, predicted_revenue/roi, ...; scenario: num_periods, total_planned_spend, predicted_outcome, ...; null metrics are omitted — treat every key as optional), and created/started/completed timestamps. Ordering is pinned-first, then newest-first.

CAVEATS:

  • count is the LENGTH OF THIS PAGE, not the total run count — page until a short page.

  • The optimizer objective ("revenue"/"profit") is NOT in the summary; fetch the specific run (get_optimizer_results with run_id) and read its inputs — profit runs carry objective: "profit" there, revenue runs omit the key.

Use get_optimizer_results / get_scenario_results with a run_id to fetch a listed run's full inputs and results; update_run / set_run_pinned to curate it.

Args: artifact: "optimizer" (run ids "opt_...") or "scenario" ("scn_..."). model_hash: Hash of the model whose run history to list. limit: Page size (API clamps to 1-200; default 50). offset: Rows to skip (paging).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
artifactYes
model_hashYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "list_runsDictOutput",
+  "type": "object"
+}
  2. First observedv0.3.2

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses important behavior: count is only the page length, ordering is pinned-first then newest-first, null metrics are omitted, and the optimizer objective is intentionally absent from summaries. These details prevent incorrect assumptions during use.

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 detailed but tightly organized: a clear purpose, a structured return-value breakdown, explicit caveats, and a compact args section. Every sentence provides actionable information, and the caveats are prominently separated rather than buried.

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

Completeness5/5

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

The description covers the operation's scope, return shape, field semantics, paging pitfalls, missing-data caveats, and relationships to sibling tools. Even with an output schema present, it supplies enough context for an agent to call the tool correctly without further exploration.

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%, but the description fully compensates: artifact is explained with expected prefixes ('optimizer' for 'opt_...', 'scenario' for 'scn_...'), model_hash is defined as the model whose history to list, limit includes clamping behavior and default, and offset explains paging. This adds meaningful semantic value absent from the schema.

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: 'List a model's saved optimizer or scenario run history.' It clarifies this is a listing operation that returns run summaries, not full results, which distinguishes it from sibling tools like get_optimizer_results and get_scenario_results.

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

Usage Guidelines5/5

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

The description explicitly routes the agent to alternatives: 'Use get_optimizer_results / get_scenario_results with a run_id to fetch a listed run's full inputs and results; update_run / set_run_pinned to curate it.' It also provides paging guidance with the caveat to page until a short page, making the intended usage clear.

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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