eBird MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools have clear purposes but significant overlap exists, particularly among observation-related tools (e.g., get_nearby_observations, get_recent_observations, get_historic_observations, get_notable_observations) and region-related tools (e.g., get_adjacent_regions, get_sub_regions, get_region_info). Descriptions help differentiate them, but an agent might struggle to choose the most appropriate one in some scenarios.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'get_' as the prefix, making them predictable and easy to parse. There are no deviations in naming style, such as mixed cases or varying verb forms, which enhances readability and usability.
Tool Count3/5
With 25 tools, the count is on the higher side for a focused domain like eBird data access, bordering on heavy. While many tools serve distinct functions, the number may overwhelm agents and could indicate potential redundancy or over-specialization in the API surface.
Completeness5/5
The tool set provides comprehensive coverage for birding data, including observations, regions, hotspots, checklists, species, and taxonomy. It supports CRUD-like operations for querying and retrieving data across the domain, with no obvious gaps that would hinder agent workflows or cause dead ends.
Average 3/5 across 25 of 25 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Get observations' but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (since there's no output schema). The description is minimal and lacks critical operational context for a tool with 11 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Get observations from a specific date in history.' It's front-loaded with the core action and resource, with zero wasted words. However, it's arguably too concise given the tool's complexity (11 parameters), leaving out necessary context that could be added in another sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'observations' entail (e.g., biological data), how results are returned, or any limitations. With rich schema but no other structured fields, the description should provide more context to guide effective use, but it falls short.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional meaning beyond implying date-based filtering ('from a specific date'), which is already covered by the required year, month, and day parameters in the schema. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get observations from a specific date in history' clearly states the verb ('Get') and resource ('observations'), but it's vague about what type of observations (e.g., bird sightings, weather data) and doesn't distinguish from siblings like 'get_recent_observations' or 'get_nearby_observations' that also retrieve observations. The purpose is understandable but lacks specificity and differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools for observations (e.g., 'get_recent_observations', 'get_nearby_observations'), the description doesn't specify that this is for historical data by date, nor does it mention prerequisites or exclusions. Usage is implied by the name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Get information') without details on permissions, rate limits, response format, or error handling. This is inadequate for a tool with no structured behavioral hints, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration, earning full marks for brevity and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what information is returned, potential errors, or behavioral traits, which is insufficient for a tool that likely returns detailed hotspot data. More context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with 'loc_id' documented as 'The location code (e.g., 'L99381').' The description adds no additional parameter details beyond this, so it meets the baseline of 3 where the schema handles the heavy lifting without extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Get information about a specific hotspot,' which includes a verb ('Get') and resource ('hotspot'), making it clear. However, it lacks specificity about what information is retrieved and does not differentiate from sibling tools like 'get_hotspots_in_region' or 'get_nearby_hotspots,' leaving it vague in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or comparisons to sibling tools, such as using this for a single hotspot versus 'get_hotspots_in_region' for multiple hotspots, resulting in minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool's function but lacks details on permissions, rate limits, output format, or error handling. For a read operation with no annotations, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is front-loaded with the core purpose and efficiently communicates the tool's function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., list of region codes, names, or details), potential errors, or usage constraints, leaving the agent with incomplete context for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'region_code' documented as accepting country or subnational codes. The description adds no additional meaning beyond this, such as examples or constraints, so it meets the baseline for high schema coverage without compensating further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get regions') and the resource ('adjacent regions'), specifying that they share a border with a given region. It distinguishes from siblings like 'get_region_info' or 'get_sub_regions' by focusing on adjacency rather than general info or hierarchical subdivisions, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_sub_regions' or 'get_region_info', nor does it specify prerequisites, exclusions, or contextual cues for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does, not how it behaves. It doesn't disclose whether it's a read-only operation, what happens with invalid IDs, if there are rate limits, authentication needs, or what 'details' and 'observations' entail in the response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes a useful detail ('including all observations') that earns its place by clarifying scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'details' or 'observations' mean in the response, nor does it cover error handling, permissions, or behavioral constraints, leaving significant gaps for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single parameter 'sub_id' with its type, description, and requirement. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'details of a specific checklist including all observations', which is specific and actionable. It distinguishes from siblings like 'get_recent_checklists' (list) or 'get_checklists_on_date' (date-filtered), but doesn't explicitly name alternatives for fetching checklist details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid checklist ID), exclusions (e.g., not for bulk operations), or refer to sibling tools like 'get_recent_checklists' for different use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves checklists but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or the format of returned data. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without any fluff or redundancy. It's front-loaded and efficiently communicates the core functionality, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 6 parameters (4 required), no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns (e.g., checklist format, pagination), behavioral traits, or usage context. For a data retrieval tool with multiple inputs, more detail is needed to ensure proper agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'a specific date,' which aligns with the year, month, and day parameters in the schema. However, with 100% schema description coverage, the schema already fully documents all parameters, including region_code, sort_key, and max_results. The description adds minimal value beyond what the schema provides, meeting the baseline score for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get checklists submitted on a specific date.' It specifies the verb ('Get') and resource ('checklists'), and indicates the scope ('submitted on a specific date'). However, it doesn't explicitly differentiate from sibling tools like 'get_recent_checklists' or 'get_checklist', which might have overlapping functionality, so it doesn't reach a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_recent_checklists' or 'get_checklist', nor does it specify prerequisites or exclusions. The user is left to infer usage based on the purpose alone, which is insufficient for clear decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks critical details: it doesn't mention whether this is a read-only operation, potential rate limits, authentication needs, or what the output looks like (e.g., list format, pagination). For a tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain return values, behavioral traits like safety or performance, or how it differs from siblings. For a tool in this context, more detail is needed to guide the agent effectively beyond the basic purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 parameters (region_code, back, fmt) thoroughly. The description adds no additional meaning beyond implying a regional scope, which is redundant with the schema. This meets the baseline of 3, as the schema does the heavy lifting for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('birding hotspots in a region'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_nearby_hotspots' or 'get_hotspot_info', which offer similar hotspot-related functionality, leaving some ambiguity about when to choose this specific tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_nearby_hotspots' (for proximity-based queries) and 'get_hotspot_info' (for detailed info on a single hotspot), the lack of context leaves the agent to infer usage based on tool names alone, which is insufficient for reliable selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but fails to describe critical behaviors like rate limits, authentication needs, pagination, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It wastes no words and is appropriately sized for a straightforward tool, earning a perfect score for conciseness and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, error conditions, or behavioral constraints, which are essential for an agent to use the tool effectively. The high schema coverage helps, but the description does not compensate for other gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add any meaning beyond what the input schema provides, as it mentions no parameters. However, with 100% schema description coverage, the baseline score is 3, as the schema adequately documents all parameters (e.g., lat/lng for location, dist for radius, back for recency, fmt for format).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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') and resource ('birding hotspots near a location'), making it immediately understandable. However, it does not explicitly differentiate from sibling tools like 'get_hotspots_in_region' or 'get_hotspot_info', which limits its score to 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'get_hotspots_in_region' for regional searches or 'get_hotspot_info' for detailed hotspot data. It lacks explicit context, exclusions, or prerequisites, leaving usage decisions unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'notable/rare observations' but doesn't explain what qualifies as notable/rare, how results are sorted, whether there are rate limits, or what the output format looks like. For a tool with 8 parameters and no output schema, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Get notable/rare observations near a location.' It's front-loaded with the core purpose and contains no unnecessary words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'notable/rare' means, how observations are returned, or any behavioral traits like pagination or error handling. For a data-fetching tool with many parameters, this leaves critical context gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so parameters like 'lat', 'lng', 'back', 'detail', 'dist', 'hotspot', 'max_results', and 'spp_locale' are well-documented in the schema. The description adds no additional parameter semantics beyond implying location-based filtering. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get notable/rare observations near a location.' It specifies the verb ('get'), resource ('notable/rare observations'), and scope ('near a location'). However, it doesn't explicitly differentiate from sibling tools like 'get_nearby_observations' or 'get_notable_observations', which reduces clarity about its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'get_nearby_observations', 'get_notable_observations'), there's no indication of how this tool differs in context, such as filtering for rarity or specific location-based queries. This leaves the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It mentions 'recent' observations but doesn't clarify what 'recent' means (the 'back' parameter handles this), nor does it describe return format, pagination, rate limits, authentication requirements, or error conditions. For a tool with 10 parameters and no output schema, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately front-loaded with the essential information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, no annotations, no output schema, and 24 sibling tools), the description is insufficiently complete. It doesn't explain the return format, differentiate from siblings, or provide behavioral context beyond the basic purpose. For a data retrieval tool with many parameters and alternatives, more guidance is needed to help the agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'recent' and 'near a geographic location,' which loosely maps to the 'back,' 'lat,' 'lng,' and 'dist' parameters. However, with 100% schema description coverage, all parameters are already documented in the schema, so the description adds minimal value beyond what's already structured. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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') and resource ('recent observations near a geographic location'), making it immediately understandable. However, it doesn't differentiate this tool from its many siblings (like 'get_nearby_notable_observations' or 'get_recent_observations'), which would require additional specificity about what makes 'nearby observations' distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With 24 sibling tools available (including several with 'nearby' or 'observations' in their names), there's no indication of what distinguishes this tool from others like 'get_nearby_notable_observations' or 'get_recent_observations'—leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'recent observations' but does not specify timeframes, data sources, rate limits, authentication needs, or return formats. For a tool with 9 parameters and no output schema, this is inadequate, though it hints at recency and location-based filtering. A score of 2 reflects partial but insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core functionality without unnecessary details. It is front-loaded and wastes no words, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, leaving significant gaps for an AI agent. Without annotations or output schema, the description should provide more comprehensive guidance, but it does not, resulting in a low score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantic value beyond the input schema, which has 100% coverage. It implies parameters like location and species but does not explain their roles or interactions (e.g., how 'back' and 'dist' affect results). With high schema coverage, the baseline is 3, as the schema documents parameters adequately, and the description does not significantly enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get recent observations of a specific species near a location.' It specifies the verb ('get'), resource ('observations'), and scope ('recent,' 'specific species,' 'near a location'). However, it does not explicitly differentiate from sibling tools like 'get_nearby_observations' or 'get_nearest_species_observations,' which reduces the score from 5 to 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'get_nearby_observations,' 'get_nearest_species_observations'), there is no indication of context, exclusions, or prerequisites. This lack of differentiation results in a score of 2, as it offers minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'recent' and defines 'notable observations' but doesn't disclose critical behavioral traits: whether this is a read-only operation, rate limits, authentication needs, pagination behavior, or what format the response returns. For a tool with 6 parameters and no output schema, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first states the core purpose, the second defines 'notable observations'. There's no wasted text, though it could be more front-loaded with additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what constitutes 'notable/rare', how results are sorted/limited, error conditions, or return format. The agent lacks sufficient context to use this tool effectively beyond basic parameter passing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the schema. The description adds no parameter-specific information beyond what's already in the schema (e.g., it doesn't clarify 'region_code' formats or 'notable' criteria). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get recent notable/rare bird observations in a region' with a specific verb ('Get'), resource ('notable/rare bird observations'), and scope ('in a region'). It distinguishes from generic observation tools by specifying 'notable/rare' but doesn't explicitly differentiate from sibling 'get_nearby_notable_observations'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any of the 22 sibling tools, nor does it specify prerequisites, exclusions, or comparative contexts. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'most recently submitted' but doesn't clarify criteria like time range, sorting order, or pagination. For a retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It's appropriately sized for a simple retrieval tool, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what 'most recently submitted' entails, the format of returned checklists, or any limitations, leaving the agent with insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters thoroughly. The description adds no additional meaning beyond implying 'region_code' is used for filtering and 'max_results' limits output, which aligns with but doesn't enhance the schema's details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('most recently submitted checklists for a region'), making the purpose understandable. However, it doesn't explicitly differentiate from siblings like 'get_checklists_on_date' or 'get_recent_observations', which might retrieve similar temporal data but for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_checklists_on_date' and 'get_recent_observations', there's no indication of whether this tool is preferred for checklist-specific recent data or if it overlaps with other tools, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool retrieves statistics but doesn't disclose behavioral traits such as whether it's a read-only operation, potential rate limits, authentication requirements, or what happens with invalid dates/regions. The description is minimal and lacks necessary operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and includes specific metric examples. Every word earns its place with zero wasted text, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with four required parameters. It doesn't explain what the statistics output looks like, how they're aggregated, or any error conditions. For a data retrieval tool, this leaves significant gaps in understanding its behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all four parameters. The description adds no additional parameter semantics beyond implying that 'region_code' and date parameters are used to fetch statistics. This meets the baseline for high schema coverage but doesn't enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get statistics for a region on a specific date' with specific metrics (checklist count, species count, contributor count). It distinguishes from siblings by focusing on aggregated statistics rather than raw observations or region metadata, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_region_info' (which might provide metadata) or 'get_checklists_on_date' (which might provide raw data). It mentions what the tool does but offers no context about appropriate use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what information is returned but doesn't disclose behavioral traits such as rate limits, authentication needs, error conditions, or response format. For a read operation with no annotations, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and lists key information returned. Every word earns its place with no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain return values, error handling, or behavioral constraints. For a tool with 3 parameters and complex sibling context, more detail is needed to ensure the agent can use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters. The description doesn't add meaning beyond what the schema provides, such as explaining region_code hierarchies or practical use of name formats. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('region information'), specifying what information is included (name, bounds, parent hierarchy). It distinguishes from most siblings that focus on observations, checklists, or hotspots rather than region metadata, though it doesn't explicitly differentiate from get_sub_regions or get_adjacent_regions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like get_sub_regions or get_adjacent_regions. The description implies usage for region metadata but doesn't specify prerequisites, exclusions, or comparative contexts with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'recent observations' but doesn't clarify what 'recent' means (e.g., time frame defaults or limits), whether results are paginated, rate limits, authentication requirements, or error conditions. For a tool with 7 parameters and no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does ('Get recent observations') and key constraints ('specific species in a region'), making it easy to parse. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain return values (e.g., observation format, data fields), behavioral traits like rate limits or errors, or how it differs from similar sibling tools. For a data-fetching tool with many parameters, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 7 parameters thoroughly. The description adds minimal value beyond the schema—it implies filtering by species and region but doesn't provide additional context like parameter interactions or examples. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get recent observations of a specific species in a region.' It specifies the verb ('Get'), resource ('observations'), and key constraints ('specific species', 'region', 'recent'). However, it doesn't explicitly differentiate from sibling tools like 'get_nearby_species_observations' or 'get_nearest_species_observations', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for observations (e.g., 'get_nearby_species_observations', 'get_nearest_species_observations', 'get_recent_observations'), there's no indication of how this tool differs in scope or context. It lacks any 'when-to-use' or 'when-not-to-use' statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states a read operation ('Get'), implying non-destructive behavior, but doesn't disclose any behavioral traits such as rate limits, authentication needs, or what the output format might be (e.g., list of forms). This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to grasp quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'subspecies/forms' means in this context, what the return values might be, or any behavioral aspects. For a tool with taxonomic complexity, more context is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with 'species_code' clearly documented. The description adds no additional meaning beyond the schema, such as format details or examples beyond what's in the schema description. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('subspecies/forms for a species'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_taxonomy' or 'get_taxonomic_groups', which might also retrieve taxonomic information, so it lacks explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to taxonomy and observations, there's no mention of context, prerequisites, or exclusions, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions retrieving data ('Get'), implying a read-only operation, but fails to specify critical traits like rate limits, authentication needs, pagination, or the format of returned results (e.g., list of contributors with details). This leaves significant gaps in understanding how the tool behaves beyond basic input-output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does, making it easy to parse quickly, and every part of the sentence contributes essential information, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain the return format (e.g., what data 'contributors' includes), behavioral constraints, or how it integrates with sibling tools. For a data retrieval tool with multiple inputs and no structured output, more context is needed to ensure proper agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantic context beyond the input schema, which has 100% coverage with detailed parameter descriptions. It implies date-based filtering via 'on a given date,' but the schema already covers 'year,' 'month,' and 'day' parameters explicitly. No additional syntax or usage nuances are provided, so the baseline score of 3 is appropriate as the schema does most of the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and target resource ('top 100 contributors'), and specifies the context ('on a given date'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_regional_statistics' or 'get_recent_observations' that might also involve contributor data, leaving some ambiguity about uniqueness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as which sibling tools might overlap in functionality (e.g., 'get_regional_statistics' for broader data or 'get_recent_observations' for time-based queries). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions 'nearest locations' and 'seen recently,' it doesn't specify what 'recently' means (e.g., default time frame), how results are ordered, whether data is real-time or cached, or any rate limits or authentication requirements. For a tool with 9 parameters and no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Find the nearest locations where a species has been seen recently.' It's front-loaded with the core purpose, uses clear language, and avoids unnecessary words. Every part of the sentence contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (9 parameters, no output schema, no annotations), the description is adequate but incomplete. It clearly states the purpose but lacks behavioral details (e.g., result format, error handling) and usage guidelines relative to siblings. Without an output schema, the description doesn't explain return values, which is a gap, but the concise purpose statement provides a minimal viable foundation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the input schema with clear descriptions (e.g., 'Latitude', 'eBird species code', 'Number of days back to fetch'). The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline score of 3 without compensating or detracting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find the nearest locations where a species has been seen recently.' It specifies the verb ('find'), resource ('nearest locations'), and scope ('species has been seen recently'), making the intent unambiguous. However, it doesn't explicitly differentiate from similar sibling tools like 'get_nearby_species_observations' or 'get_nearby_observations', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'get_nearby_species_observations', 'get_nearby_observations', 'get_historic_observations'), there's no indication of specific use cases, prerequisites, or exclusions. This lack of comparative context leaves the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves species groups but does not mention whether this is a read-only operation, potential rate limits, authentication needs, or what the output format might be. This leaves significant gaps for a tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose with illustrative examples. It is front-loaded with the core action and avoids any unnecessary details, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on output format, error handling, or behavioral traits, which are important for completeness in the absence of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters with enums and defaults. The description adds no additional parameter semantics beyond implying the tool returns grouped species data, which aligns with the schema. This meets the baseline score when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get species groups' with examples like 'Waterfowl' and 'Raptors', which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'get_taxonomy' or 'get_taxonomic_forms', which might have overlapping functionality, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'get_taxonomy' or 'get_species_list'. It lacks context about use cases, exclusions, or prerequisites, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't specify any behavioral traits such as rate limits, authentication requirements, or what the output format might be (e.g., list of codes, JSON structure). This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without any fluff or redundant information. It's front-loaded and efficiently communicates the essential information, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose but lacks details on behavioral aspects like output format or usage context. For a tool with no structured fields to rely on, the description should ideally provide more completeness, but it meets the minimum viable standard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't mention parameters, which is correct for this case. A baseline of 4 is applied since no parameter information is needed, and the description doesn't add unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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') and resource ('available language codes for species names'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate itself from sibling tools like 'get_taxonomic_forms' or 'get_taxonomic_groups', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or comparison with sibling tools, leaving the agent with no usage instructions beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't mention if this is a read-only operation, how data is returned (e.g., list format, pagination), or any constraints like rate limits or authentication needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently communicates the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters and no output schema, the description is minimally adequate but lacks details on return values or behavioral context. It's complete enough for a simple retrieval tool but could benefit from more context about what 'taxonomy versions' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't mention parameters, aligning with the schema. A baseline of 4 is given as it doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('all available taxonomy versions'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'get_taxonomy' or 'get_taxonomic_groups', but the specificity of 'versions' provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_taxonomy' or other taxonomy-related siblings. The description only states what it does, not when it's appropriate or what context it serves.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the output format ('species codes in taxonomic order') but doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, data freshness, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and includes useful output details. Every word earns its place with no redundancy or wasted text, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides basic purpose and output format but lacks completeness for a tool that returns species data. It doesn't cover behavioral aspects like data scope (e.g., historical vs. current), pagination, or error handling, which are important for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the 'region_code' parameter fully. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples of valid region codes or format details). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get all species ever recorded') and resource ('in a region'), with specificity about output format ('species codes in taxonomic order'). It distinguishes from siblings like 'get_species_observations' by focusing on comprehensive species lists rather than observations, though it doesn't explicitly name alternatives. This is clear but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving comprehensive species lists in a region, but doesn't explicitly state when to use this tool versus alternatives like 'get_checklist' or 'get_species_observations'. It provides context (region-based species list) but no exclusions or named alternatives, leaving some 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves taxonomy data but does not disclose behavioral traits such as rate limits, authentication needs, pagination, or error handling. For a read operation with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. Every word earns its place, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 optional parameters) and lack of annotations or output schema, the description is minimally adequate. It covers the purpose but misses behavioral context and usage guidelines, leaving gaps that could hinder effective tool selection and invocation by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 five parameters thoroughly. The description adds no additional meaning beyond implying a comprehensive list, which aligns with the schema but does not compensate for or enhance parameter understanding. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('eBird taxonomy'), specifying it returns a list of all species with codes, names, and classification. It distinguishes from sibling tools like 'get_species_list' or 'get_taxonomic_groups' by focusing on the comprehensive taxonomy rather than specific subsets or related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_species_list' or 'get_taxonomic_groups'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the time constraint 'up to 30 days ago' and output fields, but does not disclose behavioral traits such as rate limits, authentication needs, pagination, error handling, or whether the operation is read-only (implied but not stated). This leaves significant gaps for an agent to understand operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys purpose, scope, and output. It is front-loaded with key information and has no wasted words, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 7 parameters, no annotations, and no output schema, the description is moderately complete. It covers the core functionality and output fields, but lacks details on behavioral aspects like rate limits or error handling, and does not explain the return format beyond listing fields. This is adequate for basic use but leaves gaps for robust agent operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 7 parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as examples or usage tips. The baseline score of 3 is appropriate since the schema does the heavy lifting, but the description does not compensate with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'recent bird observations in a region', with specific scope 'up to 30 days ago' and output details 'species, location, date, and count info'. It distinguishes from siblings like 'get_historic_observations' by specifying recency, and from 'get_nearby_observations' by focusing on a region rather than proximity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for recent observations within a region, but does not explicitly state when to use this tool versus alternatives like 'get_historic_observations' (for older data) or 'get_nearby_observations' (for location-based queries). It provides some context but lacks explicit guidance on exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function and provides examples, but lacks details on permissions, rate limits, pagination, or error handling. For a read-only tool (implied by 'Get'), this is a moderate gap, but the examples add some practical context beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by two concise examples that illustrate usage without redundancy. Every sentence earns its place by clarifying scope and application, making it efficient and well-structured for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is reasonably complete. It covers purpose, usage guidelines, and parameter semantics through examples, but lacks details on output format or behavioral traits like error handling. With no output schema, it could benefit from mentioning the structure of returned data, but the examples imply a list of regions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 parameters (region_type, parent_region_code, fmt) with enums and defaults. The description adds value by explaining the semantics of parent_region_code with 'world' for countries and providing usage examples, but doesn't introduce new parameter details beyond what the schema provides. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'sub-regions within a parent region', making the purpose specific. It distinguishes from siblings like get_region_info or get_regional_statistics by focusing on hierarchical relationships rather than metadata or statistics. The examples reinforce this distinction by showing concrete use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool through examples: get_sub_regions('country', 'world') for all countries and get_sub_regions('subnational1', 'US') for US states. This clarifies the tool's scope and distinguishes it from alternatives like get_region_info (which might return metadata about a single region) or get_adjacent_regions (which might return neighboring regions rather than hierarchical children).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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