Get today's bird observatory summary with per-species detection counts and first/last heard times. Use it for daily briefings or answering what happened today.
Get an aggregate summary of today's observatory activity: per-species detection counts plus first and last heard times. Use for daily briefings or 'what happened today' questions.
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Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior, so no contradiction exists. The description adds transparency about the content returned (per-species counts and time ranges), which goes beyond the annotations and helps the agent anticipate output. This additional context earns a solid score.
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 concise, using two short sentences to convey the tool's purpose and use cases without unnecessary fluff. It is well-structured, front-loading the core function and then providing context. Every word adds value, making it highly efficient.
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 the tool's simplicity (no parameters) and the richness of the schema annotations, the description fully covers what the agent needs to know. It specifies the output content (per-species counts, first/last heard times) and the intended scenarios ('daily briefings', 'what happened today'), making it complete. The absence of an output schema is not an issue here as the description fills that gap.
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?
The tool has zero parameters, so the baseline score of 4 applies. The description correctly omits parameter details since none exist, and the schema provides full coverage at 100%. No additional semantic explanation is needed, but the score reflects the baseline for parameterless tools.
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's purpose with a specific verb ('Get'), resource ('aggregate summary of today's observatory activity'), and scope (per-species detection counts, first/last heard times). It distinguishes itself from sibling tools by its unique focus on daily summary aggregates, and the mention of use cases further clarifies its intent.
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 provides usage guidance by stating 'Use for daily briefings or 'what happened today' questions,' making it clear when to deploy this tool. It also implies when not to use it (e.g., for detailed per-detection queries, which are covered by other siblings), though it doesn't name alternatives directly, but the explicit use cases are sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.