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track_enhancement

Record an original and enhanced prompt pair with generator to train the community graph with real A/B data, contributing to creative patterns and benchmarks.

Instructions

Record a before/after enhancement pair in the Dali graph.

Call this after you've written an enhanced prompt using the rewrite brief from enhance_prompt. This trains the community graph with real A/B data — contributing to creative_patterns and community_benchmark for all users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
generatorYesTarget generation model
enhanced_promptYesThe version you actually improved
original_promptYesThe un-enhanced prompt

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Despite no annotations, the description discloses that the tool trains the community graph and contributes to creative_patterns and community_benchmark, which are significant behavioral traits. It could mention immutability or rate limits but is still informative.

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?

Two concise sentences with no redundancy. The first sentence states the core action, the second provides execution context and impact, earning 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?

Given the tool has an output schema (so return values are documented elsewhere), the description is complete: it specifies when to call, what it does, and the broader contribution. Minor gap: no mention of constraints like required authentication or data limits.

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 coverage is 100%, so the schema already describes all parameters. The description adds no extra meaning beyond mapping 'before/after' to original and enhanced prompts, so baseline 3 applies.

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 records a before/after enhancement pair in the Dali graph, distinguishing it from siblings like enhance_prompt (which creates the enhancement) and community_benchmark/creative_patterns (which are outcomes).

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?

Explicitly says 'Call this after you've written an enhanced prompt using the rewrite brief from enhance_prompt,' providing clear when-to-use guidance and implying not to call without prior enhancement.

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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