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extract

Extract a named subsystem from EN source code to create standalone EN source code for structural analysis.

Instructions

Extract a named subsystem as standalone EN source code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesEN source code describing the system
subsystemYesName of the subsystem to extract

Implementation Reference

  • Registration and handler implementation for the 'extract' tool. It calls the generic callApi helper to communicate with the EN API.
    server.tool(
      "extract",
      "Extract a named subsystem as standalone EN source code.",
      {
        source: z.string().describe("EN source code describing the system"),
        subsystem: z.string().describe("Name of the subsystem to extract"),
      },
      async ({ source, subsystem }) => {
        const result = await callApi("extract", { source, subsystem });
        return {
          content: [{ type: "text" as const, text: result.text }],
          isError: result.isError,
        };
      }
    );
Behavior2/5

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

No annotations are provided, so the description carries full burden. While 'extract' implies a read operation, it doesn't disclose whether this modifies the source, requires specific permissions, has rate limits, or what happens if extraction fails. For a tool that presumably transforms source code, this lack of behavioral context is significant.

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 a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the core purpose, making it easy for an agent to quickly understand what the tool does.

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

Completeness3/5

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

Given the tool's apparent complexity (extracting subsystems from source code), lack of annotations, and no output schema, the description is minimally adequate. It states what the tool does but doesn't provide enough context about behavior, output format, or usage scenarios to be truly complete for this type of operation.

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?

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any meaning beyond what the schema provides about 'source' and 'subsystem' parameters. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 action ('extract') and the target ('named subsystem as standalone EN source code'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from its many siblings (like 'analyze_system', 'compose', 'detail', etc.), which appear to operate on similar EN source code systems.

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 versus alternatives. With 11 sibling tools that likely work with EN source code systems, there's no indication of what problem this tool solves that others don't, nor any prerequisites or context for when extraction is appropriate.

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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