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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral context beyond that: closed trades bucket by close day in the journal timezone, open positions count toward any window that reaches today, null metrics are not computable yet (e.g. profitFactorIsInfinite), and compare adds a 'previous' equal-length window. It also discloses the OAuth sign-in requirement. This is strong added context, though it doesn't detail the exact response shape (no output schema exists), so a 4 rather than 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?

The description is dense but well-organized: it front-loads the core purpose and metric list, then covers windowing, compare, nulls, sibling routing, and auth in a logical order. Every sentence adds information. It is slightly long, but the tool is genuinely complex (many metric groups, multiple windowing modes, sibling tools), so the length is justified. A 5 would require even tighter grouping of the metric enumeration.

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 complex read-only dashboard tool with no output schema, the description covers the key things an agent needs: what metrics come back, how windows work, how compare behaves, how nulls are represented, which siblings to use for other questions, and the auth requirement. It does not describe the response structure or pagination, but the metric list is detailed enough to set expectations. The openWorldHint annotation also signals that results may vary, which the description supports with the null-metric note. A 5 would need explicit return-shape or error details.

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 the schema already documents all six parameters. The description adds value beyond the schema by explaining the default window (last 30 days), the semantics of compare ('adds previous — the equal-length window just before'), and the timezone bucketing behavior that affects from/to interpretation. It also clarifies that accounts can be omitted for every account. This exceeds the baseline 3 for full schema coverage.

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 opens with a specific verb and resource ('journal dashboard in one call for a window') and enumerates the exact metric groups returned (performance metrics, Edge Score components, per-day P&L, equity curve, open positions, accounts/settings). It also distinguishes itself from siblings by naming journal_breakdown and journal_list_trades as the tools for different questions. This is a clear, specific definition that an agent can act on.

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?

The description explicitly states when to use this tool versus alternatives: 'Use journal_breakdown for where the P&L comes from and journal_list_trades for the trades themselves.' It also gives concrete usage context: defaults to last 30 days, how to request 'all' or explicit from/to, and the compare behavior. This is explicit routing guidance, not just implied context.

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