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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond those annotations: the generated URL is only reachable from the same network as the clips server, and this tool returns a URL rather than inline data. This is useful and does not contradict the annotations.

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 three sentences with no filler. It front-loads the core action and output, then states the network caveat, then gives the routing instruction to the sibling tool. Every sentence earns its place.

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 simple URL-resolution tool with rich annotations and full schema coverage, the description is complete. It explains what is returned, flags a critical network limitation, and points to the appropriate alternative when inline data is needed. No important guidance is missing for an agent to select and use it correctly.

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 input schema already documents both clip_name and detection_date in sufficient detail. The description does not add substantial semantic information about the parameters beyond what the schema provides, so the baseline score of 3 applies.

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 states a specific verb ('Resolve'), a specific resource ('a detection's audio clip (.wav)'), and the output form ('full HTTP URL'), with the purpose of sharing or embedding. It also distinguishes itself from the sibling get_audio_clip_base64, so an agent can clearly tell what this tool does.

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 names the alternative tool get_audio_clip_base64 and gives the exact condition for choosing it: when the audio data must be returned inline to the model. It also conveys a constraint on URL reachability, which helps an agent decide whether this tool is appropriate for a given context.

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

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

Goes well beyond annotations by disclosing the severe token cost (350k-500k per 15s clip) and warning about appropriate invocation frequency. This is crucial behavioral context for an AI agent deciding whether to call the tool, and it complements the readOnlyHint and idempotentHint without contradicting them.

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?

Every sentence serves a distinct purpose: what the tool does, why it exists, a critical warning, and a pointer to the lighter alternative. No filler, and the most important operational caution (token size) is front-loaded.

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 simple two-parameter download tool with no output schema, the description covers the essential behavioral aspects: output format, cost implications, usage frequency constraints, and the alternative. Everything an agent needs to decide whether to invoke this tool and how to do so safely is present.

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% and both parameters are adequately documented in the schema itself. The tool description adds no additional parameter-level detail, which is acceptable given the schema already explains clip_name and detection_date thoroughly. 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?

States a specific verb ('Download'), a specific resource (detection's .wav audio clip), and a specific output format (base64-encoded). This makes the tool's purpose unambiguous and clearly distinguishes it from the sibling get_audio_clip by explaining what makes this version different (direct audio input for multimodal models).

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?

Provides explicit usage guidance: use for single-clip verification only, never in high-frequency or scheduled workflows, and names the alternative get_audio_clip for when a lightweight shareable URL is sufficient. These are clear when-to-use and when-not-to-use instructions.

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

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

Annotations already cover read-only, idempotent, non-destructive, and open-world behavior, so the bar for additional disclosure is lower. The description adds useful context about the return contents (weather, confidence, audio URL). It does not mention potential edge cases such as missing detections or whether the audio URL requires further authentication, but this is acceptable given the annotation coverage.

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 two sentences with no filler. The first sentence front-loads the core action, resource, and ID source; the second sentence gives a clear usage trigger. Every piece of information earns its place.

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 single-parameter lookup tool with no output schema, the description provides the essential information: what the tool does, what it returns, where the ID comes from, and when to use it. It could be slightly more explicit about the response shape or error behavior, but the description is sufficient for an agent to invoke the tool correctly.

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% and the single 'id' parameter is well-described in the schema as a numeric detection ID returned by get_recent_detections or search_detections. The description reinforces this same information but does not add significant new semantic detail beyond the schema, so the baseline score of 3 applies.

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 states a specific verb ('Get'), a specific resource ('comprehensive details for a single detection'), and the key identifier (numeric ID). It also lists the specific content returned (weather conditions, confidence score, audio clip URL), making the tool's purpose both concrete and distinguishable from sibling tools focused on audio clips, summaries, and list searches.

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 clearly indicates when to use the tool: 'Use after an interesting detection ID has been identified.' It also specifies how to obtain the ID, from get_recent_detections or search_detections. It does not explicitly name alternatives or exclusion cases, but the contextual guidance is strong enough for an agent to select this tool appropriately.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, clearly establishing safe read-only behavior. The description adds no further behavioral details, but with annotations present, the bar is lower for additional context. The tool has no side effects, so the annotation coverage is sufficient.

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 two sentences, direct, and free of extraneous detail. It states the function and the intended use without redundancy, achieving high clarity in minimal length.

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?

The description provides a complete definition and clear use cases, allowing an agent to decide when to call this tool. Since it is a read-only list with no parameters and the sibling tools are differentiated, no further context is needed.

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 there is nothing to explain. The schema coverage is 100% (empty object), and the description does not need to add parameter meaning. This dimension is trivially satisfied.

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 lists species detected for the first time ever or newly arrived this season/year, providing a specific verb (list) and resource (species). It distinguishes itself from siblings like get_recent_detections and get_today_summary by focusing on new arrivals rather than all recent activity.

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 explicit use cases: 'Use this to spot migration events, rare visitors, or new residents.' This tells the agent when to invoke the tool, though it does not explicitly contrast with sibling tools. However, the purpose clarity already differentiates it from alternatives.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds useful behavioral context beyond the annotations by noting that output is capped at 8KB to protect the agent context window and by listing typical return fields.

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 and well-structured: purpose first, then return contents, then explicit sibling-tool routing, then the output cap note. Every sentence adds value and there is no redundancy.

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 moderate complexity (three optional parameters, no output schema), the description is largely complete: it states the resource, the return fields, the primary use case, and a system constraint (8KB cap). It does not explicitly mention error behavior or empty results, but the 'most recent' wording and output cap cover the main operational context an agent needs.

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% and every parameter has its own description with defaults and bounds (limit, species_code, min_confidence). The description does not need to add much, and it does not; it provides no extra semantic information beyond the schema.

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 a specific action ('Retrieve the most recent bird acoustic detections') and a specific resource ('BirdNET-Go observatory'), and it lists the returned data fields. It also differentiates itself from sibling tools by naming search_detections and get_today_summary for other use cases.

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 explicit when-to-use guidance: 'Use this as the primary tool for "what birds were heard recently?" questions' and directs users to search_detections for historical lookups and get_today_summary for aggregates. This removes ambiguity about tool selection.

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

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds the 'real-time' nature of the data and the concrete telemetry fields, which gives the agent useful expectations beyond the annotations. No contradictions or hidden side effects are indicated.

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?

Two sentences with no filler: the first front-loads what the tool returns, and the second clarifies when to use it. Every sentence earns its place and the structure is easy to scan.

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, the description appropriately lists the returned telemetry content and explains a concrete use case. The absence of an explicit response format or caveats is a minor gap, but zero required parameters and strong annotations keep this sufficiently complete.

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 takes zero parameters and schema description coverage is 100%, so there is no parameter-documentation burden. The description is not required to explain inputs and adds no irrelevant parameter detail; the baseline of 4 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 uses a specific verb ('Get') with a clear resource ('real-time health telemetry for the monitoring station') and enumerates the included metrics. None of the sibling tool names overlap with health-telemetry scope, so it is immediately distinguishable.

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 explicitly states the diagnostic scenario ('silent station or missing detections') and gives ordering guidance ('before other tools'). It does not name alternatives or state when not to use it, but the intended context is clear enough for an agent to select it appropriately.

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

Does 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.

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context by clarifying that this searches historical records rather than live activity and by requiring YYYY-MM-DD dates. It does not describe result ordering or pagination, but the schema's limit parameter and the safety annotations keep this a minor omission.

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?

Three short sentences with no fluff: the action and resource come first, usage context and the sibling alternative follow, and the format constraint is stated plainly. Every sentence earns its place.

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 read-only, idempotent search tool with 0 required parameters and no output schema, this description covers purpose, when to use it, the key alternative, and the required date format. It stops short of describing the return value structure or ordering, but that is a modest gap given the rich annotations and fully documented params. The phrase 'date range' is slightly underspecified since the schema only exposes a single date parameter.

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 baseline is 3; the schema already documents each parameter's format and defaults. The description reinforces the same filters ('date, species name/code, and minimum confidence') but adds little semantic value beyond the schema, aside from emphasizing the date format.

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 'Search historical detection records by date, species name/code, and minimum confidence,' naming a specific verb, resource, and the exact filter dimensions. It also explicitly contrasts with get_recent_detections, so the agent can distinguish this history search from the latest-activity sibling without inspecting schemas.

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 states the exact conditions for use ('specific day, date range, or species across history') and names the alternative for the excluded case ('For the latest activity use get_recent_detections instead'). This is an explicit when/alternative routing with nothing left to inference.

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