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Generate an AI fix for an OptiQra issue

optiqra_ai_fix

Generate a suggested fix for a single issue from an OptiQra report. Send the issue and your AI provider API key to receive a concrete remediation step.

Instructions

Given a single issue from an OptiQra report (as produced by optiqra_analyze), asks an AI provider to generate a suggested fix. Requires an API key for the chosen provider — OptiQra forwards it directly to that provider and never stores it server-side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issueYesThe issue object (from an optiqra_analyze report) to generate a fix for.
modelNoOptional specific model name to use for that provider.
apiKeyNoAPI key for the chosen provider. Optional if OPTIQRA_PROVIDER_API_KEY is set in this server's environment.
providerYesAI provider to use for this request.
Behavior4/5

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

With no annotations, the description discloses important behavioral traits: the API key is forwarded directly to the provider and never stored server-side. This addresses security/privacy behavior. However, it does not mention other behaviors like error handling, cost, or whether the fix is returned vs. persisted, which would add further transparency.

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 two sentences, front-loaded with the core purpose, and includes critical context (input provenance, API key handling) without redundancy. Every sentence earns its place.

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?

The description covers purpose, input source, authentication, and privacy for a tool with no output schema or annotations. It could be more complete by outlining the expected response structure, but the essential context for invoking the tool is present.

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 100%, so the schema fully documents all four parameters. The description only states that an API key is required, which slightly overlaps with the schema's note that apiKey is optional if an environment variable is set. It adds no new semantic meaning beyond the schema.

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 uses a specific verb ('generate a suggested fix') and identifies the resource (a single issue from an OptiQra report). It clearly distinguishes from siblings by specifying it operates on output from optiqra_analyze, while siblings like optiqra_ai_test and optiqra_ai_insights serve different purposes.

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?

It provides clear context on when to use: after optiqra_analyze produces an issue, and mentions the API key prerequisite. It does not explicitly state when not to use or name alternatives, but the sibling list and the description's provenance reference imply appropriate usage.

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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