Learning Context

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

With no annotations present, the description carries the full behavioral burden. It discloses that this is a read-style search operation, that results are filtered by project and task relevance, that it uses hybrid search, and that citations are included. This is meaningful behavioral transparency, though it omits details like pagination or any limits on result size.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence communicates scope, filtering behavior, and output characteristic ('with cites') with no filler. The 'ONLY' qualifier is front-loaded, immediately telling the agent what is excluded. Every word earns its place.

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

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

The core purpose and two required parameters are covered, and the presence of an output schema reduces the need to describe return values. However, with no annotations and three undocumented optional parameters, an agent cannot fully determine how to tune the search (e.g., what max_distance affects or when to enable embeddings). The description is adequate but not complete for confident invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 for all parameters. It explains 'project' and 'tarea', the two required parameters, fairly well. However, 'limit', 'max_distance', and 'with_embeddings' receive no explanation, and their roles are not inferable from 'hybrid search' alone. This leaves significant parameter ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Returns'), a specific resource ('lessons'), and precise scoping ('of the given project applicable to the tarea'). The parenthetical adds a concrete mechanism ('hybrid search filtered by project, with cites'), making the tool's role unambiguous among siblings.

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

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

The emphasis on 'ONLY lessons applicable to the tarea' implies this tool is for task-scoped lesson retrieval, which gives some context for when to use it. However, it does not explicitly state when not to use it or name alternatives like 'search' or 'solutions', leaving the agent to infer the boundary between this tool and its siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.