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turingmindai

TuringMind MCP Server

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by turingmindai

turingmind_apply_fix

Records a repair action applied to a failed SpecNode and resets its stage to trigger re-verification. Call after applying a code patch, spec refinement, test expansion, or unblocking dependency.

Instructions

Record that a repair action was applied to a failed SpecNode. Resets the node stage so the execution loop re-runs verification. Must be called after the repair action (code patch, test expansion, spec refinement).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idYes
fix_typeYes
descriptionYesWhat was changed
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool resets the node stage and triggers re-verification, implying mutability. It does not mention side effects, idempotency, authorization needs, or what happens on multiple calls, which would be valuable for safe usage.

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 extremely concise, consisting of three short sentences. The first sentence states the purpose, the second explains the effect, and the third provides usage timing. There is no redundant information, and the key points are front-loaded.

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 complexity of three required parameters and no output schema, the description is incomplete. It lacks explanations of how to obtain 'node_id', the exact enum values for 'fix_type', and details about the return value or confirmation. Important edge cases like duplicate calls or error conditions are not addressed.

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

Parameters2/5

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

Schema description coverage is low (33%), with only the 'description' parameter having a schema description. The tool description adds some context by giving examples of fix types ('code patch, test expansion, spec refinement') but does not cover the full enum, and it does not explain 'node_id' or the exact enum values like 'unblock_dependency'. Thus, it adds limited value beyond the schema.

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 it records a repair action applied to a failed SpecNode and resets the node stage. The verb 'record' and the specific resource 'SpecNode' provide a clear purpose. However, it does not explicitly distinguish from sibling tools like 'turingmind_apply_edit' or 'turingmind_apply_spec_delta', which might be confused with applying fixes directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Must be called after the repair action', giving clear context on when to use. However, it does not mention when not to use the tool or suggest alternative tools for different scenarios, leaving some guidance gap.

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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