memory_lesson_save

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

With no annotations, the description carries the full burden and does so well: it discloses upsert semantics ('matching normalized content strengthens the existing lesson and merges support/tags; otherwise creates one'), validation scope, and the return shape with action values. It stops short of permissions, rate limits, or failure modes, which keeps it from a 5.

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 purpose and scope, then provenance, then behavior, then sibling routing. Dense but every sentence earns its place; slightly packed but not wasteful.

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 7-parameter mutation tool with no annotations and no output schema, the description covers behavior, return shape, and sibling routing adequately. Only auth/permission expectations are unaddressed.

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 coverage is 100%, so the schema already documents all seven parameters (baseline 3). The description adds genuine meaning beyond the schema by stating that 'sources pairs are preferred' over sourceIds and that both are 'validated in that project', clarifying the precedence between the two provenance inputs.

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 and resource ('Persist a reusable lesson') plus scope ('in an exact project'), and explicitly names siblings it is not (memory_save, memory_lesson_recall). An agent can distinguish it from the other lesson/memory tools without opening any schema.

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?

Provides explicit routing: 'Use memory_save for decisions/preferences, and memory_lesson_recall before applying earlier lessons.' This gives both the alternative tool and the condition that selects it, leaving nothing to inference.

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