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

With no annotations, the description carries the full load and does well: it declares 'Free, read only', states every number is read from a chain, and discloses failure behavior ('if a read fails the answer says so'). It also warns that a Tokyo job line reflects a second-opinion grade rather than a certification of the original report, which is real semantic context. It stops short of describing output shape or how the two optional params combine.

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 useful content (counters, decision fields, optional wallet/job, read-only, failure disclosure) is front-loaded reasonably, but roughly half the text is setting flavor and parenthetical asides (docs URL, 'the bar the chain needs (70 for a grade or ruling)'). The caveat sentence is valuable; the framing is not.

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 an unannotated aggregate-read tool with no output schema, the description covers what is returned and its safety profile well enough to call it. The main gaps are the output structure and how the optional parameters compose, but nothing essential is missing.

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%, so both parameters are already documented, and the description's 'give wallet' / 'give job' phrasing only restates the schema. The one addition is the interpretation of a job line as a grade of a second-opinion task, which helps but does not substantially extend parameter meaning. Baseline 3 is appropriate.

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 the specific resource and the concrete payload: BrainChain counters (jobs posted, paid, refunded, decisions, USDG paid), latest decisions with Jev's confidence, an optional wallet record, and Tokyo job lines. It is a read-aggregate tool, distinguishable from siblings like city_state or reputation once parsed. It loses a point because the verb-and-payload statement is wrapped in 'nervous system / Upper City' framing and never explicitly contrasts itself with the many sibling read tools.

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 implies optional filtering by wallet and job ('give wallet', 'give job') but gives no when-to-use guidance and no alternatives. An agent cannot tell from this text whether to call nerve_center or city_state / record / job_thread for overlapping data.

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