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AILANG Executor

by io.github.sunholo-data
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Evaluate an AILANG expression

ailang_eval
Read-onlyIdempotent

Evaluate one pure AILANG expression and print it with show(). Builtins are in scope; for stdlib functions (map, filter, ...) use ailang_run with explicit imports.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "expression": "<expression>"
    },
    "name": "ailang_eval"
  }
}

Input Schema

NameRequiredDescriptionDefault
expressionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful behavior beyond annotations: evaluation prints via show(), only builtins are in scope, and expressions must be pure. It does not describe error behavior, but the added context is meaningful.

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 short sentences, front-loaded with the core operation and followed by the key routing constraint. Every sentence earns its place with no redundant wording.

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?

For a simple one-parameter evaluation tool with full safety annotations and no output schema, the description covers the essential operation, scope, output behavior via show(), and the stdlib limitation. It could say more about error handling, but it is complete enough for correct invocation.

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 0% for the single expression parameter, so the description must carry the semantic load. It clarifies that the input is one pure AILANG expression and that builtins are available, but it gives no syntax examples or restrictions on expression form. This is adequate but not rich.

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: evaluate one pure AILANG expression and print it with show(). It also distinguishes the tool from ailang_run by limiting scope to builtins and redirecting stdlib usage. An agent can identify the tool's role without opening the schema.

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 routing guidance: use ailang_run with explicit imports for stdlib functions such as map and filter. It does not mention ailang_check or other validation alternatives, but it does provide an explicit when-not for the most relevant sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All AILANG Executor toolsInspect
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