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GIGAParviz
by GIGAParviz

log_solution

Record a problem and its solution to prevent repeated debugging, optionally including error text and tags for future reference.

Instructions

Record a problem that was hit and its fix (build failures, weird bugs, env issues), optionally with raw error output, so nobody debugs it twice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
filesNo
problemYes
solutionYes
error_textNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates a write operation ('Record') but does not explain side effects, storage behavior, deduplication, or how the record integrates with other memory tools. It also omits details about the optional tags and files parameters, leaving significant behavioral ambiguity for a mutation tool.

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, concise sentence that front-loads the core purpose and the key benefit. Every word contributes to understanding the tool's role, with no redundancy or filler. It is appropriately structured and immediately informative.

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?

Despite using a sentence that captures the essence, the description is incomplete for a tool with 5 parameters and no annotations. It fails to explain tags and files, provides no usage guidance against siblings, and lacks behavioral details about the recording process. The presence of an output schema reduces the need to describe return values, but the description still leaves significant gaps in what an agent needs to invoke it correctly.

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%, so the description must compensate. It clarifies 'problem' and 'fix' (solution) and maps 'raw error output' to error_text, covering the required parameters and one optional. However, tags and files are completely unexplained, leaving the agent to infer their purpose from the schema alone. The description adds some semantic value but does not fully compensate for the coverage gap.

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 tool's purpose: recording a problem and its fix to avoid re-debugging. It uses a specific verb ('Record') and identifies the resource ('a problem and its fix'). However, it does not differentiate from sibling tools like save_gotcha, save_pattern, or log_decision, which have overlapping functions. The mention of 'raw error output' hints at error_text but leaves tags and files unmentioned.

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 implies the tool should be used when a problem is encountered and solved ('so nobody debugs it twice'), but it provides no explicit guidance on when to choose this over alternatives. It also does not state any exclusions or prerequisites, leaving the agent to infer usage context without clear direction.

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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