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unlock_solution

Retrieve complete solutions with problem descriptions, fixes, and working code when find_solution returns partial results. Submit feedback after applying the unlocked solution.

Instructions

Retrieve the full solution body for a matched result from find_solution. Best for: When find_solution returned a match but the solution_body field is missing or empty. Returns: The complete solution with problem description, fix, and working code. Important: After applying the unlocked solution, you must call submit_feedback to rate whether it worked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
solution_idYesThe solution ID from find_solution results.
Behavior4/5

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 key behavioral traits: it retrieves data (implied read-only, though not explicitly stated), specifies the return content ('complete solution with problem description, fix, and working code'), and outlines a required follow-up action ('call submit_feedback'). However, it doesn't mention potential errors, rate limits, or authentication needs, leaving some gaps.

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 front-loaded with the core purpose, followed by specific usage guidelines and return details in a bullet-like structure. Every sentence adds value without redundancy, making it efficient and well-organized for quick comprehension.

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?

Given the tool's moderate complexity (retrieval with a follow-up requirement), no annotations, and no output schema, the description does well by explaining the purpose, usage, return content, and post-action. However, it lacks details on error handling or output structure, which could be useful for an agent, slightly reducing completeness.

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 description coverage is 100%, so the schema already documents the single parameter 'solution_id' adequately. The description adds minimal value beyond the schema by referencing 'solution ID from find_solution results,' which provides context but no additional syntax or format details. This meets the baseline for high schema coverage.

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 clearly states the tool's purpose with specific verbs ('retrieve the full solution body') and resources ('for a matched result from find_solution'). It explicitly distinguishes from its sibling find_solution by addressing when find_solution's output is incomplete, making the purpose distinct and well-defined.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('When find_solution returned a match but the solution_body field is missing or empty') and names an alternative action ('call submit_feedback') for post-use steps. It clearly differentiates usage from find_solution and links to other tools, offering comprehensive context.

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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