Brain lens — machine-readable views of a brain (freshness · provenance · activity · timeline · orrery · unresolved)

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

With no annotations, the description carries the full burden and does well: it states the tool is read-only and never writes, explains that timeline events are only included for the timeline view, and describes the structured payload size and the structured default behavior. Minor gaps remain around error behavior, but the key safety and return-shape traits are disclosed.

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?

The description is long but densely informative, covering the main purpose, each view, key defaults, and usage. It is front-loaded with the core concept and every major clause contributes. Slight redundancy like 'Read-only by construction — it never writes' could be tightened, but it does not bloat the text.

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?

Given there is no output schema and no annotations, the description gives enough detail for an agent to call the tool correctly: it explains what each view returns, how root and structured behave, and what question types the tool answers. The markdown vs. structured output distinction is also addressed.

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 baseline is 3. The description adds valuable meaning beyond the schema for root (card title prefix or id, defaults to most-connected hub), view (events omitted unless timeline), and structured (large payload, default false, historical behavior). This exceeds the baseline.

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 clearly states the tool returns one structured payload of brain lens views and enumerates what each view contains (freshness, provenance, activity, timeline, orrery, unresolved). It distinguishes itself as the read-only data twin of the desktop Brain Lenses, making its role distinct from sibling tools like brain_ask or brain_connect.

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 explicit use cases: "what's rotting / who wrote this / what happened this week / what's around X / what's undecided" or feeding a UI. It does not explicitly name alternatives or state when not to use this tool, but the described intents provide clear guidance.

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