lerobot-mcp

by noah-wardlow

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a distinct purpose, with clear differentiation between preview (build_*) and execution (run_*) commands, as well as separate utilities for Hugging Face, job management, and configuration. Overlapping verbs like 'build' and 'run' are disambiguated by their noun suffixes.
Naming Consistency4/5
All tools share the 'lerobot_' prefix, and most follow a 'verb_noun' pattern (e.g., build_command, run_example). Minor deviations exist (lerobot_capabilities, lerobot_public_symbols) but the overall pattern is consistent and predictable.
Tool Count4/5
25 tools cover a wide range of LeRobot functionalities—installation, execution, dataset conversion, Hugging Face interaction, job management—without feeling excessive. The count is appropriate for the server's scope, though slightly higher than ideal.
Completeness4/5
The tool surface addresses core LeRobot workflows: running commands and examples, converting datasets, inspecting metadata, and managing background jobs. Missing upload or training tools are likely outside the intended scope, so the set feels reasonably complete.
Average 3/5 across 25 of 25 tools scored. Lowest: 1.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 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 passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 must fully disclose behavior. It does not state whether the tool is read-only, what side effects occur, or any authentication requirements. The description is entirely uninformative regarding behavior.
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?
The description is extremely concise (one sentence) but at the cost of informativeness. It does not earn its place because it barely conveys any useful 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 6 parameters, one required, and a lack of annotations or output schema context, the description is grossly incomplete. It fails to cover the tool's functionality, inputs, or expected outcomes.
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 explanation for the six parameters (path, format, output, quick, deep, samples). The agent has no guidance on how to use these parameters effectively.
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 is vague: 'Preview pinned Forge dataset inspection.' It hints at inspecting a pinned dataset but does not clarify what 'pinned' means or how it differs from sibling tools like 'lerobot_forge_inspect' or 'lerobot_inspect_dataset_metadata'. A specific verb and resource are missing.
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 usage guidelines are provided. There is no indication of when to use this tool versus alternatives, no prerequisites, and no context about typical 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 carries the full burden of behavioral disclosure. It only states the basic action without mentioning blocking behavior, output, side effects, permissions, or asynchronous execution.
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?
The description is a single sentence, which is concise, but it is under-specified. It does not earn its place as it provides minimal useful 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 7 parameters and no schema descriptions or annotations, the description is severely incomplete. It lacks critical context about parameter usage, behavior, and output.
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 7 parameters with 0% description coverage, yet the tool description contains no parameter explanations. The agent gets no guidance on what each parameter means or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action ('Run') and the resource ('a Python script from LeRobot's examples directory'). It distinguishes from siblings like lerobot_run_command (which runs arbitrary commands) and lerobot_list_examples (which lists examples).
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. No mention of scenarios, 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 provided; description says 'preview' but doesn't clarify if actual conversion occurs or if it's a dry run. No mention of destructive potential, auth needs, or side effects.
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?
Single sentence is concise but lacks detail. Could be improved by adding key parameter context; not overly verbose.
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?
With 12 parameters and no annotations, the description fails to provide enough context. No information on return values, required parameters beyond names, or how to use optional parameters.
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 to the 12 parameters. Terms like 'source', 'output', 'target_format' are not explained; user must infer from names.
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?
Description clearly states the tool converts Forge datasets to/from LeRobot formats. 'Preview' and 'pinned' add specificity but could be clearer; overall it distinguishes from sibling 'lerobot_forge_convert' which likely does the actual conversion.
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 vs alternatives like 'lerobot_forge_convert' or 'lerobot_convert_dataset_to_latest_format'. Does not specify prerequisites or when to use dry_run.
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 provided, so the description carries full burden. It mentions using 'Forge main at the pinned bug-fix commit,' which gives some deterministic behavior, but fails to disclose side effects (destructive or not), required permissions, error handling, or output behavior. Insufficient for a conversion tool.
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 very concise (two sentences), but it omits critical information that would fit within a few more sentences. It is not overly verbose, but the 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.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 15 parameters and an output schema, the description provides no context on return values, parameter usage, or workflow integration. It does not explain the conversion process, input formats, or output structure. Incomplete for practical 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% (no parameter descriptions in schema or description). The description adds no meaning to any of the 15 parameters. Baseline is 3 for high coverage, but here coverage is low and description fails to compensate, leaving parameters entirely 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 that the tool runs a pinned Forge dataset conversion using a specific bug-fix commit. It distinguishes from siblings like 'lerobot_convert_dataset_to_latest_format' and 'lerobot_build_forge_convert' by emphasizing the pinned version, but the phrase 'pinned' is not elaborated.
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 explicit guidance on when to use this tool vs alternatives. The description does not mention prerequisites, context, or when not to use it. Sibling tools like 'lerobot_convert_dataset_to_latest_format' or 'lerobot_build_forge_convert' are not referenced or contrasted.
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 bears full responsibility for behavioral disclosure. It only says 'inspect', implying a read operation, but does not confirm side-effects, whether the tool modifies the dataset, or what output to expect. This is insufficient for safe agentic decision-making.
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 a single sentence, making it concise. However, it is too brief given the tool's complexity, and the space is not effectively used to convey essential information. It earns its place minimally by stating purpose, but lacks structure 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?
The tool has 9 parameters, no annotations, and an output schema (whose details are not in description). The description fails to explain what the tool outputs, how parameters affect behavior, or any usage context beyond a vague 'before conversion'. This is severely incomplete for a tool of this complexity.
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 any of the 9 parameters. The agent must infer meaning solely from parameter names (e.g., 'quick', 'deep'), which is inadequate. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'inspects a dataset' with a specific method ('pinned Forge'), and situates its usage 'before conversion'. This differentiates it from sibling tools like lerobot_forge_convert (conversion) and lerobot_inspect_dataset_metadata (generic metadata inspection). However, it does not elaborate on what 'inspect' entails.
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 phrase 'useful before conversion' hints at a specific use case but provides no explicit guidance on when to use this tool versus alternatives (e.g., lerobot_forge_convert, lerobot_inspect_dataset_metadata). There are no exclusions or prerequisites 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 full burden for behavioral disclosure. It only says 'summarize', implying a read-only operation, but does not state side effects, authentication requirements, rate limits, or any other behavioral traits. The description is insufficient for safe tool invocation.
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 a single concise sentence with no unnecessary words. However, it is too brief to cover the tool's complexity, resulting in under-specification rather than purposeful 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 6 unannotated parameters and no parameter descriptions, the description is severely incomplete. It does not explain the purpose of each parameter, provide examples, or clarify the return format (though an output schema exists). The tool's behavior beyond 'summarize' is not addressed.
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%, yet the description provides no explanation of the 6 parameters. The tool can read from local path or HF repo, but it's unclear which parameter corresponds to which source (e.g., repo_id vs root). Users must rely on parameter names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool summarizes LeRobot dataset metadata from a local path or Hugging Face dataset repo. It uses a specific verb 'summarize' and identifies the resource, distinguishing it from sibling tools like lerobot_forge_inspect or lerobot_hf_repo_info. However, it doesn't specify what the summary includes, leaving some 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?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use it, or comparison to siblings. Users must infer usage from the tool name and 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 exist, and the description does not disclose behavioral traits such as whether termination is destructive, idempotent, or what happens if the job is already completed.
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 very concise (4 words), but it lacks important context that would justify the brevity. It is not front-loaded with critical 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 the low complexity (1 parameter, no annotations, output schema exists but not described), the description is incomplete. It fails to specify success/failure behavior, return values, or edge cases.
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 detail beyond the schema for the single required parameter 'job_id'. The agent receives no guidance on how to obtain the job_id.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Terminate a background job' uses a specific verb and resource, clearly distinguishing it from sibling tools like lerobot_list_jobs or lerobot_job_status.
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, nor are there any exclusion criteria or prerequisites 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 provided. Description does not disclose what 'basic information' entails, whether authentication is required, or any side effects. The output schema exists but the description adds no 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but may be overly terse given the lack of schema descriptions. Sentence structure is acceptable but could benefit from more detail without becoming verbose.
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?
Description is minimal despite having 3 parameters (1 required) and an output schema. It does not specify what information is returned, 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.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning to parameters like repo_id, repo_type, or revision. Agent gets no guidance on valid values or usage beyond the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'return' and resource 'Hugging Face Hub repository information'. It is distinct from sibling tools that perform actions like building, converting, or searching.
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 vs alternatives such as lerobot_hf_search_datasets or lerobot_inspect_dataset_metadata. Agent is left without context for selecting this tool.
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?
The description does not disclose behavioral traits beyond the basic action. 'Tails' implies limited output, but there is no mention of permissions, prerequisites (e.g., job completion), error handling, or output format. Annotations are absent, so the description carries the full burden but fails to provide sufficient 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, front-loaded sentence that precisely conveys the tool's purpose without any extraneous words. Every word is necessary and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's simplicity (1 parameter, output schema exists), the description is incomplete for an agent. It lacks context on how logs are retrieved (e.g., job completion needed), output format (though schema may help), and integration with sibling tools. The agent would need additional knowledge to use it 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 parameter 'job_id' is a required string with 0% schema description coverage. The description adds no meaning beyond the schema, such as format, examples, or constraints, leaving the agent without guidance for correct invocation.
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 it returns stdout and stderr tails for a background job, using a specific verb and resource. It is distinct from sibling tools like 'lerobot_job_status' (status) and 'lerobot_list_jobs' (listing), though it doesn't explicitly differentiate.
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 'lerobot_job_status' or 'lerobot_list_jobs'. The description only states what it does, with no 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 provided, so description must disclose behavior. It mentions foreground vs background but does not explain job management, cancellation, status checks, or return behavior. The output schema exists but its content is not described.
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?
Single sentence is concise but at the expense of necessary detail. It is not well-structured to convey critical information about parameters or usage.
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?
With 8 parameters and an output schema, the description is far too sparse. It fails to explain command format, option dictionary, or background job lifecycle, making it incomplete for effective tool selection.
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%, yet the description does not explain any parameter beyond the concept of 'command'. Parameters like options, cwd, timeout, background, env are left completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it runs a 'known LeRobot entry point' and distinguishes between foreground call and managed background job. It is specific enough to differentiate from siblings like lerobot_run_example or build 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 on when to use this tool versus alternatives like lerobot_run_example, or when to choose foreground vs background. The description lacks explicit usage conditions.
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. It only says 'list' but does not disclose side effects, data source, error conditions, or whether it requires a specific configuration. The behavior is opaque.
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, concise sentence with no unnecessary words. However, it sacrifices completeness for brevity, missing important details.
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?
Although an output schema exists, the description lacks completeness: it does not explain the parameter, provide usage context, or reveal behavioral details. The agent cannot fully understand how to use 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?
The schema has one parameter 'category' with 0% description coverage, and the description does not mention or explain this parameter at all. The agent has no guidance on what values to provide or how it affects the result.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list), the resource (Python example scripts), and the scope (under configured LeRobot checkout), distinguishing it from sibling tools like lerobot_run_example or lerobot_build_example.
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 usage guidelines are provided. The description does not indicate when to use this tool instead of alternatives, nor does it give any context on prerequisites or appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It states 'preview', implying no side effects, but doesn't explicitly confirm read-only or state that no conversion occurs. It does not describe output format or any behavioral traits like rate limits or authentication needs. The clarity that it's a preview is decent, but lacks depth for full transparency.
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 (one sentence). It front-loads the purpose effectively, but is so brief that it sacrifices clarity. While no words are wasted, it could include essential usage context without becoming verbose. It earns its place for purpose but falls short on 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 tool's complexity (8 parameters, output schema present), the description is insufficient. It does not mention what the preview output looks like, how the parameters affect it, or any prerequisites. The sibling tools add context, but the description itself fails to provide a complete picture.
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 coverage is 0%, and the description adds no parameter information. The 8 parameters (including 'repo_id', 'root', etc.) are completely unexplained. The agent cannot infer what each parameter does beyond its name. The description fails to add any meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to preview a conversion command for LeRobot datasets from v2.1 to v3.0. The verb 'preview' and the specific resource 'conversion command' make the action unambiguous. It distinguishes from the sibling tool 'lerobot_convert_dataset_to_latest_format', which likely executes the conversion.
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 that this is meant for previewing before actual conversion, nor does it reference sibling tools like 'lerobot_convert_dataset_to_latest_format' for execution. An agent would lack context on when previewing is appropriate.
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 provided. The description discloses the main actions but omits important behavioral details like whether local changes are overwritten, required permissions, or what 'refresh config' entails.
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?
Single sentence with no waste. However, it sacrifices completeness for 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?
Despite having an output schema, the description is too terse for a tool that modifies server state. It lacks information about side effects, error cases, and expected outcomes.
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 coverage is 0%, and the description adds no meaning to any of the three parameters (root, ref, timeout_seconds). The parameters remain entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool clones or updates a LeRobot checkout and refreshes the server config. It distinguishes from sibling tools like lerobot_build_command or lerobot_run_example, which focus on building or running.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs. alternatives or prerequisites. The description implies it's for updating LeRobot code, but doesn't mention when not to use or what conditions must be met.
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 must cover behavioral traits. It only says 'Preview... without running it', which indicates non-destructiveness but does not explain what 'preview' entails (e.g., output format, side effects). Minimal disclosure.
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 a single sentence, which is concise, but it sacrifices necessary detail. It is appropriately front-loaded, but lacks substance.
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 has no annotations, 4 parameters with 0% schema coverage, and many sibling tools, the description fails to explain the tool's behavior, parameters, or return value. It is too minimal for an agent to use 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%, yet the description provides no information about any of the 4 parameters (example_path, options, extra_args, use_uv). The agent receives no guidance on what these parameters mean or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Preview' and the resource 'LeRobot example script command'. It distinguishes from sibling 'lerobot_run_example' by explicitly saying 'without running it'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (preview) and when not (running) by saying 'without running it'. It does not explicitly mention alternatives like 'lerobot_run_example' or 'lerobot_build_command' but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description only indicates it runs help, implying a read-only operation. Adds minimal behavioral context beyond the obvious.
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?
Single sentence, front-loaded, no wasted words. Ideal conciseness for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with output schema, description is adequate but lacks details on parameters and output context. Could mention that help text is returned.
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 has 3 parameters with 0% description coverage. The description does not explain timeout_seconds or use_uv, providing no added meaning beyond type/default values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool runs `--help` for any LeRobot console command, distinguishing it from sibling tools like lerobot_run_command and lerobot_list_commands.
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 explicit guidance on when to use this tool versus alternatives. Does not mention conditions 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 bears full responsibility for behavioral disclosure. It fails to mention key traits such as the tool querying Hugging Face, the nature of results, rate limits, authentication requirements, or the impact of boolean flags like 'prefer_lerobot' or 'include_forge_registry'. The description is too minimal to provide adequate transparency.
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 sentence with no redundant words. It is concise and front-loaded, but the brevity comes at the cost of completeness. Still, it earns a high score for efficiency.
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 has 16 parameters with 0% schema coverage, no output schema, and no annotations, the description is too short. It does not explain how filters combine, default values, result format, or how to use the output. The tool is complex but the description provides minimal 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%, so the description must compensate. It only mentions a subset of parameters (robot, format, task, scale/size, compatibility hints). Many parameters (e.g., query, language_conditioned, simulation, demo_suitable, sort, limit, boolean flags) are omitted. While it adds some meaning for the mentioned parameters, it is insufficient for the 16-parameter schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Search' and identifies the resource as 'robotics datasets'. It lists multiple filter criteria (robot, format, scale, size, task, compatibility hints), clearly distinguishing this tool from sibling tools like lerobot_hf_repo_info or lerobot_inspect_dataset_metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching datasets by various criteria but does not explicitly state when to use this tool versus alternatives (e.g., lerobot_hf_repo_info for repo info, lerobot_inspect_dataset_metadata for metadata inspection). No exclusions or when-not-to-use guidance provided.
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 must fully disclose behavior. It states it's a dry-run, but does not explain what the preview output contains (e.g., the command string, parsed arguments, etc.), leaving the agent uncertain about the return value. The output schema exists but is not detailed in the description.
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 sentence, concise and to the point. It is appropriately front-loaded with purpose. However, it might be too brief, sacrificing clarity on details.
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 presence of an output schema, the description does not need to detail return values, but it lacks context about what 'known LeRobot entry point command' means and how parameters like options or extra_args are used. Sibling tools are numerous, but no guidance on when to choose this over others is provided. Overall, the description is minimal and insufficient for a 5-parameter 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. It does not explain any of the 5 parameters (command, options, extra_args, cwd, use_uv). While parameter names give some hints, the description adds no value for understanding their meaning or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Preview' and clarifies 'without running it', clearly indicating a dry-run. This distinguishes it from sibling tools like lerobot_run_command, which actually executes the command.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (for previewing before execution), but does not explicitly mention when not to use it or specify alternatives beyond the implied contrast with run commands. Still, the context is clear enough for an AI agent.
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 present, so the description carries full burden for behavioral disclosure. It states what the tool does but does not mention read-only nature, lack of side effects, or any other behavioral traits. Minimal 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 succinct sentence (10 words) that is front-loaded with the verb 'List'. Every word contributes meaning, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no parameters and an output schema exists (not shown but indicated). The description sufficiently conveys the tool's purpose as listing command names and scripts, which is complete for this simple tool.
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?
There are no parameters, and the description does not need to add parameter details. Coverage is trivially 100%, so baseline 4 applies.
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 uses a specific verb 'List' and clearly identifies the resource as 'supported command names and discovered LeRobot console scripts'. It is unambiguous, but does not explicitly differentiate from sibling list tools like lerobot_list_jobs or lerobot_list_examples.
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 (e.g., lerobot_command_help for details, lerobot_list_jobs for jobs). The description does not mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full burden. It implies a read-only operation by saying 'list', but does not explicitly confirm no side effects, auth requirements, or performance characteristics. Adequate but minimal for a simple list 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?
Single sentence, no wasted words. Clearly states the action and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an output schema, the description covers the core purpose. It specifies the source (current checkout) and categories. A minor gap is the lack of mention of output format, but the output schema likely provides that.
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?
No parameters, so schema coverage is effectively 100%. The description correctly doesn't need to add parameter info. It could optionally describe the output structure, but the presence of an output schema reduces that need.
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 uses a specific verb 'List' and explicitly names the resources: scripts, extras, examples, and registered components. It distinguishes from siblings like lerobot_list_examples and lerobot_list_commands by covering a broader set, but does not explicitly compare or differentiate.
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 the many sibling list tools. The description only states what it lists, without specifying contexts or exclusions, leaving the agent to infer use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses default local behavior and the effect of `force_conversion`. However, it does not specify if the conversion modifies the original data, creates a new version, or any potential side effects like overwriting files. More detail on the conversion process would improve transparency.
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 concise with two short paragraphs. The first paragraph states the core purpose, and the second adds key details. It is front-loaded and avoids unnecessary fluff, though it could be more structured with clear sections.
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 11 parameters, zero schema descriptions, and no annotations, the description is incomplete. It explains the main conversion and a key parameter but leaves most parameters (root, branch, file sizes, push_to_hub, etc.) unexplained. The output schema exists but the description does not mention return values or side effects.
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 explains `repo_id` implicitly and `force_conversion` explicitly. However, 9 out of 11 parameters (e.g., root, branch, data_file_size_in_mb, push_to_hub, timeout_seconds, use_uv, env) are not described at all. The description adds minimal meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert a LeRobot v2.1 dataset to the current v3.0 parquet layout.' It specifies the source format (v2.1) and target format (v3.0), distinguishing it from sibling tools that handle other conversion types or builds.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use: defaults to local/no-push behavior, and explains the `force_conversion` parameter for overriding existing v3.0 tags. It also notes that older versions must first be migrated to v2.1. However, it doesn't explicitly compare with sibling tools like `lerobot_forge_convert` or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description relies on the phrase 'by static source inspection' to hint at non-dynamic behavior, but fails to disclose potential issues like invalid modules, performance, or internet requirements.
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 sentence with no extraneous words, communicating the core action efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description covers the basic purpose but lacks details on error handling or edge cases, limiting completeness.
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%, yet the description does not explain the module_prefix or limit parameters beyond implying module_prefix's role, leaving the agent uninformed about parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists public classes/functions below a LeRobot module prefix using static inspection, with a specific verb and resource that distinguishes it from sibling tools like build or convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for exploring the library's API modules but does not explicitly state when to use it versus alternatives or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must convey behavioral traits. It discloses the returned fields but does not indicate whether the tool has side effects, requires authentication, or can be called on jobs in any state. The behavioral transparency is adequate but minimal.
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 sentence with no extraneous information. It is concise and front-loaded with the key action and outputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (context indicates true), the description does not need to detail return values. It lists the three fields returned (state, return code, output tails), which is sufficient for a basic understanding. However, it could hint at output tails being limited lines, but overall it is complete enough.
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 on the single parameter job_id. The tool description does not add any additional meaning, e.g., explaining how to obtain job_id or its format. For a tool with one required parameter and no schema descriptions, the description should compensate but fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns state, return code, and output tails for a background job. It uses specific verbs ('Return') and specifies the resource ('background job'), distinguishing it from siblings like lerobot_job_logs and lerobot_list_jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for checking job status, but it does not explicitly mention when to use it versus alternatives like lerobot_job_logs for detailed logs or lerobot_list_jobs for listing all jobs. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It correctly indicates a read-only operation but lacks details on authentication, side effects, or output format. Adequate but not rich.
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?
A single sentence with no extraneous words, efficiently conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool (no parameters, no outputs needing explanation due to output schema), the description is complete and sufficient.
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?
No parameters exist (0 params), so baseline is 4. The description doesn't need to add parameter info beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'resolved server configuration and LeRobot checkout paths', specifying a specific verb and resource, and it distinguishes itself from sibling tools that handle builds, datasets, and commands.
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; no context about prerequisites or situations is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the basic function but does not clarify what 'visible account' means (e.g., authenticated user vs token scope) or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the tool's purpose with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, output schema exists), the description adequately covers the function. No additional context is necessary.
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?
There are no parameters, so the description cannot add parameter meaning. Baseline score of 4 applies since no additional parameter semantics are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Return' and the resource 'Hugging Face account visible to huggingface_hub', distinguishing it from sibling tools like lerobot_hf_repo_info and lerobot_hf_search_datasets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking the current Hugging Face account, but lacks explicit guidance on when to use versus alternatives or any prerequisites.
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?
In the absence of annotations, the description carries the full burden. It discloses that the tool lists jobs started during the server process, implying an ephemeral scope (not persistent across restarts). This provides useful behavioral context, though it could additionally state that it is read-only or describe the output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no extraneous information. It is front-loaded and efficient, conveying the tool's purpose and scope without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (zero parameters, clear purpose, output schema present), the description is fully adequate. It provides the essential information an agent needs to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters and the schema coverage of descriptions is 100%. The description adds meaning beyond the empty schema by specifying the precise scope of listing (background jobs started during the server process), which helps the agent understand what will be returned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists background jobs started during the MCP server process. It uses a specific verb ('List') and resource ('background jobs'), and the scope ('during this MCP server process') differentiates it from sibling tools that operate on individual jobs or other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool (to list background jobs started in the current server process). It provides clear context for usage, though it does not explicitly state when not to use it or mention alternatives. However, the sibling tool names (e.g., lerobot_job_status, lerobot_cancel_job) provide implicit differentiation.
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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