User context

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered. The description adds the useful detail of what the payload contains (role, stack, interests, exclusions, project context), which matters because there is no output schema, but it says nothing about freshness, caching, or empty-result behavior.

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?

Two sentences, no waste. The content listing comes first and the invocation guidance second, which is the right front-loading for a tool meant to be called early.

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 read-only tool with two optional boolean flags, the description covers purpose, contents, and invocation timing, and the absence of an output schema is offset by the enumeration of returned context categories. Minor gaps remain around what happens when context is missing for a new user.

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 100% and both parameters (include_ace, include_learned) are documented with defaults in the schema. The description never mentions either toggle, so it adds no meaning beyond the structured fields; baseline 3 applies.

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 resource (the user context that 4DA holds) and enumerates its contents: role, tech stack, interests, exclusions, detected project context. It is clear what the tool returns, but it does not distinguish itself from siblings such as what_should_i_know or agent_memory, which also surface user-relevant knowledge.

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?

It gives an explicit trigger and priority: 'Call FIRST when you need to know what the user works on before answering or recommending.' That tells the agent both when to reach for it and that it should precede other calls. It stops short of naming an alternative or a when-not-to-use condition.

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