Scan MQL source files for deprecated functions and syntax. Replaced by analyze_mql(source, checks=['deprecated']).
DEPRECATED (removed in 0.6.0): use analyze_mql(source, checks=["deprecated"]).
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | Absolute Windows path to the .mq4/.mq5/.mqh source file. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.5.0Input schema / properties / source / descriptionAdded value: +"Absolute Windows path to the .mq4/.mq5/.mqh source file."Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "title": "check_deprecatedDictOutput",
+ "type": "object"
+}v0.4.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the tool is removed in 0.6.0, which is useful behavioral context beyond annotations because it warns that execution should be avoided. It does not describe the old tool's behavior, but that is unnecessary for a deprecated stub.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one compact sentence, front-loaded with DEPRECATED and ending with the precise replacement call. Every part earns its place and there is no filler or redundant restatement of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a deprecated tool, the context is complete: annotations cover safety, the schema covers the parameter, and the description names the replacement and the removal version. An output schema exists, so return-value documentation is not needed. An agent has everything required to decide how to handle this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents the single parameter as an absolute Windows path to a .mq4/.mq5/.mqh source file, so schema coverage is 100%. The description only references the source argument in the replacement call and adds no new parameter-level semantics. The baseline of 3 is appropriate because the schema already carries the meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description immediately marks the tool as DEPRECATED and removed in 0.6.0, making its status unmistakable. It then names the exact replacement call, analyze_mql(source, checks=['deprecated']), which distinguishes it clearly from the analyze_mql sibling and tells the agent not to select this tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use analyze_mql(source, checks=['deprecated']) instead, leaving no ambiguity about when this tool should be used: never. It provides both the exlusion condition (deprecated/removed) and the exact alternative with required arguments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.