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codecalc

by The-40-Thieves
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Python
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Session Start

session_start

Start a persistent session for code execution. Python/Node gain stateful REPL preserving variables and imports; other languages receive a persistent workspace directory. Returns session ID.

Instructions

Start a persistent session. python3/node get a stateful REPL worker (variables/imports persist across execute_code calls); other languages get a persistent workspace directory. Returns session_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoLanguage for the new session's worker/workspace; default 'python3' gets a stateful REPLpython3

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.0
    • addedInput schema / properties / language / description
      Added value: +"Language for the new session's worker/workspace; default 'python3' gets a stateful REPL"
  2. Changed1 schema field changedv0.11.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "session_startDictOutput",
+  "type": "object"
+}
  3. Changed4 schema fields changedv0.2.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / language / title
      Added value: +"Language"
    • addedInput schema / title
      Added value: +"session_startArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "type": "object"
-}New value: +null
  4. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=false (not read-only) and destructiveHint=false; the description adds concrete behavior: persistence across execute_code calls and language-specific workspace creation. It does not explicitly warn about resource lifecycle, but the persistent aspect is transparently stated.

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?

Two sentences with no filler. The primary effect (persistent session) is front-loaded, and language-specific details and return value are packed efficiently. Every clause adds value.

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?

With one optional parameter, a generated output schema, and no nested objects, the description is complete for calling this tool correctly. It explains what is returned (session_id) and the exact behavior for the parameter, leaving nothing essential missing.

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

Parameters4/5

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

The schema already provides 100% coverage for the single 'language' parameter, including its default. The description enriches semantics by explicitly stating that python3/node get a stateful REPL while other languages get a persistent workspace, adding meaning beyond the schema's generic wording.

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 a specific verb and resource: 'Start a persistent session.' It clarifies language-specific behavior (python3/node get stateful REPL worker; other languages get a persistent workspace directory) and states it returns session_id, fully distinguishing it from siblings like session_stop or execute_code.

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?

It implies when to use this tool by noting variables/imports persist across execute_code calls and mentions persistent workspace, indicating it should be used when cross-call state is needed. It does not explicitly state when not to use it (e.g., one-off code runs), but the distinction from execute_code is reasonably 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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