context_snapshot

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

No annotations are supplied, so the description carries the full behavioral disclosure burden, and it discloses almost nothing. It does not say the call is read-only (only implied by '快照'), whether the data is live or cached, how fresh the weather and shuttle data are, whether results are scoped to the current user, or how 'level' changes breadth or depth. For a tool that aggregates six data sources, omitting what actually happens at each level is a meaningful gap.

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?

A single compact line with a label, a colon, and a slash-delimited content list has no wasted words, and the resource name is front-loaded. The format is scannable and dense, but here the extreme terseness comes at the cost of use-case guidance, so the size is efficient while still being incomplete.

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?

With no output schema and no annotations, the description must carry both what is returned and how it behaves, and it only lists field topics. It does not explain the output shape at each verbosity level, which is essential because 'level' implies the returned structure varies. Compared with the tool's aggregation complexity, the definition is under-specified.

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%: the single 'level' parameter has an enum (terse/normal/verbose) and a default of 'normal' documented in the schema. The description adds nothing about how each level changes the snapshot, such as terse returning only date/week versus verbose including todos. Per the high-coverage baseline, a 3 is appropriate, but the missing per-level detail is the one thing only the description could supply.

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 resource (「此刻西湖」快照) and enumerates exactly which data categories are bundled: date, week number, academic calendar events, shuttle, weather, and todo deadlines. This tells an agent more than a generic name would, and no single sibling tool covers all of these categories. The only shortfall is that it is a noun phrase with no verb, so it never explicitly says it 'returns' or 'collects' these items.

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 gives no when-to-use guidance, no 'use this instead of calendar_today / transit_next / canvas_todo' routing, and no conditions that set it apart from the many sibling tools that cover the same data individually. An agent likely finds out that this is an all-in-one overview tool only by inference from the content list. The 'level' parameter, which controls how much data is returned, is never connected to a usage decision.

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