MCP Server for Apache Airflow

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific Airflow entities (DAGs, tasks, connections, variables, datasets), but there is some overlap between get_dag_details and get_dag, and between get_tasks and get_dag_tasks, which could cause minor confusion. The descriptions help differentiate, but the sheer number of tools increases cognitive load.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout (e.g., get_dag, create_connection, delete_variable, update_task_instance). There are no deviations in naming conventions, making the set predictable and easy to navigate.
Tool Count2/5
With 68 tools, this server is overloaded for typical agent use. While Airflow is a complex system, this count far exceeds the 3-15 range for well-scoped servers, making it heavy and likely overwhelming for agents to handle efficiently.
Completeness5/5
The tool surface provides comprehensive CRUD/lifecycle coverage for all key Airflow domains (DAGs, tasks, connections, variables, datasets, pools, logs, XComs). There are no obvious gaps, and operations like create, get, update, delete, list, and state management are fully represented across entities.
Average 2.3/5 across 68 of 68 tools scored. Lowest: 1.3/5.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 5 issues responded to in the last 6 months
- No commit activity data available
- Last stable release on February 6, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
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{
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  "maintainers": [
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  ]
}
```
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states 'Create' which implies a write/mutation operation, but offers no details on permissions, side effects, idempotency, or response format. For a tool that likely modifies system state, this lack of transparency is inadequate and could lead to misuse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with only two words, this is under-specification rather than effective brevity. The description lacks necessary detail and structure—it doesn't front-load key information or provide any context. Every word should earn its place, but here the words don't provide enough value to justify their inclusion without expansion.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity (a creation/mutation operation with two parameters), no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what the tool does beyond its name, how to use it, what parameters mean, or what to expect in return. This leaves the agent with insufficient information to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning neither parameter ('dataset_uri', 'extra') is documented in the schema. The description adds no information about these parameters—it doesn't explain what a 'dataset_uri' is, its format, or what 'extra' data might be used for. With two parameters and zero coverage, the description fails to compensate, leaving parameters completely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create dataset event' is a tautology that restates the tool name without elaboration. It provides a basic verb ('Create') and resource ('dataset event'), but lacks specificity about what a 'dataset event' is or what creation entails. It doesn't distinguish this tool from sibling tools like 'create_connection' or 'create_variable' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 doesn't mention prerequisites, context, or exclusions. Given sibling tools like 'get_dataset_events' and 'delete_dataset_queued_events', there's no indication of how this tool fits into workflows or when it's appropriate to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. The description 'Get dataset events' implies a read operation but reveals nothing about permissions required, rate limits, pagination behavior (despite limit/offset parameters), whether it returns historical or real-time data, or what format the events are in. This is a complete lack of behavioral transparency for an 8-parameter tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with only three words, this is under-specification rather than effective conciseness. The description doesn't earn its place by providing necessary information. It's front-loaded only in the trivial sense that there's nothing to load beyond the initial phrase.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter tool with no annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what dataset events are, how they're structured, what filtering options exist, or what the tool returns. The agent would struggle to use this tool correctly without significant trial and error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 8 parameters, the description provides zero information about any parameters. It doesn't mention dataset_id, source filtering parameters (dag_id, task_id, run_id, map_index), or pagination controls (limit, offset, order_by). The description fails completely to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get dataset events' is a tautology that restates the tool name without adding meaningful clarification. It specifies the verb 'get' and resource 'dataset events' but provides no additional context about what dataset events are, their format, or scope. This is slightly better than a pure tautology but remains vague and minimally informative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. There are multiple sibling tools related to datasets (e.g., get_dataset, get_datasets, get_dataset_queued_events, get_upstream_dataset_events) but no indication of how this tool differs or when it should be selected. The agent receives no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 fails completely. It doesn't indicate whether this is a read or write operation (though 'create' implies mutation), what permissions are required, whether it's idempotent, what happens on failure, or what the return value might be. For a tool with 8 parameters that presumably creates a persistent resource, this lack of behavioral information is critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just two words, which could be appropriate if it were informative, but here it's under-specified rather than efficiently informative. While it's front-loaded (the entire description is in those two words), it fails to provide necessary context, making this conciseness detrimental rather than helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, 2 required), complete lack of annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. A tool that presumably creates a persistent connection resource needs far more context about what it does, when to use it, what the parameters mean, and what behavior to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for all 8 parameters, and the tool description provides zero information about what any parameter means. The description doesn't explain what 'conn_id' or 'conn_type' represent, what 'extra' might contain, or how these parameters relate to creating a connection. With 8 undocumented parameters, this is a severe deficiency.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a connection' is a tautology that merely restates the tool name without providing any meaningful context about what a 'connection' is or what it does. It doesn't specify what type of connection (database, API, network) or what resource it creates, nor does it distinguish this from sibling tools like 'update_connection' or 'test_connection'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. There are multiple sibling tools related to connections (delete_connection, get_connection, list_connections, test_connection, update_connection), but the description offers no context about when this specific creation tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. 'Get DAG stats' implies a read-only operation but fails to specify critical details: whether it requires authentication, has rate limits, returns real-time or historical data, or what format the output takes (e.g., JSON, summary statistics). This lack of transparency leaves the agent guessing about the tool's behavior and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just three words, which could be seen as efficient. However, it is under-specified rather than appropriately sized, as it lacks essential details needed for effective tool use. While front-loaded, it does not earn its place by adding value beyond the minimal statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (inferred from sibling tools involving DAG operations), lack of annotations, no output schema, and poor parameter documentation, the description is severely incomplete. It does not cover what stats are retrieved, how results are structured, or any behavioral aspects, making it inadequate for an agent to use the tool correctly in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter (dag_ids) with 0% description coverage, meaning the schema provides no semantic information. The description 'Get DAG stats' does not mention parameters at all, failing to explain what dag_ids is (e.g., a list of DAG identifiers to filter stats), its optional nature, or how null values are handled. This leaves the parameter's purpose and usage completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get DAG stats' is a tautology that merely restates the tool name without elaboration. It specifies the verb 'Get' and resource 'DAG stats', but provides no details about what 'stats' entails (e.g., performance metrics, status counts, runtime information) or how it differs from sibling tools like get_dag, get_dag_details, or get_dag_runs. This leaves the purpose vague and indistinguishable from related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as whether it's for monitoring, debugging, or reporting, or how it compares to siblings like get_dag_runs or get_dag_details. Without such information, an agent cannot determine appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 none. It doesn't indicate whether this is a read-only diagnostic operation or has side effects, what authentication is required, whether it modifies system state, what happens on failure, or what the typical response format might be. For a tool with 7 parameters that presumably interacts with external systems, this lack of behavioral context is severely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, but this brevity comes at the cost of being under-specified rather than efficient. While it's front-loaded with the core action, every word earns its place only in the most minimal sense—it communicates the basic action but lacks the necessary detail for effective tool use. The structure is simple but incomplete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's apparent complexity (7 parameters for connection testing), complete lack of annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what the tool does beyond the name, provides no behavioral context, offers no parameter guidance, and gives no indication of return values or error conditions. This leaves an agent with insufficient information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 7 parameters (only one required), the description provides zero information about parameter meanings. It doesn't explain what 'conn_type' represents, what the various connection parameters (host, port, login, password, schema, extra) are for, or how they relate to testing connections. The description fails completely to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Test a connection' is a tautology that restates the tool name 'test_connection' without adding meaningful specificity. It doesn't clarify what type of connection is being tested (database, network, API, etc.), what 'testing' entails (connectivity verification, authentication, performance check), or what resource is involved. While it includes a verb ('Test') and resource ('connection'), it lacks the specificity needed to distinguish it from potential alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or relationships to sibling tools like 'create_connection', 'get_connection', 'update_connection', or 'delete_connection'. An agent would have no indication whether this should be used before creating a connection, after modifying one, or as a standalone diagnostic tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Delete a pool' implies a destructive, irreversible mutation, but it doesn't specify permissions required, whether deletion is permanent, if confirmation is needed, or what happens on success/failure. For a destructive tool with zero annotation coverage, this is critically 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 extremely concise ('Delete a pool')—a single three-word sentence. While this is efficient and front-loaded, it's arguably under-specified rather than appropriately concise, as it omits essential context. However, it doesn't waste words or include redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature, lack of annotations, no output schema, and minimal parameter documentation, the description is severely incomplete. It doesn't cover behavioral risks, parameter meaning, expected outcomes, or error conditions. This is inadequate for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter (pool_name) with 0% description coverage. The tool description adds no information about this parameter—it doesn't explain what a pool_name is, its format, valid values, or how to obtain it. With low schema coverage and no compensation in the description, this leaves the parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Delete a pool' restates the tool name 'delete_pool' without adding specificity. It doesn't clarify what a 'pool' is in this context (e.g., resource pool, connection pool, data pool) or distinguish it from sibling tools like delete_connection, delete_dag, or delete_variable. This is a tautology that provides minimal value beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 to identify an existing pool), consequences (e.g., what happens to dependent resources), or when to choose other deletion tools like delete_dag or delete_variable. This leaves the agent with no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 'Get a source code', which implies a read operation but doesn't cover aspects like authentication needs, rate limits, error handling, or what 'source code' entails (e.g., file content, metadata). This is inadequate for a tool with no annotation support.
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 extremely concise ('Get a source code'), which is efficient and front-loaded. However, it's under-specified rather than optimally concise, as it lacks necessary details. It earns a 4 because it's brief and to the point, but the brevity comes at the cost of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (1 required parameter, no annotations, no output schema, and many sibling tools), the description is incomplete. It doesn't explain what 'source code' refers to, how to use the 'file_token', or what the tool returns, making it insufficient for effective agent use in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter ('file_token') with 0% description coverage, and the tool description provides no information about parameters. The description does not add any meaning beyond the schema, failing to compensate for the lack of schema documentation, which is critical for a required parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a source code' states a vague action ('Get') and resource ('source code'), but it doesn't specify what type of source code (e.g., DAG source code) or from where. It's slightly better than a tautology but lacks specificity compared to siblings like 'get_dag' or 'get_dag_details', which clearly indicate their scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 siblings like 'get_dag', 'get_dag_details', and 'get_import_error' that might relate to DAGs or code, the description offers no context for differentiation, leaving the agent to guess based on 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.
Behavior1/5
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 tasks') without any details on permissions, rate limits, pagination, error handling, or what 'Get' entails (e.g., returns a list, single object, or metadata). For a tool with no annotation coverage, this is a significant gap.
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 extremely concise ('Get tasks for DAG'), which is efficient and front-loaded. However, it's under-specified rather than appropriately sized—it lacks essential details that would make it useful. While not verbose, its brevity comes at the cost of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (2 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain the tool's behavior, parameter usage, or output format, leaving the agent with insufficient information to use the tool correctly. This is inadequate for a tool in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters 'dag_id' and 'order_by' are undocumented in the schema. The description adds no information about these parameters—it doesn't explain what 'dag_id' refers to (e.g., Airflow DAG identifier), what 'order_by' does, or valid values. With low coverage and no compensation in the description, this fails to provide necessary context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get tasks for DAG' restates the tool name 'get_tasks' without adding specificity. It mentions 'DAG' which is clarified by the required 'dag_id' parameter, but it doesn't distinguish this tool from sibling tools like 'get_dag_tasks' or explain what 'tasks' means in this context (e.g., Airflow tasks vs. general tasks). This is a tautology with minimal added value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 sibling tools like 'get_dag_tasks' and 'get_task' available, there's no indication of how this tool differs (e.g., scope, filtering capabilities, or performance). The agent must infer usage from the name alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 provides none. 'Set a state' implies a mutation operation, but there's no information about permissions required, whether changes are destructive or reversible, rate limits, side effects, or what happens when state is changed. For a tool with 9 parameters that appears to modify workflow execution states, this lack of behavioral context is critically 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 extremely concise at just 5 words, which is appropriate for its length. However, this conciseness comes at the cost of being severely under-specified rather than efficiently informative. The single sentence is front-loaded with the core action but lacks any supporting context that would make it genuinely helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no output schema, no annotations, and multiple similar sibling tools), this description is completely inadequate. It fails to explain what the tool does beyond the obvious, provides no parameter guidance, offers no behavioral context, and gives no usage differentiation. For a state-modification tool in what appears to be a workflow/airflow system, this minimal description leaves the agent guessing about critical operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 9 parameters (7 optional), the description provides zero information about any parameters. It doesn't mention dag_id, state, task_ids, execution_date, or any of the boolean flags (include_upstream, include_downstream, etc.). The agent must rely entirely on parameter names without any semantic explanation of what these parameters mean or how they interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Set a state of task instances' is essentially a tautology that restates the tool name with minor grammatical changes. While it indicates the verb ('set') and resource ('task instances'), it lacks specificity about what 'state' means or how this differs from similar tools like 'update_task_instance' or 'clear_task_instances' in the sibling list. The purpose is vague and doesn't provide meaningful differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With multiple sibling tools that manipulate task instances (clear_task_instances, update_task_instance, list_task_instances), the agent receives no indication of when this specific state-setting operation is appropriate versus other modification operations. There's no mention of prerequisites, typical 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.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Clear a DAG run' implies a destructive mutation but doesn't specify what 'clear' entails (e.g., deletion, state reset, data removal), whether it's reversible, what permissions are needed, or any side effects. This is inadequate for a mutation tool with zero 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 extremely concise at just three words, with no wasted language. It's front-loaded with the core action, though this brevity comes at the cost of clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what 'clear' means, when to use it, what the parameters do, or what to expect in return, leaving critical gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 3 parameters (dag_id, dag_run_id, dry_run) are documented in the schema. The description adds no information about these parameters—not their purposes, formats, or examples—failing to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Clear a DAG run' is essentially a tautology that restates the tool name. It specifies the verb 'clear' and resource 'DAG run', but lacks specificity about what 'clear' means operationally (e.g., delete, reset, remove data). It doesn't distinguish from sibling tools like 'delete_dag_run', leaving ambiguity about their differences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 sibling tools like 'delete_dag_run', 'clear_task_instances', and 'set_task_instances_state', the description offers no context on appropriate use cases, prerequisites, or exclusions, leaving the agent to guess based on naming alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers no behavioral details. It doesn't clarify if 'clear' is destructive (e.g., deletes data), requires specific permissions, has side effects, or how it interacts with other operations. The term 'clear' is ambiguous without context on what happens to the cleared instances.
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 extremely concise with a single, straightforward sentence. It avoids redundancy and is front-loaded, though this brevity contributes to underspecification rather than clarity. Every word earns its place, but the place is minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (12 parameters, no annotations, no output schema), the description is grossly inadequate. It fails to explain the tool's purpose beyond the name, provide usage context, disclose behavior, or clarify parameters. This leaves the agent unable to effectively select or invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning all 12 parameters are undocumented in the schema. The description adds no parameter information—it doesn't explain what 'dag_id', 'task_ids', date ranges, boolean flags (e.g., 'include_subdags'), or 'dry_run' do. This leaves the agent with no semantic understanding of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Clear a set of task instances' restates the tool name with minimal elaboration, making it tautological. It specifies the verb 'clear' and resource 'task instances', but lacks detail on what 'clear' means operationally (e.g., delete, reset, mark as cleared) and doesn't distinguish it from sibling tools like 'clear_dag_run' or 'set_task_instances_state'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. It doesn't mention prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage from the tool name alone. This is particularly problematic given multiple sibling tools that might handle similar operations on tasks or DAGs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 fails completely. 'Create a variable' implies a write/mutation operation but provides no information about permissions required, whether the operation is idempotent, what happens if a variable with the same key already exists, rate limits, or what the response looks like. This leaves the agent with critical gaps in understanding how to properly invoke this tool.
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 maximally concise at just two words, with no wasted language or unnecessary elaboration. While this conciseness comes at the cost of completeness, the description is perfectly structured in its brevity and gets straight to the point without any filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with no annotations, 3 parameters (2 required), 0% schema description coverage, and no output schema, the description is completely inadequate. A proper description for this context would need to explain what system the variable belongs to, what the parameters mean, what happens on success/failure, and how this differs from sibling variable tools. The current description provides none of this essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about the three parameters (key, value, description) despite the schema having 0% description coverage. The agent must infer from the parameter names alone what these represent and how they should be used. For a creation tool with multiple parameters, this represents a significant documentation gap that the description fails to address.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a variable' is a tautology that merely restates the tool name without providing any meaningful context about what kind of variable is being created, in what system, or for what purpose. While it does contain a verb ('Create') and resource ('variable'), it lacks the specificity needed to distinguish this from other variable-related tools like 'update_variable' or 'delete_variable' in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. There are multiple sibling tools dealing with variables (create_variable, delete_variable, get_variable, list_variables, update_variable), but the description offers no context about when this specific creation tool should be selected over other variable operations or what prerequisites might be needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 none. It doesn't indicate whether this is a read-only operation, what permissions might be required, whether results are paginated (despite having limit/offset parameters), what format the results return, or any error conditions. For a tool with 13 parameters and no annotation coverage, this is critically insufficient.
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 maximally concise at just four words. While this represents severe under-specification, from a pure conciseness perspective, there's zero wasted language. Every word earns its place, though collectively they provide inadequate information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 13 parameters, no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what the tool returns, how to interpret the numerous filtering parameters, what DAG runs are, or how this differs from similar tools. The agent would struggle to use this tool correctly without significant external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 13 parameters have descriptions in the schema. The description 'Get DAG runs by ID' only vaguely references the 'dag_id' parameter but doesn't explain what a DAG ID is, what format it expects, or how it relates to the other 12 filtering parameters (date ranges, state, ordering, etc.). The description fails to compensate for the complete lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get DAG runs by ID' is a tautology that essentially restates the tool name 'get_dag_runs'. It doesn't specify what 'get' means (list, retrieve, fetch), nor does it explain what DAG runs are or how they differ from other DAG-related resources. While it mentions 'by ID', the required parameter is 'dag_id', which suggests it's filtering by DAG identifier rather than retrieving specific run IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides zero guidance on when to use this tool versus alternatives. With sibling tools like 'get_dag_run' (singular), 'get_dag_runs_batch', 'fetch_dags', and 'get_dag_details', there's no indication of which tool to choose for different scenarios. No prerequisites, limitations, or comparison context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'List DAG runs (batch)' reveals nothing about whether this is a read-only operation, what permissions are required, whether it's paginated (though parameters suggest it might be), rate limits, or what the output format looks like. For a tool with 11 parameters and no output schema, this is critically insufficient.
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 extremely concise at three words, with no wasted language. It's front-loaded with the core action and resource. While this conciseness comes at the cost of completeness, it meets the criteria for efficient structure without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (11 parameters, no annotations, no output schema, and 0% schema description coverage), the description is completely inadequate. It doesn't explain what DAG runs are, how batch differs from non-batch, what parameters mean, what the tool returns, or any behavioral traits. This leaves the agent unable to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 11 parameters and 0% schema description coverage, the schema provides only parameter names and types without any semantic meaning. The description adds absolutely nothing about what any parameter does (e.g., what 'dag_ids', 'execution_date_gte', or 'state' represent), leaving all parameters completely undocumented. This fails to compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List DAG runs (batch)' is essentially a tautology that restates the tool name 'get_dag_runs_batch' with minimal elaboration. While it indicates the action (list) and resource (DAG runs), it lacks specificity about what DAG runs are or what 'batch' entails compared to the sibling tool 'get_dag_runs'. This provides only basic purpose without meaningful differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 a sibling tool named 'get_dag_runs' (without 'batch'), there's a clear opportunity to explain the difference, but the description offers no comparison, prerequisites, or context for choosing between them. This leaves the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the action 'get' without disclosing behavioral traits such as read-only vs. destructive nature, authentication needs, rate limits, pagination, or error handling. This is inadequate 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 extremely concise with a single sentence 'Get tasks for DAG', which is front-loaded and wastes no words. However, this conciseness comes at the cost of underspecification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, no output schema, and multiple sibling tools, the description is severely incomplete. It fails to provide necessary context for a tool that likely interacts with a complex system like Apache Airflow DAGs, leaving the agent with insufficient information to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond the input schema. It does not explain what 'dag_id' represents, its format, or how it relates to retrieving tasks, leaving the single required parameter undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get tasks for DAG' restates the tool name 'get_dag_tasks' almost verbatim, making it tautological. It specifies the verb 'get' and resource 'tasks for DAG', but lacks specificity about what 'tasks' means in this context or how they differ from sibling tools like 'get_tasks' or 'get_task'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 sibling tools like 'get_tasks', 'get_task', and 'get_task_instance', the description offers no context on differentiation, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 provides none. 'List pools' doesn't indicate whether this is a read-only operation, whether it requires authentication, what the response format might be, whether it supports pagination (though parameters suggest it does), or any rate limits. For a tool with 3 parameters and no annotation coverage, this is completely inadequate.
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 maximally concise at just two words. While this represents severe under-specification rather than ideal conciseness, from a pure structural perspective, there's no wasted language or unnecessary elaboration. Every word (both of them) directly relates to the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a tool with 3 parameters, 0% schema description coverage, no annotations, no output schema, and multiple sibling tools in the same domain, the description 'List pools' is completely inadequate. It provides minimal purpose information but fails to address parameter usage, behavioral characteristics, differentiation from alternatives, or expected outputs. This is insufficient for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning none of the 3 parameters (limit, offset, order_by) are documented in the schema. The description 'List pools' provides no information about any parameters, their purposes, or how they affect the listing operation. The description fails to compensate for the complete lack of parameter documentation in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List pools' is a tautology that essentially restates the tool name 'get_pools'. While it indicates a listing action, it provides no information about what 'pools' are in this context or what specific listing operation is performed. Compared to sibling tools like 'get_pool' (singular) and 'post_pool', it doesn't clearly distinguish itself beyond the plural form.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. There are multiple sibling tools that interact with pools (get_pool, post_pool, patch_pool, delete_pool), but the description offers no context about when to list all pools versus retrieve a specific one, create a new one, or modify/delete existing ones. No prerequisites, constraints, or comparison information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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' without detailing behavioral traits such as read-only nature, error handling (e.g., if the key doesn't exist), permissions required, or rate limits. This lack of information makes it inadequate for understanding how the tool behaves beyond its basic function.
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 extremely concise with a single sentence 'Get a variable by key', which is front-loaded and wastes no words. While it lacks depth, it efficiently communicates the core action without unnecessary elaboration, making it structurally sound for its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a retrieval operation with 1 parameter), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't cover what the tool returns, error conditions, or behavioral context, making it insufficient for the agent to understand and use the tool effectively in this environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, meaning the schema provides no details about the 'key' parameter. The description adds no semantic information beyond implying the parameter is used to retrieve a variable, failing to explain what the key represents, its format, or examples. This leaves the parameter undocumented and unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a variable by key' is a tautology that essentially restates the tool name 'get_variable' with minimal elaboration. It specifies the verb 'get' and resource 'variable', but lacks specificity about what a 'variable' represents in this context (e.g., configuration, environment, or data variable) and doesn't differentiate from sibling tools like 'get_value' or 'list_variables', making it vague and minimally informative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 such as 'list_variables' for browsing or 'get_value' for similar retrieval, nor does it specify prerequisites like authentication or context. This absence of usage context leaves the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. 'Get' implies a read operation, but there's no information about permissions required, rate limits, error conditions, what happens if the XCom entry doesn't exist, or whether this operation has side effects. The description fails to provide any behavioral context beyond the basic verb.
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 extremely concise at just three words. While this represents under-specification rather than ideal conciseness, it contains zero wasted words and is perfectly front-loaded. Every word directly relates to the tool's purpose, earning its place in the description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 parameters, no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It provides no context about what XCom entries are, how to use the tool, what parameters mean, what behavior to expect, or what the tool returns. The description fails to provide the minimal context needed for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 7 parameters and 0% schema description coverage, the description provides no parameter information whatsoever. It doesn't explain what 'dag_id', 'dag_run_id', 'task_id', 'xcom_key', 'map_index', 'deserialize', or 'stringify' mean or how they relate to retrieving XCom entries. The description fails completely to compensate for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get an XCom entry' is a tautology that restates the tool name without adding meaningful context. It doesn't explain what XCom entries are, what resource is being accessed, or how this differs from sibling tools like 'get_xcom_entries' (plural). The purpose is minimally stated 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 Guidelines1/5
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. There's no mention of prerequisites, when this tool is appropriate versus 'get_xcom_entries', or any context about XCom systems. The agent receives zero usage direction beyond the tool name itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but discloses no behavioral traits. It doesn't mention whether this is a read-only operation, potential side effects, authentication needs, rate limits, or return format, making it inadequate for a tool with parameters.
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 extremely concise with a single three-word phrase, 'List all variables,' which is front-loaded and wastes no words. While under-specified, it is structurally efficient without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, three parameters, and no output schema, the description is severely incomplete. It lacks essential details on behavior, parameters, and output, failing to provide adequate context for tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about the three parameters (limit, offset, order_by). It fails to explain their purposes, such as pagination or sorting, leaving parameters undocumented and unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all variables' restates the tool name 'list_variables' with minimal elaboration, making it tautological. It specifies the resource ('variables') and action ('list') but lacks detail on scope or format, failing to distinguish from siblings like 'get_variable' or 'delete_variable'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 such as 'get_variable' for retrieving a single variable or 'delete_variable' for removal. The description offers no 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.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Update a DAG' implies a mutation operation but provides no information about permissions required, whether changes are reversible, what happens to unspecified fields, error conditions, or response format. This is inadequate for a mutation tool with zero 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 maximally concise with just three words. While severely under-specified, it contains zero wasted words and is front-loaded with the core action. This meets the criteria for perfect conciseness despite the content deficiencies.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 3 parameters, 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what DAGs are, what fields can be updated, the operation's behavior, or what to expect in return. Given the complexity implied by the sibling tools list, this description fails to provide necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the three parameters (dag_id, is_paused, tags) are documented in the schema. The description provides absolutely no information about these parameters - not what they represent, their formats, constraints, or how they affect the update operation. This fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update a DAG' is a tautology that merely restates the tool name 'patch_dag' without adding specificity. It doesn't clarify what aspects of a DAG are updated, how this differs from other DAG-related tools like 'pause_dag' or 'unpause_dag', or what 'DAG' refers to in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 multiple sibling tools like 'pause_dag', 'unpause_dag', 'delete_dag', and 'patch_dags', the description offers no indication of when this specific DAG update tool is appropriate versus those other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Update a pool' suggests a mutation operation but doesn't disclose whether this requires special permissions, what happens to existing pool settings not mentioned, whether the operation is idempotent, or what the typical response looks like. For a mutation tool with zero annotation coverage, this represents a significant transparency gap.
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 maximally concise at just three words. While this represents under-specification rather than ideal conciseness, from a pure structural perspective, there's no wasted language or unnecessary elaboration. Every word serves a purpose, even if that purpose is insufficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 4 parameters, 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what a 'pool' is in this system, what aspects can be updated, what the typical response contains, or any behavioral characteristics. The description fails to provide the contextual information needed to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about parameters, while the schema has 0% description coverage. With 4 parameters (pool_name, slots, description, include_deferred) completely undocumented in both schema and description, users have no guidance on what these parameters mean, their expected formats, or how they affect the update operation. The description doesn't compensate for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update a pool' is a tautology that restates the tool name 'patch_pool' without adding meaningful specificity. It doesn't clarify what aspects of a pool are updated or what 'pool' refers to in this context. While it includes a verb ('Update') and resource ('pool'), it lacks the specificity needed to distinguish this from sibling tools like 'post_pool' or 'delete_pool'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. There are multiple pool-related tools in the sibling list (post_pool, delete_pool, get_pool, get_pools), but the description offers no differentiation. It doesn't mention prerequisites, appropriate contexts, or when this tool should be preferred over other pool operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. 'Delete a DAG' implies a destructive operation but provides no details about consequences, permissions required, whether deletion is permanent or reversible, rate limits, or error conditions. This is inadequate for a destructive tool with zero 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 maximally concise at three words, with zero wasted verbiage. It's front-loaded with the essential action and target, though this brevity comes at the cost of completeness. Every word earns its place by communicating the core function without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what happens when a DAG is deleted, what dependencies might be affected, whether there are confirmation steps, or what the response looks like. The agent would be operating blindly with significant risk.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the single parameter 'dag_id' is completely undocumented in structured fields. The description adds no information about this parameter—no explanation of what a DAG ID is, format requirements, or where to find valid values. While the parameter count is low (1), the description fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Delete a DAG' is a tautology that merely restates the tool name without adding meaningful context. While it correctly identifies the verb ('Delete') and resource ('DAG'), it lacks specificity about what a DAG is or what deletion entails. It doesn't differentiate from sibling deletion tools like delete_dag_run or delete_connection, leaving the agent to guess based on naming conventions alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 multiple deletion tools in the sibling list (delete_dag_run, delete_connection, delete_variable, etc.), there's no indication of what distinguishes deleting a DAG from deleting other entities. The description offers no prerequisites, warnings, or context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states the action 'Get current configuration' without any details on permissions, rate limits, side effects, or return format. This is inadequate for a tool with potential read operations and no output schema.
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 extremely concise with a single sentence 'Get current configuration', which is front-loaded and wastes no words. However, this brevity contributes to underspecification rather than clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
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 low parameter coverage, the description is incomplete. It does not explain what 'configuration' entails, how results are returned, or behavioral aspects, making it insufficient for effective tool use in a context with many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'section' with 0% description coverage and no enums. The description does not mention parameters at all, failing to compensate for the lack of schema documentation. It should explain what 'section' refers to (e.g., a configuration category) to add semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get current configuration' restates the tool name 'get_config' with minimal elaboration, making it tautological. It specifies the verb 'Get' and resource 'current configuration' but lacks detail on what configuration refers to (e.g., system, application, or Airflow-specific settings), failing to distinguish it clearly from sibling tools like get_variable or get_connection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 context, prerequisites, or comparisons to sibling tools (e.g., get_variable for specific values or get_connection for connection details), leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the action ('List log entries') without any information about permissions, rate limits, pagination (implied by limit/offset but not explained), response format, or side effects. For a tool with 14 parameters and no annotations, this is a critical 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 with no wasted words: 'List log entries from event log.' It is front-loaded and appropriately sized for its minimal content, though this conciseness comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (14 parameters, no schema descriptions, no annotations, no output schema), the description is severely incomplete. It lacks essential context such as what the event log contains, how to filter or paginate, what the return structure is, and how it differs from similar tools. For a data retrieval tool with many options, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 14 parameters are documented in the schema. The description adds no information about any parameters—it doesn't mention filtering by dag_id, task_id, date ranges (before/after), ordering, or pagination. With high parameter count and zero coverage, the description fails to compensate, leaving semantics entirely unclear.
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 'List log entries from event log' states the basic action (list) and resource (log entries from event log), which is clear but vague. It doesn't specify what kind of event log (e.g., Airflow DAG events) or differentiate from sibling tools like get_event_log (singular) or get_log (general logs). The purpose is understandable but lacks specificity and sibling 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 sibling tools like get_event_log (singular), get_log (general logs), and get_dataset_events (dataset-specific), there's no indication of context, prerequisites, or exclusions. The agent must infer usage from the tool name alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden but discloses nothing beyond the basic action. It doesn't mention whether this is a read-only operation, what permissions are needed, if there are rate limits, or the format of returned data. For a tool with no annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just three words, front-loaded and zero waste. However, this conciseness comes at the cost of completeness, but as a standalone measure, it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, no output schema), the description is completely inadequate. It doesn't explain what 'import errors' are in this context, how results are structured, or any behavioral aspects. For a list operation with pagination parameters, more detail is essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning all three parameters (limit, offset, order_by) are undocumented in the schema. The description adds no information about these parameters, failing to compensate for the coverage gap. It doesn't explain what 'order_by' options exist or how pagination works.
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 'List import errors' clearly states the action (list) and resource (import errors), but it's vague about scope and format. It doesn't specify whether it lists all import errors or filtered ones, nor does it distinguish from sibling tools like 'get_import_error' (singular).
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 on when to use this tool versus alternatives is provided. With sibling tools like 'get_import_error' (singular) and 'get_event_logs' (which might include errors), the description offers no context for selection. It lacks prerequisites 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 full burden for behavioral disclosure. 'List datasets' implies a read-only operation but doesn't specify pagination behavior, authentication requirements, rate limits, or what constitutes a 'dataset' in this context. The two-word description leaves critical behavioral aspects undocumented for a tool with 5 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 extremely concise at just two words, which could be appropriate if it were more informative. However, given the tool's complexity (5 parameters, no annotations), this brevity represents under-specification rather than efficient communication. It's front-loaded but lacks substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 undocumented parameters, no annotations, no output schema, and multiple sibling tools, the two-word description is completely inadequate. It doesn't explain what a 'dataset' is in this system, how results are returned, what filtering options exist, or how this differs from other dataset-related tools. The description fails to provide necessary context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 5 parameters have descriptions in the schema. The tool description 'List datasets' provides no information about any parameters - not even hinting at filtering, pagination, or ordering capabilities. This fails to compensate for the complete lack of schema documentation.
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 'List datasets' clearly states the verb ('List') and resource ('datasets'), providing a basic understanding of the tool's function. However, it lacks specificity about scope or filtering capabilities, and doesn't differentiate from sibling tools like 'get_dataset' (singular) or 'get_dataset_events'. The purpose is clear but minimal.
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_dataset' (singular), 'get_dataset_events', and 'get_dataset_queued_events', there's no indication of when this list operation is appropriate versus more specific dataset-related tools. No context or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'List all connections' implies a read-only operation, but it doesn't specify whether this requires authentication, what the output format is (e.g., paginated list), or any rate limits. For a tool with zero 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 extremely concise at three words, with no wasted text. It's front-loaded with the core action ('List all connections'), making it easy to parse quickly. This efficiency is appropriate for a simple-sounding tool, though it may sacrifice clarity.
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 with no schema descriptions, no annotations, and no output schema), the description is incomplete. It doesn't explain the tool's behavior, parameter usage, or output, leaving the agent with insufficient context to use it effectively. For a list tool with undocumented parameters, more detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 3 parameters (limit, offset, order_by) with 0% schema description coverage, meaning none are documented in the schema. The description 'List all connections' adds no information about these parameters—it doesn't explain what 'limit' controls, how 'offset' works for pagination, or what 'order_by' values are acceptable. This fails to compensate for the low schema coverage.
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 'List all connections' clearly states the verb ('List') and resource ('connections'), which is better than a tautology. However, it lacks specificity about what 'connections' are in this context (e.g., Airflow connections) and doesn't distinguish from sibling tools like 'get_connection' (which fetches a single connection) or 'create_connection' (which creates one). This makes it vague compared to 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_connection' for retrieving a specific connection or 'create_connection' for adding new ones. There's no context about prerequisites, such as authentication or permissions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Get queued Dataset events', which implies a read-only operation, but doesn't cover critical aspects like authentication needs, rate limits, pagination, response format, or error handling. For a tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it appropriately concise. However, it's front-loaded with basic information but lacks depth, which slightly limits its effectiveness despite the brevity.
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 (1 parameter with no schema description, no annotations, no output schema), the description is incomplete. It doesn't explain what 'queued' means, how results are returned, or provide any operational context, making it inadequate for a tool that likely interacts with event systems in a dataset context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the tool description doesn't explain the 'uri' parameter at all. No details are provided on what the URI represents, its format, or examples. Since schema coverage is low, the description fails to compensate, leaving the parameter's meaning unclear.
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 queued Dataset events for a Dataset' clearly states the action (get) and resource (queued Dataset events), but it's vague about scope and doesn't distinguish from siblings like 'get_dataset_events' or 'get_dag_dataset_queued_events'. It specifies the target is 'for a Dataset', which provides some context but lacks detail on what 'queued' means operationally.
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 such as 'get_dataset_events' or 'get_dag_dataset_queued_events'. The description implies it's for retrieving queued events, but it doesn't specify prerequisites, exclusions, or comparison to sibling 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 the full burden of behavioral disclosure. It states 'Get' implies a read operation, but doesn't cover permissions, rate limits, error handling, or response format. For a configuration tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
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 with no wasted words, making it easy to parse. However, it's under-specified rather than concise—it lacks necessary details for effective use, which slightly reduces its utility despite the clean 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 no annotations, 0% schema coverage, no output schema, and multiple sibling tools, the description is incomplete. It doesn't clarify the tool's scope (e.g., vs. 'get_config'), parameter usage, or behavioral aspects, making it inadequate for a tool in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with two required parameters ('section' and 'option') undocumented in the schema. The description adds no meaning beyond the parameter names, failing to explain what 'section' and 'option' refer to, their expected formats, or examples. This doesn't compensate for the coverage gap.
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 a specific option from configuration' clearly states the verb ('Get') and resource ('option from configuration'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_config' or 'get_variable', which also retrieve configuration-related data, leaving ambiguity about when to use 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?
No guidance is provided on when to use this tool versus alternatives. With sibling tools like 'get_config' (likely for broader configuration) and 'get_variable' (for variables), the description offers no context on usage scenarios, prerequisites, or exclusions, 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 'Request re-parsing', which implies a mutation or action, but doesn't clarify if this is idempotent, requires specific permissions, has side effects (e.g., clearing runs), or what happens on success/failure. For a tool with no annotations, this leaves significant gaps in understanding its behavior and safety.
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 with no wasted words, making it easy to parse. However, it's front-loaded but under-specified—while concise, it could benefit from slightly more detail to improve clarity without losing brevity.
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 (a mutation tool with no annotations, 1 undocumented parameter, and no output schema), the description is incomplete. It doesn't explain what re-parsing does, the expected outcome, error conditions, or how it interacts with the system (e.g., Airflow DAGs). For a tool that likely triggers server-side processing, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the schema provides no semantic information. The description adds no details about the 'file_token' parameter (e.g., what it represents, how to obtain it, format constraints). This fails to compensate for the low schema coverage, leaving the parameter's meaning and usage unclear.
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 action ('Request re-parsing') and resource ('a DAG file'), which provides a basic understanding of purpose. However, it's vague about what 're-parsing' entails (e.g., does it trigger validation, reloading, or error detection?) and doesn't distinguish from siblings like 'patch_dag' or 'get_dag_source' that might involve DAG file operations. It avoids tautology by not merely restating the name.
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. For example, it doesn't specify if this should be used after editing a DAG file, to fix parsing errors, or as an alternative to 'patch_dag'. The context is implied (e.g., after file changes), but no explicit when/when-not or sibling comparisons are made, leaving the agent to guess based on the 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 full burden for behavioral disclosure. 'Update' implies mutation, but the description doesn't state what permissions are required, whether the update is partial or complete, what happens to unspecified fields, or what the response looks like. This is a significant gap for a mutation tool with zero 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just 5 words, making it front-loaded and efficient. However, this conciseness comes at the cost of completeness - it's arguably under-specified rather than optimally concise.
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 mutation tool with 8 parameters, 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what a 'connection' is in this context, what fields can be updated, what the update behavior entails, or what to expect as a result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 8 parameters, the description provides no information about parameter meanings beyond the obvious 'conn_id'. It doesn't explain what 'conn_type', 'host', 'port', 'login', 'password', 'schema', or 'extra' represent or how they relate to connection updates, failing to compensate for the schema coverage gap.
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 'Update a connection by ID' clearly states the verb (update) and resource (connection), but it's vague about what aspects of a connection can be updated. It doesn't distinguish this tool from sibling tools like 'patch_dag' or 'update_variable' that also perform updates on 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?
No guidance is provided about when to use this tool versus alternatives. There's no mention of prerequisites (like needing an existing connection ID), when-not-to-use scenarios, or comparison with related tools like 'create_connection' or 'delete_connection' in the sibling list.
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 'update' which implies mutation, but fails to describe permissions needed, whether changes are reversible, side effects (e.g., on dependent processes), or error handling. This is inadequate for a mutation tool with zero 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it's overly terse, bordering on under-specification, which reduces its helpfulness despite the concise 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 complexity (mutation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, parameter meanings, or expected outcomes, leaving significant gaps for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'key' implicitly, without explaining what 'key' represents, the purpose of 'value' and 'description', or their formats (e.g., string types, null handling). This adds minimal value beyond the schema's structure.
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 'Update a variable by key' states the verb ('update') and resource ('variable'), but it's vague about what a 'variable' represents in this context (e.g., configuration, environment, workflow variable). It doesn't differentiate from sibling tools like 'create_variable' or 'delete_variable' beyond the basic action, leaving ambiguity about scope and impact.
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 such as 'create_variable' or 'delete_variable'. The description lacks context about prerequisites (e.g., existing variable), exclusions, or typical scenarios, leaving the agent to infer usage from 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 full burden. 'Fetch all DAGs' implies a read operation but provides no behavioral context about permissions required, rate limits, pagination behavior (despite limit/offset parameters), what 'fetch' actually returns, or whether this is a safe operation. The description doesn't disclose any behavioral traits beyond the minimal implication of retrieval.
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 maximally concise at just three words. There's zero waste or unnecessary elaboration, though this conciseness comes at the cost of completeness. The structure is simple and front-loaded with the core action.
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 7 parameters, 0% schema description coverage, no annotations, no output schema, and numerous sibling alternatives, the description is severely incomplete. It doesn't address what the tool returns, how to use its filtering parameters, when to choose it over other DAG retrieval tools, or any behavioral considerations for a read operation in this system.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 7 parameters, the description 'Fetch all DAGs' provides no parameter semantics whatsoever. It doesn't mention any of the filtering capabilities (limit, offset, tags, only_active, paused, dag_id_pattern, order_by) that the schema reveals, nor does it explain what 'all' means in relation to these parameters.
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 'Fetch all DAGs' states the basic action (fetch) and resource (DAGs), but it's vague about scope and functionality. It doesn't specify what 'all' means in context of the 7 filtering parameters available, nor does it distinguish this from sibling tools like 'get_dag', 'get_dag_details', or 'get_dag_stats' which also retrieve DAG information.
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 about when to use this tool versus alternatives. With 7 sibling tools that also retrieve DAG-related information (get_dag, get_dag_details, get_dag_stats, etc.), the description offers no context about when this list-fetching approach is appropriate versus more targeted retrieval methods.
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 it's a read operation ('Get'), implying non-destructive behavior, but doesn't disclose error handling (e.g., what happens if the ID is invalid), authentication needs, rate limits, or return format. This leaves significant behavioral 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 extremely concise at 4 words, front-loaded with the core action, and has zero wasted words. It efficiently communicates the basic purpose 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 1 parameter with no schema descriptions, no annotations, and no output schema, the description is incomplete. It doesn't explain what a 'connection' is, how to obtain IDs, what data is returned, or error cases, making it inadequate for effective tool use in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description adds minimal meaning beyond the schema. It mentions 'by ID' which clarifies the parameter's purpose, but doesn't explain what a 'conn_id' is (e.g., format, source, or constraints), failing to compensate for the low schema coverage.
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 a connection by ID' clearly states the verb ('Get') and resource ('connection'), but it's vague about what a 'connection' entails in this context. It distinguishes from siblings like 'list_connections' by specifying retrieval by ID rather than listing, but lacks specificity about the connection type or system.
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. It doesn't mention prerequisites (e.g., needing a valid connection ID), exclusions, or compare it to siblings like 'list_connections' for browsing or 'test_connection' for validation.
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 'Get a DAG by ID', implying a read operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what the return value includes (e.g., JSON structure). 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 extremely concise with just four words, front-loaded with the core action. There's no wasted language, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.
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 low schema coverage, the description is incomplete. It doesn't explain what 'get' returns, how to interpret results, or handle errors, making it inadequate for a tool that likely returns complex DAG data in a server with many related operations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description doesn't add any meaning beyond the parameter name 'dag_id'. It doesn't explain what a DAG ID is, its format, or where to find it, failing to compensate for the low schema coverage.
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 a DAG by ID' clearly states the action (get) and resource (DAG), but it's vague about what 'get' entails—whether it retrieves metadata, configuration, or status. It doesn't differentiate from siblings like 'get_dag_details' or 'get_dag_source', which might provide more specific information about the same DAG.
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 like 'get_dag_details', 'get_dag_source', and 'fetch_dags', the description lacks any indication of context, prerequisites, or exclusions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states it 'gets' a representation, implying a read operation, but doesn't cover critical aspects like authentication requirements, rate limits, error conditions, or what the output format looks like. For a tool with zero annotation coverage, this leaves 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 extremely concise with just one sentence and no wasted words. It's front-loaded with the core purpose, though this brevity comes at the cost of completeness. Every word earns its place in conveying the basic intent.
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 (2 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain what 'simplified representation' means, doesn't document parameters, and provides no behavioral context. For a tool that likely returns structured DAG data, this leaves too many unanswered questions for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so parameters 'dag_id' and 'fields' are completely undocumented in the schema. The description doesn't mention either parameter or explain their purpose, format, or constraints. It fails to compensate for the schema's lack of documentation, leaving agents guessing about required inputs.
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 a simplified representation of DAG' clearly states the action (get) and resource (DAG), but it's vague about what 'simplified representation' means compared to siblings like 'get_dag' or 'get_dag_tasks'. It doesn't specify what aspects are simplified or how it differs from other DAG retrieval tools.
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_dag', 'get_dag_tasks', or 'fetch_dags'. The description doesn't mention any prerequisites, constraints, or specific use cases that would help an agent choose this tool over its siblings.
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 offers minimal behavioral insight. It doesn't disclose if this is a read-only operation, what permissions are needed, how errors are handled, or the format of the returned data. 'Get' implies retrieval, but details like rate limits or side effects are missing, 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 extremely concise—a single sentence—and front-loaded with the core action. There's no wasted verbiage, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.
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 (a retrieval operation with 1 parameter), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address what the tool returns, error conditions, or usage context, making it inadequate for effective agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description only mentions 'URI' without adding meaning. It doesn't explain what a URI is in this context, its format, or examples, failing to compensate for the schema's lack of documentation.
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 a dataset by URI' clearly states the action (get) and resource (dataset), but it's vague about what 'get' entails—does it fetch metadata, content, or both? It doesn't differentiate from sibling tools like 'get_datasets' (plural) or 'get_dataset_events', leaving ambiguity in scope.
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. For example, it doesn't explain if this is for retrieving a single dataset by identifier while 'get_datasets' is for listing multiple, or how it relates to 'get_dataset_events'. The description lacks context for selection among similar 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. 'Get a task by ID' implies a read-only operation, but it doesn't disclose behavioral traits such as error handling (e.g., what happens if the ID is invalid), authentication needs, rate limits, or return format. This is a significant gap 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 extremely concise—a single sentence with no wasted words. It's front-loaded and efficiently states the core action, though this brevity contributes to gaps in other dimensions.
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 (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what a 'task' is, how parameters relate, what data is returned, or error conditions. For a tool in a server with many similar siblings, more context is needed to guide proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 2 parameters with 0% description coverage, so the schema provides no semantic information. The description adds minimal value by implying parameters are IDs, but doesn't explain what 'dag_id' and 'task_id' represent, their formats, or relationships. It fails to compensate for the low schema coverage.
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 a task by ID' clearly states the verb ('Get') and resource ('task'), but it's vague about what 'get' entails (e.g., retrieve metadata, fetch details) and doesn't distinguish it from siblings like 'get_tasks' (plural) or 'get_task_instance'. It specifies 'by ID', which helps, but lacks precision on what a 'task' is in this 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. It doesn't mention prerequisites, context (e.g., after fetching a DAG), or exclusions. With many sibling tools like 'get_tasks', 'get_task_instance', and 'get_dag_tasks', the agent has no help in choosing correctly.
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 for behavioral disclosure. It states it 'gets' data, implying a read-only operation, but doesn't mention pagination behavior (despite limit/offset parameters), authentication needs, rate limits, or what happens if no entries match. This leaves significant gaps for a tool with 7 parameters.
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 extremely concise at three words, with no wasted language. It's front-loaded with the core action, though this brevity comes at the cost of completeness.
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 (7 parameters, 3 required), lack of annotations, and no output schema, the description is inadequate. It doesn't explain what XCom entries are, how results are returned, or address behavioral aspects like error handling. For a data retrieval tool in this context, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what XCom entries are, how parameters like dag_id, task_id, or map_index relate to filtering, or the purpose of limit/offset for pagination. This fails to provide meaning beyond the bare schema.
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 all XCom entries' clearly states the verb ('Get') and resource ('XCom entries'), but it's vague about scope and doesn't differentiate from sibling tools like 'get_xcom_entry' (singular). It doesn't specify whether this retrieves all entries globally or with filtering, leaving ambiguity.
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_xcom_entry' (singular) or other data retrieval tools in the sibling list. The description offers no context about prerequisites, filtering capabilities, or typical 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. 'Trigger a DAG' implies a write/mutation operation, but it doesn't specify whether this creates a new DAG run, what happens if a run already exists, whether it's idempotent, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in safety and 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 extremely concise at just 4 words, with zero wasted language. It's front-loaded with the core action and resource. While it's under-specified for a tool with 7 parameters, it's not verbose or poorly structured—it just lacks necessary detail.
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 (7 parameters, mutation operation, no output schema, 0% schema description coverage, no annotations), the description is incomplete. It doesn't explain what the tool returns, how parameters interact, error conditions, or behavioral nuances. For a tool that likely initiates workflow executions, this leaves critical gaps for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 7 parameters have descriptions in the schema. The tool description adds no parameter information beyond the name 'dag_id' implied by 'by ID'. It doesn't explain what 'dag_run_id', 'data_interval_start/end', 'execution_date', 'logical_date', or 'note' are for, leaving most parameters undocumented. The description fails to compensate for the schema gap.
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 'Trigger a DAG by ID' clearly states the action (trigger) and target resource (DAG), which is better than a tautology. However, it lacks specificity about what 'trigger' means in this context (e.g., starting a workflow execution) and doesn't distinguish it from sibling tools like 'update_dag_run_state' or 'pause_dag/unpause_dag' that also affect DAG runs. The purpose is understandable but vague.
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., DAG must exist, be unpaused), when to use it over other DAG-related tools like 'update_dag_run_state', or any constraints (e.g., rate limits, permissions). With many sibling tools affecting DAGs, this omission leaves the agent without context for 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 of behavioral disclosure. 'Create a pool' implies a write operation but doesn't specify permissions required, whether it's idempotent, what happens on failure, or the expected response format. This leaves critical behavioral traits undocumented for a creation tool.
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 extremely concise with just two words, 'Create a pool', which is front-loaded and wastes no space. It efficiently conveys the basic action, though this brevity contributes to gaps in other dimensions like guidelines and transparency.
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 a creation tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameters, return values, and usage context, making it inadequate for an agent to reliably invoke the tool without additional inference or trial-and-error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters with 0% description coverage, and the description adds no parameter information. It doesn't explain what 'name', 'slots', 'description', or 'include_deferred' mean, their constraints, or how they affect pool creation. With low schema coverage, the description fails to compensate, leaving parameters largely unexplained.
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 'Create a pool' states the action (create) and resource (pool), which is clear but vague. It doesn't specify what kind of pool (e.g., resource pool, connection pool) or distinguish it from sibling tools like 'get_pool', 'patch_pool', or 'delete_pool'. The purpose is understandable but lacks specificity.
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., authentication), compare to similar tools like 'patch_pool' for updates, or indicate when not to use it (e.g., for existing pools). Without such context, the agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether this is a destructive mutation, what permissions are required, how state changes affect workflows, or what happens if the DAG run doesn't exist. For a state-update tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and identifiers, making it easy to parse quickly. Every word contributes directly to the tool's purpose.
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 (state mutation), lack of annotations, 0% schema coverage, and no output schema, the description is insufficient. It doesn't cover behavioral risks, parameter details, return values, or error conditions. For a mutation tool in a workflow system, more context is needed to use it safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but only partially does. It mentions 'DAG ID' and 'DAG run ID' as identifiers, mapping to two required parameters, but doesn't explain the 'state' parameter's purpose, possible values (e.g., 'running', 'failed'), or that it's optional with a default of null. This leaves key parameter meaning undocumented.
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 ('Update') and target ('DAG run state') with specific identifiers ('by DAG ID and DAG run ID'). It distinguishes this from siblings like 'delete_dag_run' or 'set_task_instances_state' by focusing on state modification rather than deletion or task-level changes. However, it doesn't fully differentiate from 'set_dag_run_note' which might also involve DAG run updates.
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 'set_task_instances_state' or 'clear_dag_run'. It mentions no prerequisites, constraints, or typical scenarios for updating DAG run states, 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a mutation operation ('Update') but doesn't disclose required permissions, whether changes are reversible, side effects (e.g., on downstream tasks), or response format. It mentions the 'state' parameter indirectly but doesn't explain its role or valid values, leaving critical behavioral aspects undocumented.
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 that front-loads the core action and key identifiers. There's no wasted verbiage or redundancy. However, it could be more structured by explicitly separating the update action from parameter explanations, but its brevity is appropriate for the minimal content provided.
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 (mutation with 4 parameters, no annotations, no output schema), the description is inadequate. It lacks behavioral details (e.g., error conditions, idempotency), parameter explanations (especially for 'state'), and comparison to siblings. For a mutation tool in a workflow system, this leaves the agent with significant gaps in understanding how to use it correctly and safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds limited value. It lists three required identifiers (DAG ID, DAG run ID, task ID) which map to parameters, clarifying they are needed to locate the instance. However, it doesn't explain the optional 'state' parameter's purpose, valid values, or default behavior, leaving 25% of parameters (1 of 4) without semantic context in either schema or description.
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 ('Update') and the target resource ('a task instance'), providing specific identifiers (DAG ID, DAG run ID, task ID). It distinguishes the tool's focus on updating existing instances rather than creating or deleting them. However, it doesn't explicitly differentiate from similar sibling tools like 'set_task_instances_state' or 'update_dag_run_state'.
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., the task instance must exist), compare it to sibling tools like 'set_task_instances_state' (which might handle multiple instances), or specify use cases (e.g., correcting state, updating metadata). The agent must infer usage from the tool name and 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is 'Delete', implying a destructive mutation, but does not clarify permissions needed, whether the deletion is reversible, or what happens on success/failure. This is a significant gap for a mutation tool.
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 action and resource, 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?
For a destructive mutation tool with no annotations, 0% schema coverage, and no output schema, the description is inadequate. It lacks details on behavior, parameters, outcomes, and error handling, leaving critical 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.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It mentions 'a queued Dataset event for a DAG', which hints at 'dag_id' and 'uri' but does not define their semantics, formats, or examples. The description adds minimal value beyond the schema's structure.
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 ('Delete') and the target resource ('a queued Dataset event for a DAG'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'delete_dag_dataset_queued_events' (plural) or 'delete_dataset_queued_events', leaving some ambiguity about scope.
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 does not mention prerequisites, such as needing an existing queued event, or specify scenarios where this deletion is appropriate, leaving the agent to infer usage from the 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 full burden. It states 'Delete' which implies a destructive mutation, but doesn't disclose behavioral traits like permissions needed, whether deletion is reversible, rate limits, or what 'queued' means operationally. This is inadequate for a mutation tool with zero 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 with no wasted words. It's front-loaded with the core action and target, 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?
For a destructive mutation tool with 2 parameters (0% schema coverage), no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameters, error conditions, and doesn't compensate for the missing structured data, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so parameters are undocumented in the schema. The description mentions 'for a DAG', which hints at 'dag_id', but doesn't explain 'before' parameter or provide any semantic context for either parameter. It adds minimal value beyond the schema.
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 ('Delete') and target ('queued Dataset events for a DAG'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'delete_dag_dataset_queued_event' (singular) or 'delete_dataset_queued_events' (without DAG context), leaving some ambiguity about scope.
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 multiple deletion-related siblings (e.g., 'delete_dag_dataset_queued_event', 'delete_dataset_queued_events'), the description lacks context about scope, prerequisites, or comparative 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. While 'Delete' implies a destructive mutation, the description doesn't specify whether this action is reversible, what permissions are required, or what happens if the dataset or events don't exist. It also doesn't describe the return value or error conditions, leaving the agent with incomplete 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 with no wasted words. It's front-loaded with the core action and resource, making it easy to scan. Every word contributes directly to stating the tool's purpose, achieving optimal conciseness.
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 a destructive operation with two parameters, no annotations, and no output schema, the description is inadequate. It lacks details on parameter usage, behavioral traits like idempotency or error handling, and expected outcomes. For a tool that modifies system state, this leaves too many unknowns for reliable agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, with two parameters (uri and before) undocumented. The description mentions 'for a Dataset', which hints that 'uri' might refer to a dataset identifier, but provides no format or examples. It doesn't explain 'before' at all, leaving its purpose (e.g., timestamp filter) ambiguous. This fails to compensate for the low schema 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 action ('Delete') and target resource ('queued Dataset events for a Dataset'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'delete_dag_dataset_queued_event' or 'delete_dag_dataset_queued_events', which appear to handle similar operations but for DAGs rather than Datasets specifically.
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, such as needing a valid dataset URI, or clarify whether this deletes all queued events or only those before a certain time. With many sibling tools for dataset and DAG operations, the lack of differentiation is a significant gap.
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 'Delete' implying a destructive mutation, but does not disclose behavioral traits such as permissions required, whether deletion is permanent or reversible, error handling (e.g., if key doesn't exist), or side effects. This is a significant gap for a mutation tool with zero 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 with zero waste—'Delete a variable by key' is front-loaded and directly conveys the core action. Every word earns its place, 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 (destructive mutation), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It fails to address key aspects like behavioral transparency, parameter details, or expected outcomes, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter 'key' undocumented in the schema. The description adds minimal semantics by specifying 'by key', implying the parameter identifies the variable to delete, but does not explain what 'key' represents (e.g., variable name, identifier format) or constraints. It partially compensates but leaves the parameter meaning vague.
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 'Delete a variable by key' clearly states the action (delete) and resource (variable), with the method specified (by key). It distinguishes from siblings like 'get_variable' (read) and 'update_variable' (modify), but does not explicitly differentiate from 'clear_dag_run' or other deletion tools, keeping it at 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?
No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites (e.g., variable must exist), exclusions, or related tools like 'create_variable' or 'update_variable' for context. The description is purely functional without usage context.
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 'Get' implying a read operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'queued' means operationally. For a tool with no annotation coverage, this leaves 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, efficient sentence with no wasted words. It's front-loaded with the core action and resource, 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, 0% schema coverage, no output schema, and multiple similar sibling tools, the description is incomplete. It lacks details on behavior, parameter usage, return values, and differentiation from alternatives, making it inadequate for a tool with 2 required parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so parameters 'dag_id' and 'uri' are undocumented in the schema. The description adds no meaning beyond the tool name, failing to explain what these parameters represent, their format, or how they identify the event. This doesn't compensate for the coverage gap.
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 ('queued Dataset event for a DAG'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_dag_dataset_queued_events' (plural) or 'get_dataset_queued_events', leaving some ambiguity about scope.
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 siblings like 'get_dag_dataset_queued_events' (plural) and 'get_dataset_queued_events', the description lacks context on whether this fetches a single event, how it relates to other get_* tools, or any prerequisites.
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 'Get' implies a read operation, but does not disclose behavioral traits such as whether it returns all queued events, pagination, error handling, or if it requires specific permissions. This is inadequate 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 is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, 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 complexity (a read operation with one parameter), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on return values, error conditions, and usage context, which are essential for effective tool invocation in this environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not add any meaning beyond the input schema, which only shows 'dag_id' as a required string. No details on format, constraints, or examples are provided, leaving parameters poorly documented.
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 the resource ('queued Dataset events for a DAG'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_dag_dataset_queued_event' (singular) or 'get_dataset_queued_events' (general), leaving some ambiguity about scope.
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. For example, it does not specify if this is for monitoring queued events, debugging, or how it differs from 'get_dag_dataset_queued_event' (singular) or 'delete_dag_dataset_queued_events'. The description lacks context for selection among siblings.
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 it 'gets' a DAG run, implying a read-only operation, but doesn't disclose behavioral traits like error handling (e.g., what happens if IDs are invalid), authentication needs, rate limits, or response format. This leaves gaps for safe and effective use.
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 directly states the tool's purpose without fluff. It's appropriately sized for a simple retrieval tool and front-loaded with essential information.
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, 0% schema coverage, no output schema, and a read operation with two required parameters, the description is incomplete. It lacks details on parameter semantics, behavioral context (e.g., errors, permissions), and what the tool returns, making it inadequate for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions parameters 'dag_id' and 'dag_run_id' but adds no meaning beyond their names—no explanation of what these IDs represent, their format, or where to obtain them. This is insufficient for a tool with two required parameters.
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 ('a DAG run'), specifying it's retrieved by DAG ID and DAG run ID. It distinguishes from sibling tools like 'get_dag_runs' (plural) which likely lists multiple runs, but doesn't explicitly contrast with 'get_dag' or 'get_task_instance' which fetch 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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing existing DAG and run IDs), contrast with 'get_dag_runs' for listing runs, or specify use cases like monitoring or debugging. The agent must infer usage from the name and context 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 full burden. It states a read operation ('Get'), implying it's likely non-destructive, but doesn't disclose any behavioral traits such as authentication needs, error handling (e.g., what happens if ID doesn't exist), rate limits, or return format. 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 with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, 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 simplicity (1 parameter) but lack of annotations and output schema, the description is incomplete. It doesn't explain what a 'log entry' contains, how results are structured, or potential errors, leaving the agent with inadequate context for reliable use despite the straightforward operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the schema provides no semantic context. The description mentions 'by ID', which adds some meaning for the 'event_log_id' parameter, but doesn't specify ID format, valid ranges, or examples. This partially compensates but is insufficient given the low schema 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 'Get a specific log entry by ID' clearly states the verb ('Get') and resource ('log entry'), and specifies the lookup method ('by ID'), which is helpful. However, it doesn't distinguish this tool from sibling tools like 'get_event_logs' (plural) or 'get_log', leaving some ambiguity about scope.
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_event_logs' (plural) and 'get_log' present, the agent lacks explicit direction on whether this is for single-entry retrieval versus bulk operations or different log types.
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 operation. It doesn't disclose whether this is a read-only operation, what format/log level the log returns, potential size limits, authentication requirements, or error behavior. The description is minimal and lacks 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, efficient sentence that directly states the tool's purpose and required parameters. It's front-loaded with the core operation and wastes no words, making it easy to parse despite its brevity.
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 4 required parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain what the log contains, its format, size considerations, or error scenarios. The agent lacks critical context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but only lists parameter names without explaining their meaning or relationships. It doesn't clarify what DAG ID, task ID, DAG run ID, or task try number represent, how to obtain them, or their expected formats, leaving significant 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 the resource 'log from a task instance', specifying it retrieves log content. It distinguishes from siblings like get_event_log or get_task_instance by focusing specifically on task execution logs, though it doesn't explicitly contrast them.
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_event_log or get_task_instance. It lists required parameters but offers no context about prerequisites, error conditions, or appropriate use cases beyond the basic operation.
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 it 'gets a list' which implies a read-only operation, but doesn't disclose behavioral traits like pagination (implied by limit/offset parameters), authentication needs, rate limits, or what 'loaded providers' entails. The description is minimal and lacks context beyond the basic action.
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 and appropriately sized for a simple list operation, though this conciseness comes at the cost of detail.
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, 0% schema coverage, no output schema, and two parameters, the description is incomplete. It doesn't explain what 'loaded providers' are, how results are structured, or parameter usage. For a tool with undocumented inputs and no output schema, more context is needed to be adequately helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It provides no information about the two parameters (limit and offset), their purposes, or how they affect the list retrieval. The description fails to add meaning beyond the bare schema, leaving parameters semantically unclear.
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 'Get a list of loaded providers' clearly states the action (get) and resource (loaded providers). It distinguishes from siblings like get_connection or get_plugins by specifying 'providers' as the target resource, though it doesn't explicitly differentiate from other list operations like list_connections or list_variables beyond the resource name.
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. It doesn't mention prerequisites, context, or compare to similar tools like get_plugins or list_connections, leaving the agent to infer usage based on the 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 full burden. It states a read operation ('Get') but doesn't disclose behavioral traits such as permissions needed, error handling (e.g., if IDs are invalid), response format, or rate limits. 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 with zero waste, front-loading the core action and parameters. It's appropriately sized for the tool's purpose 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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameter meanings, return values, and usage context, making it inadequate for a 3-parameter tool in a complex server environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only names the parameters (dag_id, task_id, dag_run_id) without explaining their semantics, formats, or examples. It adds minimal value beyond the schema, failing to compensate for the low 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 the resource 'a task instance', specifying it's retrieved by three identifiers (DAG ID, task ID, and DAG run ID). It distinguishes from siblings like 'list_task_instances' by focusing on a single instance retrieval, though it doesn't explicitly mention this 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 'list_task_instances' or 'get_task'. The description implies usage for retrieving a specific task instance but lacks context on prerequisites, error cases, or comparisons to 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?
With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It lacks information on permissions, rate limits, pagination, or what constitutes 'dataset events', making it insufficient for safe and effective use.
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, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose 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 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It fails to explain parameter meanings, behavioral traits, or return values, which are critical for this data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter details. It does not explain what 'dag_id' or 'dag_run_id' represent, their formats, or how they relate to dataset events, leaving parameters semantically unclear.
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 ('dataset events for a DAG run'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'get_dataset_events' (which lacks the DAG run context), leaving some ambiguity about scope.
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 (e.g., needing a valid DAG run), exclusions, or comparisons to siblings like 'get_dataset_events', 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 it's a list operation (implied read-only) but doesn't disclose behavioral traits like pagination (implied by limit/offset parameters), rate limits, authentication needs, return format, or whether it's destructive. The description is minimal and lacks critical 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?
Extremely concise with a single, front-loaded sentence that states the core purpose. There's no wasted text, though this brevity contributes to gaps in other dimensions.
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 (17 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the rich filtering options, return values, or operational behavior. For a tool with many parameters and no structured documentation, this minimal description is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only mentions 'dag_id' and 'dag_run_id', ignoring 15 other parameters (e.g., date ranges, state, pool, limit/offset). No parameter semantics, formats, or examples are provided, leaving most inputs undocumented.
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 ('List') and resource ('task instances'), specifying filtering by 'DAG ID and DAG run ID'. It distinguishes from siblings like 'get_task_instance' (singular) and 'list_task_instance_tries', but doesn't explicitly differentiate from broader listing tools like 'get_dag_runs'.
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 on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing valid DAG IDs), exclusions, or compare with siblings like 'get_task_instance' (for single instance) or 'list_task_instance_tries' (for retry details).
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 implies a read-only list operation but doesn't disclose behavioral traits like pagination (handled by limit/offset), ordering (order_by), error conditions, or output format. For a tool with 6 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 with zero waste. It's front-loaded with the core action and key identifiers, making it easy to parse. Every word contributes directly to the tool's purpose.
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 (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return values, pagination behavior, or how parameters interact. For a list operation with filtering and sorting options, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions three required parameters (dag_id, dag_run_id, task_id) but omits the optional ones (limit, offset, order_by) and provides no semantic context for any parameters. This leaves most parameters undocumented and their purposes unclear.
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 ('List') and resource ('task instance tries'), specifying the key identifiers (DAG ID, DAG run ID, task ID) needed. It distinguishes from siblings like 'list_task_instances' by focusing on 'tries', but doesn't explicitly contrast them. The purpose is specific and actionable.
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 'list_task_instances' or 'get_task_instance'. The description only states what it does, not when it's appropriate or what prerequisites exist. This leaves the agent to infer usage from context.
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 'update' without clarifying behavioral traits. It doesn't mention whether this is a safe operation, what permissions are required, if changes are reversible, rate limits, or what happens to DAGs matching the pattern. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just three words, front-loading the core action. There's no wasted language, though this brevity contributes to underspecification in other dimensions.
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 a mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what DAGs are, what 'update' entails, parameter usage, or expected outcomes, leaving significant gaps for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'dag_id_pattern', 'is_paused', or 'tags' mean, their formats, or how they interact to update DAGs. With 3 undocumented parameters, the description adds no value beyond the schema.
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 'Update multiple DAGs' clearly states the verb ('update') and resource ('multiple DAGs'), making the purpose understandable. It distinguishes from the sibling 'patch_dag' (singular) by specifying 'multiple', but doesn't explain what DAGs are or what aspects are updated beyond the implied scope.
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 'patch_dag' (for single DAG updates), 'pause_dag', or 'unpause_dag'. The description mentions 'multiple DAGs' but doesn't specify prerequisites, constraints, or typical use cases for batch updates.
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. 'Update' implies a mutation operation, but it doesn't specify whether this requires special permissions, if changes are reversible, what happens to existing notes, or any rate limits/error conditions. This is inadequate for a mutation tool with zero 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 with zero wasted words. It's appropriately sized for a simple update operation and front-loads the essential information.
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 mutation tool with 3 undocumented parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what a DagRun note is, what format the note should take, what permissions are required, or what the tool returns. The context demands more completeness than provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 3 parameters (dag_id, dag_run_id, note) are documented in the schema. The description adds no parameter information beyond what's implied by the tool name, failing to compensate for the complete lack of schema documentation.
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 ('Update') and the target resource ('DagRun note'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'update_dag_run_state' or 'update_task_instance' that also modify DAG-related entities, missing 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 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. There are no mentions of prerequisites, appropriate contexts, or exclusions, leaving the agent without usage direction despite having many sibling tools that modify DAG-related entities.
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. 'Delete' implies a destructive mutation, but it doesn't specify if this is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting dependent DAGs). This is a significant gap for a destructive tool with zero 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 with zero waste—it directly states the action and required parameter. It's appropriately sized and front-loaded, 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 this is a destructive tool with no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It lacks critical details like behavioral traits, parameter specifics, and expected outcomes, which are essential for safe and 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 schema description coverage is 0%, so the description must compensate. It mentions 'by ID', which adds meaning to the 'conn_id' parameter by indicating it's an identifier, but doesn't explain the ID format, source, or constraints. This provides some value but doesn't fully compensate for the coverage gap.
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 ('Delete') and resource ('a connection by ID'), making the purpose unambiguous. However, it doesn't distinguish this tool from other deletion tools like delete_dag, delete_dag_run, or delete_variable, which would require mentioning what type of connection is being deleted or its 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing the connection ID from get_connection or list_connections), when not to use it, or how it differs from update_connection or clear_dag_run for related operations.
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 it's a deletion operation, implying it's destructive, but doesn't specify whether this is permanent, reversible, requires specific permissions, or has side effects (e.g., on related tasks or data). For a destructive tool with zero annotation coverage, this is a significant gap in safety and 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 with no wasted words. It's front-loaded with the core action and directly states the required identifiers, 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?
For a destructive tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks critical information about behavioral traits (e.g., permanence, permissions), parameter details, and usage context compared to siblings like 'clear_dag_run'. This leaves the agent under-informed for safe and 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 description mentions parameters ('by DAG ID and DAG run ID'), which aligns with the two required parameters in the schema. However, schema description coverage is 0%, so the schema provides no details about these parameters. The description adds basic semantic context (what the parameters identify) but doesn't explain format, constraints, or examples, leaving significant 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 ('Delete') and resource ('a DAG run'), specifying it's identified by DAG ID and DAG run ID. It distinguishes from sibling tools like 'delete_dag' (which deletes the DAG itself) and 'clear_dag_run' (which clears but may not delete). However, it doesn't explicitly differentiate from 'clear_dag_run' in terms of permanent vs temporary removal.
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 'clear_dag_run' or 'delete_dag'. The description only states what it does, not when it's appropriate, what prerequisites exist, or what the consequences are compared to similar 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 full burden. It implies a read-only operation ('Get'), but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or what 'status' entails (e.g., uptime, metrics, alerts). For a tool with zero annotation coverage, 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 extremely concise ('Get instance status') with no wasted words, making it easy to parse. It's front-loaded with the core action and resource, though its brevity contributes to vagueness in other dimensions.
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 simplicity (0 parameters, no output schema), the description is minimal but insufficient. It lacks context about what 'instance status' means, how it differs from other get_* tools, and what the output might contain. With no annotations or output schema, more detail is needed to make it complete for effective use.
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 documentation is needed. The description doesn't add parameter semantics, but that's appropriate here. A baseline of 4 is applied as it adequately handles the lack of parameters without introducing confusion.
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 instance status' clearly indicates a read operation ('Get') on a resource ('instance status'), but it's vague about what 'instance' refers to in this context. It doesn't distinguish this tool from siblings like get_config, get_version, or get_health (if present), leaving ambiguity about what specific status information is retrieved.
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 (e.g., get_config, get_version, get_dag_stats), the description lacks context about whether this is for overall system health, specific component status, or other purposes, offering no help in 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'gets' an import error, implying a read-only operation, but doesn't specify if it requires authentication, what happens if the ID doesn't exist (e.g., returns null or error), or any rate limits. This leaves significant gaps for a tool that likely queries a system.
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, direct sentence that efficiently conveys the core functionality without unnecessary words. It's front-loaded with the key action and resource, 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 lack of annotations, 0% schema description coverage, and no output schema, the description is insufficient. It doesn't explain what an 'import error' is in this context, what data is returned, or error handling, leaving the agent with incomplete information for reliable 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 description mentions 'by ID', which aligns with the single parameter 'import_error_id' in the schema. However, with 0% schema description coverage, the schema only indicates it's an integer without explaining what constitutes a valid ID (e.g., format, source). The description adds minimal value beyond the schema's basic type information.
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 ('a specific import error by ID'), making the purpose immediately understandable. However, it doesn't differentiate from its sibling 'get_import_errors' (plural), which appears to retrieve multiple errors, leaving some ambiguity about when to use each.
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_import_errors' or other error-related tools. It lacks context about prerequisites, such as needing an existing import error ID, or exclusions for when it shouldn't be used.
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 for behavioral disclosure. 'Get a list' implies a read-only operation, but it doesn't specify whether this requires authentication, what format the list returns (names, metadata, status), whether it's paginated, or if there are rate limits. For a tool with zero annotation coverage, 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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple list operation. Every word earns its place, 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 simplicity (2 optional parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what 'loaded plugins' means in this context, what information is returned, or how the parameters affect the result. For even a basic list tool, more context about the return format and parameter usage would be 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?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. However, the description mentions nothing about the 'limit' and 'offset' parameters shown in the schema. While 'Get a list' implies potential pagination, it doesn't explicitly connect to these parameters or explain their purpose. The description adds no value beyond what's inferred from the schema structure.
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 ('list of loaded plugins'), making the purpose immediately understandable. It distinguishes itself from sibling tools that mostly deal with DAGs, connections, datasets, and variables rather than plugins. However, it doesn't specify what information about plugins is returned or the scope of 'loaded' (e.g., active vs. all available).
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 (like get_providers, get_config, get_version), there's no indication of when plugins specifically should be queried versus other system components. No prerequisites, exclusions, or comparison to similar tools are mentioned.
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 'Get a pool by name,' implying a read operation, but doesn't clarify if this requires authentication, returns specific data formats, handles errors (e.g., if the pool doesn't exist), or has rate limits. This leaves significant gaps for an agent to understand how to invoke it safely and effectively.
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 'Get a pool by name' is extremely concise and front-loaded, with no wasted words. It efficiently conveys the core action in a single phrase, making it easy for an agent to parse and understand 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 simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It lacks details on behavioral aspects (e.g., error handling, authentication), parameter specifics, and how it differs from siblings like 'get_pools'. For a read operation in a server with many tools, more context would help an agent 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?
The input schema has 1 parameter ('pool_name') with 0% description coverage, meaning the schema provides no details about this parameter. The description adds minimal semantics by implying 'pool_name' is used to look up a pool, but doesn't specify format, constraints, or examples. Since schema coverage is low, the description partially compensates but not fully, warranting a baseline score.
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 'Get a pool by name' clearly states the verb ('Get') and resource ('pool'), and specifies the lookup method ('by name'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_pools' (plural) or 'patch_pool', leaving room for confusion about when to use this versus 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?
No guidance is provided on when to use this tool versus alternatives like 'get_pools' (which likely lists multiple pools) or 'patch_pool' (which modifies pools). The description implies it's for retrieving a single pool by name, but lacks explicit context or exclusions, such as whether it's for read-only access or requires specific permissions.
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. 'Get version information' implies a read-only operation, but it doesn't specify any behavioral traits such as authentication requirements, rate limits, or what the output format might be. For a tool with zero 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 extremely concise with just three words, front-loaded with the key action and resource. There is zero waste or redundancy, making it easy to parse quickly. Every word earns its place by directly conveying the tool's purpose without extra fluff.
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 is low (0 parameters, no output schema), the description is minimal but adequate for basic understanding. However, with no annotations and no output schema, it lacks completeness in terms of behavioral context and expected return values. For a tool that might return structured version data, more detail would be helpful, but it's not critically incomplete.
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 doesn't need to add parameter semantics, and it appropriately doesn't mention any. This meets the baseline for tools with no parameters, as it avoids unnecessary details.
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 version information' clearly states the verb ('Get') and resource ('version information'), making the purpose understandable. However, it's somewhat vague about what 'version information' specifically entails (e.g., software version, API version, system version) and doesn't differentiate from siblings like 'get_health' or 'get_config', which could also provide system-related information.
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. Given the sibling tools include other informational tools like 'get_health' and 'get_config', the description lacks context on when version information is needed or how it differs from other get operations. This leaves the agent without explicit usage instructions.
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 offers minimal behavioral insight. It states the action is to 'pause' a DAG, implying a state change (likely from active to paused), but doesn't disclose effects (e.g., halts future runs, leaves current runs unaffected), permissions required, or error conditions. This is inadequate for a mutation tool with zero 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 extremely concise with a single, front-loaded sentence: 'Pause a DAG by ID'. Every word earns its place—verb, resource, and identifier method—with zero redundancy. It's appropriately sized for a simple tool.
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 (a mutation with no annotations, 1 parameter, 0% schema coverage, and no output schema), the description is incomplete. It lacks details on behavior (e.g., what pausing entails), error handling, return values, or prerequisites. For a tool that alters system state, this leaves significant gaps for an AI 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?
The description adds minimal meaning beyond the input schema. It specifies 'by ID', indicating the single parameter 'dag_id' is an identifier, but the schema already defines it as a string with 0% description coverage. This provides basic context but doesn't detail format (e.g., string pattern) or examples. With one parameter and low schema coverage, it partially compensates but remains vague.
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 'Pause a DAG by ID' clearly states the action (pause) and target resource (DAG), with 'by ID' specifying the identifier method. It distinguishes from siblings like 'unpause_dag' (opposite action) and 'delete_dag' (different operation), though it doesn't explicitly contrast them. The purpose is specific 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 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., DAG must be active), exclusions (e.g., cannot pause if running), or direct comparisons to siblings like 'unpause_dag' or 'set_task_instances_state'. Usage is implied only by the verb 'pause'.
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, the description carries full burden but only states the action without behavioral details. It doesn't mention permissions required, whether it's idempotent, what happens if the DAG isn't paused, or the response format. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, 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?
For a mutation tool with no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks behavioral context, parameter details, usage guidance, and expected outcomes, leaving significant gaps for an AI agent to operate 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?
Schema description coverage is 0%, but the description adds minimal context by specifying 'by ID' for the single parameter 'dag_id'. However, it doesn't explain what a DAG ID is, its format, or where to find it. With one parameter and low coverage, this provides basic but insufficient compensation.
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 ('Unpause') and resource ('a DAG by ID'), making the purpose immediately understandable. It doesn't differentiate from its sibling 'pause_dag' beyond the opposite action, but the purpose is unambiguous. A 5 would require explicit distinction from siblings.
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 'patch_dag' or 'update_dag_run_state', nor prerequisites such as whether the DAG must be paused first. The description only states what it does, not when it's appropriate.
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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