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get_training_suggestions

Fetches pending AI training suggestions generated by automatic error detection, allowing owners to review and decide on workflow or prompt changes.

Instructions

Get AI Training Suggestions — List pending AI improvement suggestions generated by the automatic error detection system. These are proposed changes to workflows or the shop prompt that need owner review. [query]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by status: pending, applied, dismissed. Default: pending
Behavior4/5

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

With no annotations, the description carries the full burden. It correctly indicates a read-only operation ('list pending') and mentions the automatic error detection system. It doesn't disclose any side effects, but none are expected.

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 concise, two sentences, with no unnecessary words. It front-loads the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is adequate for a simple list operation with no output schema. However, it lacks information about the return format or fields in each suggestion, which would improve 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 only parameter 'status' is fully described in the schema (filter by status with default). The description adds no additional meaning beyond the schema, which has 100% 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: listing pending AI improvement suggestions from the automatic error detection system. It distinguishes from sibling tools like apply_training_suggestion and dismiss_training_suggestion.

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?

The description explains that these are suggestions needing owner review, implying when to use. It doesn't explicitly state when not to use or mention alternatives, but the context is clear.

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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