Agent Farm
Server Quality Checklist
Latest release: v3.1.0
- Disambiguation2/5
Multiple tools have overlapping or unclear boundaries, causing ambiguity. For example, 'chunked_analysis', 'deep_analysis_swarm', 'recon_swarm', and 'system_health_swarm' all involve analysis but with vague distinctions in purpose. Similarly, 'deploy_swarm', 'quick_swarm', and 'tool_swarm' all handle task deployment with unclear differences, making it hard for an agent to choose the right one.
Naming Consistency3/5The naming conventions are mixed, with some tools using snake_case (e.g., 'api_swarm', 'chunked_analysis') and others using more descriptive phrases (e.g., 'deep_analysis_swarm', 'system_health_swarm'). While there is a general pattern of appending '_swarm' to many tools, it's not consistently applied across all tools, leading to a readable but inconsistent set.
Tool Count2/5With 25 tools, the count feels excessive for the apparent scope of managing agent colonies and parallel task execution. Many tools seem redundant or overly specialized, such as having separate tools for 'cleanup_idle', 'colony_status', 'list_colonies', and 'quick_colony', which could likely be consolidated into fewer, more general-purpose tools.
Completeness4/5The tool set covers a wide range of operations for agent colony management and parallel task execution, including spawning, deploying, monitoring, and synthesizing results. However, there are minor gaps, such as the lack of tools for updating or configuring existing colonies beyond dissolution, and some tools like 'heavy_write' seem redundant with functionality in others like 'tool_swarm'.
Average 3.1/5 across 25 of 25 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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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
- 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 'parallel' processing and 'optionally synthesize,' hinting at concurrency and output merging, but fails to detail critical aspects like rate limits, error handling, authentication needs, or what 'synthesize' entails (e.g., aggregation, summarization). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The examples are concise and relevant, though the structure could be slightly improved by separating usage notes from examples. Overall, it avoids unnecessary verbosity and earns its place with efficient sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (parallel querying with synthesis), no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on output format, error conditions, performance implications, and how synthesis integrates with results, making it inadequate for an agent to use the tool effectively without guesswork.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 explains 'queries' as a 'JSON array of query strings OR single topic to auto-expand' with examples, adding meaning beyond the schema's basic string type. However, it doesn't clarify the 'synthesize' parameter's effect or default behavior, leaving half the parameters inadequately explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Query KMKB from multiple angles in parallel, optionally synthesize,' which provides a general purpose (querying KMKB with parallel processing and optional synthesis). However, it lacks specificity about what KMKB is (a knowledge base, database, etc.) and doesn't clearly differentiate from sibling tools like 'api_swarm' or 'synthesize,' making it vague rather than distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes examples of query formats (JSON array or single topic) but offers no guidance on when to use this tool versus alternatives like 'synthesize' or other swarm tools. It implies usage for parallel querying but doesn't specify contexts, prerequisites, or exclusions, leaving the agent with minimal direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'One-shot' and the sequence of actions, but doesn't disclose critical behavioral traits such as whether it's read-only or destructive, authentication needs, rate limits, error handling, or what 'return results' entails. This leaves significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with key actions, using minimal sentences. However, the second sentence 'tasks: JSON array or single prompt string' could be integrated more smoothly, and some redundancy exists in listing actions without additional value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by spawning and deploying, no annotations, no output schema, and low schema coverage, the description is inadequate. It lacks details on what the tool returns, error conditions, or how it interacts with sibling tools, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 'tasks: JSON array or single prompt string', which adds some meaning beyond the schema's generic 'string' type for 'tasks'. However, it doesn't explain the 'colony_type' parameter or provide details on task format, making it incomplete for the two parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool performs three actions: 'spawn colony + deploy swarm + return results', which gives a general purpose. However, it's vague about what these actions entail and doesn't differentiate from sibling tools like 'spawn_colony', 'deploy_swarm', or 'quick_colony'. 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 Guidelines2/5Does 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 'api_swarm', 'code_gen_swarm', and 'quick_colony', the description fails to indicate appropriate contexts, exclusions, or prerequisites for use.
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 information. It lists available subtools but doesn't explain how they're used, what permissions are needed, whether this creates/destroys resources, or what the execution model is. The mention of 'worker' and 'tools' hints at some execution capability but lacks operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and structured with bullet-like formatting. However, the first sentence 'Single worker bug with tools to complete a task' is confusing and could be more clearly phrased. The tool listing and parameter explanations are efficiently presented without unnecessary verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain what happens when invoked, what results to expect, error conditions, or how it differs from the many sibling swarm/colony tools. The agent lacks sufficient information to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 'task: What to do' and 'context: Optional context/background' which adds basic meaning to parameter names, but doesn't explain format, constraints, or examples. For a tool with 2 parameters and no schema descriptions, this is minimal but not entirely absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Single worker bug with tools to complete a task' which is vague and confusing - 'bug' appears to be a typo or misnomer. It lists available tools (read_file, write_file, etc.) but doesn't clearly state what this tool actually does. The purpose is implied rather than explicitly stated as a specific action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the many sibling tools (api_swarm, chunked_analysis, etc.). The description mentions available subtools but provides no context about appropriate use cases, prerequisites, or alternatives. The agent must infer usage from the tool name and parameter 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 the tool returns multiple components (main code, tests, docstring, usage examples), which adds some context about output behavior. However, it lacks critical details such as whether this is a read-only or mutating operation, performance characteristics (e.g., rate limits), error handling, or authentication needs. The description is minimal and doesn't fully compensate for the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences that are front-loaded: the first states the purpose, and the second lists return components. There's no wasted text, and it efficiently communicates core information. However, it could be slightly improved by integrating the return details into the first sentence for better flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of code generation, no annotations, no output schema, and low schema coverage (0%), the description is incomplete. It lacks details on behavioral traits, parameter usage, error cases, and how the '4 parallel perspectives' work. The mention of return components is helpful but insufficient for a tool with 2 parameters and no structured output documentation, leaving significant gaps for an AI agent to understand proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 mentions 'spec' implicitly ('Generate code from spec') but doesn't explain what a 'spec' entails or provide examples. It doesn't address the 'language' parameter at all, even though it has a default value ('python'). The description adds minimal semantic value beyond the schema, failing to clarify parameter usage or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Generate code from spec with 4 parallel perspectives.' It specifies the verb ('Generate code'), resource ('from spec'), and method ('with 4 parallel perspectives'), distinguishing it from siblings like 'chunked_code_gen' or 'quick_swarm' by emphasizing the parallel approach. However, it doesn't explicitly differentiate from all siblings, such as 'code_review_swarm' or 'exec_swarm', which might have overlapping domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 mentions the output components (main code, tests, docstring, usage examples) but doesn't specify contexts, prerequisites, or exclusions. For example, it doesn't clarify if this is for initial code generation versus refinement, or how it compares to 'chunked_code_gen' or 'synthesize' among the 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 the full burden. It mentions deploying 'guardian bugs' and using a model for synthesis, but lacks details on permissions, rate limits, side effects, or what the output looks like. For a tool that likely interacts with system resources, this is a significant gap in behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main purpose, followed by parameter details. Both sentences are relevant, with no wasted words, making it efficient. However, the second sentence could be slightly more structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a tool that performs system checks (potentially complex), the description is incomplete. It doesn't cover output format, error handling, or detailed behavioral traits, leaving gaps for the agent to understand full usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 1 parameter and 0% schema description coverage, the description compensates by explaining the 'synthesize' parameter's purpose and default value. It adds meaning beyond the schema by specifying that it 'uses qwen2.5:14b to synthesize results into unified summary', which clarifies the parameter's effect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool performs a 'quick system health check using tool-enabled bugs' and deploys 'guardian bugs to check CPU, memory, disk, and services', which provides a clear verb ('check') and resource ('system health'). However, it doesn't distinguish this from sibling tools like 'colony_status' or 'farm_stats' that might also provide system-related information, making it somewhat vague in comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 doesn't mention any prerequisites, exclusions, or compare it to siblings such as 'colony_status' or 'farm_stats', leaving the agent with no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'parallel HTTP API requests' but doesn't explain concurrency limits, error handling, timeout behavior, authentication requirements, or response format. For a tool that executes multiple HTTP requests, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: one sentence states the purpose, followed by a clear parameter explanation and a practical example. Every sentence earns its place without redundancy, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of executing parallel HTTP requests, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks information on behavioral traits (e.g., error handling, rate limits), output format, and usage guidelines. This makes it inadequate for safe and effective tool invocation in a production context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the 'requests' parameter by providing an example JSON array structure with fields like url, method, headers, and body. However, with 0% schema description coverage and one parameter, the description compensates somewhat but doesn't fully detail syntax constraints (e.g., JSON validation, required fields beyond url). The baseline is 3 due to the example adding value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Execute parallel HTTP API requests.' It specifies the verb ('execute') and resource ('parallel HTTP API requests'), making the function unambiguous. However, it doesn't distinguish this tool from sibling swarm tools like 'code_gen_swarm' or 'deploy_swarm', which limits it to a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 scenarios where parallel HTTP requests are appropriate, prerequisites, or comparisons to other swarm tools or standard single-request methods. This lack of context leaves 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.
- 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 read operation ('Get'), but lacks details on permissions, rate limits, error handling, or what 'detailed status' entails (e.g., health metrics, member count). This is insufficient for a tool with potential complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 purpose, making it easy to parse quickly, which is ideal for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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 doesn't explain what 'detailed status' includes, potential side effects, or error cases, making it inadequate for a tool that likely returns complex data about colonies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 implies the 'colony_id' parameter is used to identify a specific colony, adding some meaning beyond the bare schema. However, it doesn't specify format, constraints, or examples, leaving gaps in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get detailed status of a specific colony' clearly states the action (Get) and resource (colony), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_colonies' or 'farm_stats' that might also provide colony-related information, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, context, or exclusions, such as how it differs from 'list_colonies' or 'farm_stats', 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'parallel task execution' which hints at concurrency behavior, but doesn't disclose critical operational details: whether this is a read or write operation, what happens to existing swarms, authentication requirements, rate limits, error conditions, or what 'deploy' actually entails. The example shows input format but not behavioral outcomes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with three sentences: purpose statement, parameter explanation, and example. Each sentence adds value - the example is particularly helpful for understanding the tasks parameter format. The structure is front-loaded with the core purpose. Minor improvement could be adding colony_id context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It partially documents one parameter but leaves colony_id completely unexplained. As a deployment tool likely involving system changes, it should address behavioral implications, prerequisites, and expected outcomes more thoroughly given the lack of structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description compensates partially by explaining the 'tasks' parameter with an example JSON structure showing {prompt, context?} objects. However, it provides no information about the 'colony_id' parameter - what it represents, format requirements, or where to obtain it. With 2 parameters and only 1 partially documented, this meets the baseline for partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Deploy swarm for parallel task execution.' It specifies the verb ('deploy') and resource ('swarm'), and the example provides concrete context about task structure. However, it doesn't explicitly differentiate from sibling tools like 'api_swarm' or 'quick_swarm', which appear to be related swarm operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 sibling tools containing 'swarm' in their names (api_swarm, code_gen_swarm, quick_swarm, etc.), there's no indication of when this specific deployment tool is appropriate versus other swarm-related tools. The example shows task structure but doesn't establish 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 the full burden of behavioral disclosure. It only states the action ('Get comprehensive farm statistics') without detailing what 'comprehensive' entails, whether it's a read-only operation, potential side effects, rate limits, or authentication needs. This is a significant gap for a 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.
Conciseness5/5Is 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. Every word earns its place by conveying the essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a vague description, the description is incomplete. It doesn't explain what 'farm' means in this context, what statistics are returned, or how this tool fits with siblings. For a tool with zero structured data, more detail is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 there are no parameters to document. The description doesn't need to add parameter information, and it appropriately doesn't mention any. Baseline is 4 for 0 parameters, as it avoids unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get comprehensive farm statistics' states a clear verb ('Get') and resource ('farm statistics'), but it's vague about what 'farm' refers to in this context and doesn't differentiate from sibling tools like 'colony_status' or 'system_health_swarm' that might also provide statistical information. 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 Guidelines2/5Does 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 'colony_status' and 'system_health_swarm' that might offer related statistics, the description doesn't indicate whether this tool is for general farm overview, specific metrics, or how it differs from other tools, leaving usage 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While it lists possible actions and shows an example, it doesn't describe error handling, concurrency limits, file permission requirements, whether operations are atomic, or what happens with partial failures. For a tool performing potentially destructive file operations, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured: a clear purpose statement, parameter explanation with action enumeration, and a concrete example. Every sentence earns its place with no wasted words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool performing potentially destructive file operations with no annotations and no output schema, the description is incomplete. It doesn't explain return values, error formats, performance characteristics, or safety considerations. The context signals show this is a single-parameter tool with complex nested data expectations that aren't fully documented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for the single 'operations' parameter, the description provides essential semantic information by explaining it's a JSON array of objects with specific fields and actions. The example clarifies the expected structure. However, it doesn't fully compensate for the schema gap by explaining all field requirements, validation rules, or error conditions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Execute parallel file operations' with specific actions listed (read, write, append, exists, delete). It distinguishes itself from siblings by focusing on file operations rather than API calls, code generation, or colony management. However, it doesn't explicitly contrast with similar file-related tools like 'chunked_write' or 'heavy_write'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'chunked_write', 'heavy_write', and 'exec_swarm' that might handle file operations differently, there's no indication of when file_swarm is preferred, what its performance characteristics are, or any prerequisites for use.
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 'status check' and returns data, implying a read-only operation, but lacks details on permissions, rate limits, error handling, or what 'verdict' and 'stats' entail. For a tool with zero annotation coverage, this is insufficient to guide 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with two short sentences that efficiently convey the core purpose and return values. Every sentence adds value: the first defines the action and scope, the second lists outputs. There's no wasted text, though it could be slightly more structured (e.g., bullet points for returns).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (implied by health monitoring), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the meaning of return values like 'verdict' or 'stats', behavioral aspects, or error conditions. For a tool with no structured data to supplement it, this leaves significant gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for zero parameters, as no compensation is needed, and the description doesn't detract from the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a 'quick status check' for 'colony health', specifying it returns specific data points (verdict, issues, active colonies, stats). It distinguishes from siblings like 'colony_status' by emphasizing 'ONE CALL' and 'quick', though it doesn't explicitly contrast functionality. The verb 'check' and resource 'colony health' are specific, avoiding tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance, implying it's for a fast, single-call health check, but offers no explicit when-to-use rules, prerequisites, or alternatives. It doesn't specify when to choose this over similar tools like 'colony_status' or 'system_health_swarm', leaving the agent to infer based on 'quick' and 'ONE CALL' without clear exclusions or 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 the full burden of behavioral disclosure. It describes the parallel generation process ('bugs write functions in parallel') and output handling ('Python assembles the file'), but lacks critical details: it doesn't specify error handling, performance characteristics (e.g., speed, reliability), side effects (e.g., file overwriting), or authentication needs. For a tool that generates and saves code files, this omission is substantial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by parameter explanations and an example. Each sentence adds value: the first explains the method, the second lists parameters, and the third provides an illustrative example. It's appropriately sized without redundancy, though the example could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (code generation with parallel processing), lack of annotations, and no output schema, the description is moderately complete. It covers the purpose and parameters adequately but misses behavioral details like error handling, side effects, and output format. For a tool that creates files, more context on safety (e.g., overwrite warnings) and result structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 explains all four parameters: 'output_path' (where to save), 'spec' (what the code should do), 'language' (with examples), and 'num_functions' (default and max). This adds clear meaning beyond the bare schema. However, it doesn't detail parameter constraints (e.g., valid 'language' values beyond examples) or interactions, preventing a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate code files by having bugs write functions in parallel. Each bug writes one function, Python assembles the file.' It specifies the verb ('generate'), resource ('code files'), and method ('bugs write functions in parallel'), distinguishing it from generic code generation tools. However, it doesn't explicitly differentiate from sibling tools like 'code_gen_swarm' or 'synthesize', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 includes an example but doesn't specify contexts, prerequisites, or exclusions. With sibling tools like 'code_gen_swarm' and 'synthesize' present, the lack of comparative guidance is a significant gap, 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 full burden for behavioral disclosure. It mentions 'Workers can run shell commands (find, du, grep, etc.) for real analysis' which implies execution capabilities, but doesn't disclose critical behavioral traits like whether this is a read-only operation, potential system impact, permission requirements, or rate limits. The description is insufficient for a mutation-capable 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with four sentences that each add value. It's front-loaded with the core purpose, followed by worker capabilities, parameter explanations, and usage context. There's minimal redundancy, though the parameter explanations could be more integrated with the main description flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how workers coordinate, error handling, or the scope of 'deep analysis'. The mention of synthesis with qwen2.5:14b is helpful but insufficient for overall completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by explaining 'target_path: Directory/path to analyze', 'analysis_type: 'full', 'redundant', 'sizes', 'cleanup'', and 'synthesize: If True (default), uses qwen2.5:14b to synthesize findings'. However, it doesn't fully document all three parameters' semantics, particularly the specific meanings of analysis_type values beyond listing them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'deep analysis swarm using WORKERS with exec_cmd for thorough system analysis' and lists specific use cases like finding redundant files, cache sizes, disk usage, and log files. This provides a specific verb ('deep analysis swarm') and resource ('system'), though it doesn't explicitly distinguish from sibling tools like 'system_health_swarm' or 'recon_swarm'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context with 'Use this for finding: redundant files, cache sizes, disk usage, log files, etc.' but doesn't explicitly state when to use this tool versus alternatives like 'system_health_swarm' or 'chunked_analysis'. It gives general application areas but lacks specific guidance on 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 the full burden of behavioral disclosure. It indicates a destructive action ('dissolve') and mentions 'free resources', but lacks details on permissions required, whether the operation is reversible, potential side effects, or response format. For a mutation tool with zero annotation coverage, this is insufficient to inform safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that front-loads the core action ('dissolve a colony') and adds a brief outcome ('free resources'). Every word earns its place, making it efficient and easy to parse without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive operation with no annotations and no output schema, the description is incomplete. It fails to explain what 'free resources' means, the return value, error conditions, or dependencies. This leaves significant gaps for an agent to understand the full context and implications of using the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention parameters, but with only one parameter ('colony_id') and 0% schema description coverage, the baseline is high. Since there are zero parameters described in the schema, the description's lack of parameter info is acceptable, as it doesn't need to compensate for gaps. The single parameter is self-evident from the context of dissolving a colony.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('dissolve') and the resource ('a colony'), making the purpose understandable. It distinguishes from siblings like 'list_colonies' or 'colony_status' by being a destructive operation. However, it doesn't specify what 'free resources' entails, leaving some ambiguity about the exact outcome.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. The description implies it's for terminating colonies, but it doesn't mention prerequisites (e.g., whether the colony must be idle), exclusions, or comparisons to siblings like 'cleanup_idle' or 'spawn_colony'. This leaves the agent with minimal context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'List all active colonies' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the 'bugs' information takes. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states exactly what the tool does without any wasted words. It's appropriately sized for a simple listing tool and front-loads the core functionality clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a read operation with no annotations and no output schema, the description should provide more context about what 'active colonies' means, what 'bugs' information is included, and the format of the response. The current description is too minimal for a tool that presumably returns structured data about colonies and their associated bugs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing parameters that don't exist, earning a baseline score of 4 for not adding unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('all active colonies with their bugs'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this tool from sibling tools like 'colony_status' or 'farm_stats', which might provide related information about colonies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'colony_status', 'farm_stats', and 'spawn_colony' that might relate to colony management, there's no indication of when this listing tool is appropriate or what distinguishes it from other colony-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 full burden for behavioral disclosure. It mentions 'read-only tools' which is helpful, and describes the 'synthesize' parameter's effect on report generation. However, it doesn't cover important behavioral aspects like: what the output looks like, whether it's synchronous/asynchronous, error handling, performance characteristics, or resource usage implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with four sentences that each add value. It's front-loaded with the core purpose, then explains parameters. No wasted words, though the structure could be slightly improved by grouping parameter explanations more clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 3 parameters, the description provides adequate but incomplete coverage. It explains the tool's purpose and parameters reasonably well, but lacks crucial information about what the tool returns, error conditions, and how it differs from similar swarm tools. For a reconnaissance tool with behavioral complexity, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant value by explaining all three parameters: 'target_path' as 'Directory to explore', 'deep' as 'Enable deep work mode... multi-iteration for complex analysis', and 'synthesize' as using 'qwen2.5:14b to synthesize findings into unified report'. This provides meaningful context beyond the bare schema, though it doesn't specify format requirements for target_path.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'scouts explore a directory/codebase' and 'map out a target', specifying the verb (explore/map) and resource (directory/codebase/target). It distinguishes from siblings by mentioning 'read-only tools' and 'reconnaissance swarm', but doesn't explicitly differentiate from similar tools like 'file_swarm' or 'deep_analysis_swarm'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (including other swarm tools like 'file_swarm', 'deep_analysis_swarm', 'code_review_swarm'), there's no indication of what makes this tool appropriate for reconnaissance versus other analysis approaches.
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. It mentions that analysis is done 'in parallel' and 'results are synthesized', which adds some behavioral context. However, it lacks details on permissions, rate limits, error handling, or what the synthesis entails, leaving significant gaps for a tool that performs analysis.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by brief elaboration and a clear example. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 3 parameters with 0% schema coverage, the description is moderately complete. It covers the tool's purpose and parameters adequately but lacks details on behavioral traits, output format, and usage context. It's minimal viable but has clear gaps in transparency and guidelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 explains each parameter: 'target' as 'What to analyze (file path, concept, code, etc.)', 'question' as 'The analysis question', and 'num_perspectives' as 'How many different angles (default 4)'. This adds meaningful semantics beyond the bare schema, though it could be more detailed (e.g., constraints on 'num_perspectives').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze something from multiple perspectives in parallel' with 'results are synthesized'. It specifies the action (analyze) and resource (something), but doesn't explicitly differentiate from sibling tools like 'deep_analysis_swarm' or 'recon_swarm' that might also perform analysis, 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 Guidelines2/5Does 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 mentions 'multiple perspectives in parallel' but doesn't specify contexts, exclusions, or compare to sibling tools like 'deep_analysis_swarm' or 'api_swarm'. The example shows usage but doesn't explain when this approach is preferred.
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 the tool runs 'parallel code review' and returns 'security, performance, style, and refactoring analysis,' but lacks details on execution time, error handling, permissions, or side effects. For a tool with no annotations, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: three sentences that efficiently cover purpose, input methods, and output. Each sentence adds clear value without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a code review tool with no annotations, no output schema, and 2 parameters at 0% schema coverage, the description is incomplete. It lacks details on behavioral traits, error cases, output format beyond high-level categories, and differentiation from siblings. This makes it inadequate for confident tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds some meaning beyond the input schema by explaining that 'code' and 'filepath' are alternative input methods ('Pass code directly OR filepath to read from disk'). However, with 0% schema description coverage and 2 parameters, it doesn't fully compensate—missing details like format constraints or examples. The baseline is 3 due to the schema's lack of descriptions, but the added value is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run parallel code review with 4 specialized perspectives.' It specifies the verb ('run'), resource ('code review'), and scope ('parallel' with '4 specialized perspectives'). However, it doesn't explicitly differentiate from sibling tools like 'deep_analysis_swarm' or 'quick_swarm' that might also analyze code, leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context by stating 'Pass code directly OR filepath to read from disk,' which implies two alternative input methods. However, it doesn't specify when to use this tool versus alternatives like 'deep_analysis_swarm' or 'chunked_analysis,' nor does it mention prerequisites or exclusions, leaving the guidance incomplete.
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 implies a mutation action ('spawn') but doesn't state what resources are consumed, whether permissions are required, or what happens on success/failure. The colony type details add some context but don't cover broader behavioral traits like side effects or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: a brief purpose statement followed by a bulleted list of colony types with clear, terse explanations. Every sentence earns its place by adding essential information without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (creating a colony with type variations), no annotations, no output schema, and low schema coverage, the description is partially complete. It covers the parameter semantics well but lacks behavioral context, usage guidelines, and output details, leaving gaps for an agent to infer missing information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 1 parameter with 0% description coverage, so the description must compensate. It adds significant meaning by explaining the 'colony_type' parameter with four options and their compositions (e.g., 'standard: scout, worker, worker, memory'), which goes beyond the schema's basic type information. However, it doesn't specify if these are the only valid values or provide format details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('spawn a new bug colony') and resource ('bug colony'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'list_colonies' or 'dissolve_colony' by focusing on creation. However, it doesn't explicitly differentiate from 'quick_colony' or other swarm-related tools that might also create colonies, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'quick_colony' or 'api_swarm', nor does it mention prerequisites or exclusions. It lists colony types but doesn't explain when to choose one over another in practical terms, leaving usage decisions unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Remove') but does not clarify if this is destructive, irreversible, requires permissions, or has side effects. The description is minimal and misses key behavioral traits 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded and directly states the tool's function, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation) and lack of annotations or output schema, the description is incomplete. It fails to address critical context like what 'Remove' entails, confirmation prompts, error handling, or return values, 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.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate here, but it could have mentioned implicit assumptions (e.g., no filters). Baseline is 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and target resource ('all colonies with 0 tasks completed'), making the purpose specific and unambiguous. It distinguishes itself from siblings like 'list_colonies' or 'dissolve_colony' by focusing on a specific cleanup criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'dissolve_colony' or 'list_colonies'. It lacks context about prerequisites, risks, or typical scenarios for cleanup, offering only a basic functional statement without 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 of behavioral disclosure. It mentions the model used ('qwen2.5:14b for accuracy') which adds useful context about implementation, but doesn't describe important behavioral traits like whether this is a read-only operation, potential rate limits, expected response format, or error conditions. The example helps but doesn't fully compensate for missing behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with purpose statement, implementation detail, parameter explanations, and a concrete example - all in four concise sentences. Every sentence adds value, and the front-loaded purpose statement immediately communicates the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and no annotations or output schema, the description does a reasonable job explaining parameters and providing an example. However, for a synthesis tool that presumably returns text summaries, the lack of output description and behavioral context (rate limits, error handling) leaves gaps. The description is adequate but not fully complete for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 clearly explains both parameters: 'results' as 'JSON array of result objects (with 'answer' or 'response' keys)' and 'context' as 'Optional context about what these results are from'. The example further illustrates parameter usage with concrete values. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'synthesize any JSON results into unified summary' with specific verb ('synthesize') and resource ('JSON results'). It distinguishes from siblings by being 'standalone' and focused on synthesis rather than analysis, generation, or swarm operations. However, it doesn't explicitly contrast with the most similar sibling 'chunked_analysis'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the example showing health check results synthesis, suggesting this tool is for aggregating multiple responses. However, it lacks explicit guidance on when to use this versus alternatives like 'chunked_analysis' or 'deep_analysis_swarm', and doesn't specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 does well by explaining key behaviors: role-based tool permissions for different bug roles, the 'DIRECT EXECUTE' mechanism for long content, and how 'deep' and 'synthesize' parameters affect agent behavior. However, it doesn't cover error handling, performance characteristics, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably structured with clear sections, but contains some redundancy and could be more front-loaded. The bug role permissions list is detailed but necessary, while the 'DIRECT EXECUTE' explanation repeats the content length threshold. Some sentences could be more efficiently phrased to improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multi-agent deployment with role-based permissions) and the complete lack of annotations and output schema, the description provides substantial context but has gaps. It covers core functionality and parameter behaviors well, but doesn't explain the return format, error conditions, or how results from different agents are organized. The 'colony_type' parameter remains unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the lack of parameter documentation. It provides substantial semantic information: it explains 'tasks' with examples and the special 'DIRECT EXECUTE' behavior, clarifies 'deep' enables chaining for complex tasks, and states 'synthesize' uses a specific model for summaries. The only parameter not well-explained is 'colony_type'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Deploy tool-enabled agents that can use real system tools.' It specifies the verb ('deploy') and resource ('tool-enabled agents'), and distinguishes it from siblings by focusing on multi-agent deployment with role-based permissions. However, it doesn't explicitly differentiate from similar swarm tools like 'api_swarm' or 'exec_swarm'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context through examples and explanations of parameters like 'deep' and 'synthesize', but lacks explicit guidance on when to use this tool versus alternatives. It mentions 'DIRECT EXECUTE' for specific cases but doesn't compare to sibling tools or outline scenarios where other swarm tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the parallel chunking process, the involvement of 'bugs' (likely agents), that Python concatenates without LLM involvement, and that it saves to a file. It doesn't cover error handling, performance, or side effects, but provides substantial operational context beyond basic parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections ('HOW IT WORKS', 'EXAMPLE'), front-loaded purpose, and efficient sentences. The example is helpful but slightly verbose; overall, it's appropriately sized with minimal waste, though could be slightly tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description does a decent job explaining inputs and process. However, it lacks details on output format, error cases, or integration with sibling tools, leaving gaps in full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 explains all four parameters: 'output_path' as where to save, 'spec' as the document topic, 'num_sections' with default and max values, and 'doc_type' with enum options. The example further clarifies usage. This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate large documents by having bugs write sections in parallel.' It specifies the verb ('generate') and resource ('large documents'), and mentions the parallel chunking mechanism. However, it doesn't explicitly differentiate from sibling tools like 'heavy_write' or 'chunked_code_gen' beyond mentioning that it bypasses long-content limitations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: it's for generating large documents when facing content length limitations, and mentions that 'heavy_write saves result,' suggesting a workflow. However, it lacks explicit guidance on when to use this tool versus alternatives like 'heavy_write' or 'chunked_code_gen,' and doesn't specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 effectively describes key traits: parallel execution, safety checks, and a list of blocked commands. This gives the agent insight into what the tool does and its constraints, though it could add more on error handling, output format, or performance limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: a clear purpose statement, parameter explanation with example, and a blocked list, all in three lines. Every sentence adds value without redundancy, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (parallel shell execution with safety), no annotations, and no output schema, the description is moderately complete. It covers purpose, parameter semantics, and behavioral traits like blocked commands, but lacks details on return values, error cases, or how parallel execution is managed, which could hinder agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 description must compensate. It adds meaningful context: 'commands' is a JSON array of command strings, with an example and blocked commands. This clarifies the parameter's format and constraints beyond the schema's basic type, though it doesn't detail array size limits or command length.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Execute shell commands in parallel (with safety checks).' It specifies the verb ('execute'), resource ('shell commands'), and key characteristics ('parallel', 'safety checks'). However, it doesn't explicitly differentiate from sibling tools like 'api_swarm' or 'code_gen_swarm', which might also involve execution in different contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage context through the 'BLOCKED' list, suggesting when not to use it (for dangerous commands). However, it lacks explicit guidance on when to choose this tool over alternatives like 'quick_swarm' or 'deploy_swarm', and doesn't mention prerequisites or ideal scenarios for parallel execution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and effectively discloses key behavioral traits: it's a write operation ('writes directly to disk'), handles large content, bypasses the LLM, and returns status/bytes. It doesn't cover permissions or error details, but gives substantial context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and guidelines, uses bullet-like clarity for parameters and returns, and every sentence adds value without waste. It's appropriately sized for a 2-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no annotations, and no output schema, the description is largely complete: it explains purpose, usage, behavior, parameters, and returns. It could detail error cases or path requirements, but covers core aspects well for a write tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 adds meaning for both parameters: 'path: File path to write to' and 'content: Content to write (any length)', clarifying usage beyond schema types. It doesn't specify path format or content constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Direct file write'), resource ('file'), and scope ('NO LLM involved', 'Use for large content'). It distinguishes from siblings like 'chunked_write' by emphasizing direct disk writing and handling large content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance on when to use ('Use for large content', 'Bugs can't reliably echo content >300 chars through the LLM') and when not to use ('NO LLM involved'), with clear context for bypassing model limitations.
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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