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lessons

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Capture lessons from pipeline runs and retrieve them by category or tags to apply proven patterns.

Instructions

Pattern Library & Learnings Engine — capture and retrieve patterns across pipelines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYescapture: save a new learning | retrieve: search existing learnings
tagsNoTags to search for
categoryNoLearning category to filter by
market_nameNoPipeline name for context
Behavior1/5

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

The description indicates both capture and retrieve actions, but annotations declare readOnlyHint=true, implying read-only. This is a direct contradiction. The agent cannot determine if writes are allowed.

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 conveys the core functionality without extraneous text.

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?

No output schema is provided. The description does not explain what is stored when capturing or what is returned when retrieving. Combined with the annotation contradiction, the agent lacks necessary context.

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% with clear param descriptions. The tool description adds no extra semantic value, so baseline 3 is appropriate.

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 it's a pattern library and learnings engine that captures and retrieves patterns. The verb-resource pair (capture/retrieve patterns) is explicit. However, it does not differentiate from sibling 'capture_learning', missing some precision.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. The mode enum in the schema hints at usage, but the description itself lacks context about when to capture vs retrieve or comparisons with siblings.

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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