get_learning_summary

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

No annotations are provided, so the description carries the full burden. It discloses the payload contents and the fact that it is a digest read, but says nothing about permissions, caching, or rate limits, and the enumerate-then-'Returns' structure partially duplicates the output schema.

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?

Front-loaded with the core verb and resource, followed by content enumeration and a usage note. The trailing 'Returns:' block restates the enumeration already given in sentence two and duplicates the output schema, which is mild waste.

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?

For a no-arg read tool with an output schema present, the description covers purpose, contents, and intended use adequately; return-value structure is correctly left to the schema. The only shortfall is the absence of any behavioral note (auth, freshness) in lieu of annotations.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly avoids inventing parameter detail that does not exist.

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?

States a specific verb ('Get') and resource ('learning summary'), then enumerates the digest contents: streak days, total hours, recent activity, pending labs, next suggested lesson. That enumeration implicitly distinguishes it from siblings like get_course_progress and get_active_labs, though it never names them.

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?

Gives an explicit use case: 'Designed specifically for constructing personalized study schedules.' That tells the agent when to reach for this tool rather than a per-course tool, but offers no when-not condition or named alternative among the eight siblings.

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