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by maglionejm
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Python
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create_session_tool

Creates a Design Thinking session from a brief. Provide problem space, target segments, success criteria, risk tolerance, and optional files; input paths are validated to permitted roots.

Instructions

Create a Design Thinking session. The brief needs problem_space, target_segments, success_criteria, risk_tolerance, and may declare inputs (repo path, metrics/discussion/document files). Input paths are resolved on the server and confined to the authorized input root(s): traversal, escaping symlinks, and outside absolute paths are refused.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNodojo
nameYes
seedNo
briefYes
modelNo
providerNoanthropic
panel_sizeNo
gate_policyNo
reasoning_effortNo
total_token_budgetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.4.0
    • addedInput schema / properties / model
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Model"
+}
    • addedInput schema / properties / provider
      Added value: +{
+  "default": "anthropic",
+  "enum": [
+    "anthropic",
+    "openai"
+  ],
+  "title": "Provider",
+  "type": "string"
+}
    • addedInput schema / properties / reasoning_effort
      Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "low",
+        "medium",
+        "high"
+      ],
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Reasoning Effort"
+}
  2. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the transparency burden. It discloses that input paths are resolved server-side and restricted to authorized roots, which is a useful behavioral constraint. However, it does not mention side effects like whether a session ID is returned or if persistent state is created.

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 two concise sentences, front-loading the primary purpose and then adding key constraints. There is no redundant or extraneous content, making it highly efficient.

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 the tool has 10 parameters including a nested brief object, the description is undercomplete. It explains the brief's required fields and path restrictions, but omits details about other parameters, expected output, and potential errors, leaving significant gaps for an agent to navigate.

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?

The schema has zero description coverage, so the description must compensate. It explains that the brief requires problem_space, target_segments, success_criteria, and risk_tolerance, and may include input paths. However, it leaves many other parameters (mode, provider, panel_size, gate_policy, reasoning_effort, total_token_budget) without semantic explanation, requiring the agent to rely on names and enums.

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 clearly states the tool creates a Design Thinking session, which is a specific verb and resource. However, it does not explicitly distinguish it from sibling tools like run_session or step_session, so it falls slightly short of a perfect score.

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?

The description provides no guidance on when to use this tool compared to alternatives such as run_session or step_session. There is no indication of the appropriate context or conditions for invoking this tool.

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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