Orbit-MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation3/5
Several tools have overlapping purposes, such as discover_gateway_tools and list_enabled_tools both listing tools from enabled servers. list_available_servers vs list_enabled_servers are distinct but could confuse agents. Description clarity helps, but the boundaries between some tools remain fuzzy.
Naming Consistency4/5Most tools follow a verb_noun pattern (list_packs, create_pack, enable_server). Minor deviations exist: hello_orbit is not verb_noun, gateway_status uses noun_noun instead of get_gateway_status. These are small inconsistencies in an otherwise predictable scheme.
Tool Count3/5At 25 tools, the set is on the heavy side for the domain of MCP server management. It is borderline but each tool addresses a specific management function, so the count is not unreasonable, though it could be consolidated to reduce cognitive load.
Completeness4/5The domain covers server lifecycle (enable/disable/reset), OAuth management, gateway operations, and pack CRUD. Major operations are present, but there is no delete_pack tool (only uninstall_pack, which disables servers without removing the pack). Minor gaps exist but agents can work around them.
Average 3.7/5 across 25 of 25 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only connectivity test but does not explicitly state side effects, auth requirements, or what 'status' includes. The agent is left to infer that this is a safe, non-destructive operation.
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, concise sentence that omits unnecessary detail. It is front-loaded with the action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter and an output schema, so the description need not explain return values. However, it lacks parameter semantics and usage context, making it minimally viable but not fully complete for an agent to use correctly without additional inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description adds no information about the 'message' parameter. The parameter is optional with a default, but neither the schema nor the description explains its purpose or expected format, leaving the agent without semantic guidance.
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: 'Test connectivity and show Orbit-MCP status.' It uses specific verbs and resources, making the purpose unambiguous. While it doesn't explicitly differentiate from siblings like gateway_status, the intent is obvious enough for an agent to select it for connectivity checks.
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. The description simply states what it does without mentioning prerequisites, exclusions, or comparison to related tools like check_server_auth or gateway_status.
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 reveals the return type but adds no information about side effects, permissions, performance implications, or behavior beyond the schema. With no annotations provided, the description carries the full burden and fails to disclose whether this tool queries live servers, caches results, or requires prior setup.
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?
Two short sentences put the purpose first and the return value second. There is no filler or redundant information, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description explains the output and has no parameters, it does not clarify the relationship to sibling tools like list_enabled_tools or list_available_servers. Given the rich sibling context, a more complete description would mention when this tool should be used or how it differs from nearby alternatives.
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, so the schema is empty. Per the rubric, the baseline for 0 params is 4. The description adds context about the tool's scope ('from enabled Docker MCP servers'), which is sufficient and meaningful.
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 with a specific verb ('Discover') and a specific resource ('tools available from enabled Docker MCP servers'). It also specifies the return value. However, it does not explicitly differentiate from sibling tool 'list_enabled_tools', which may overlap in purpose.
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. It does not mention any exclusions, prerequisites, or relationships to sibling tools like list_enabled_tools or list_available_servers, leaving the agent uncertain about the best tool for a given context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 states the operation and return type but does not disclose whether the update replaces the entire configuration or merges with existing values, nor any permissions or side effects. This lacks necessary transparency 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured in an Args/Returns format. It avoids unnecessary words, though the parameter lines slightly duplicate schema information. It remains efficient and readable.
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, no annotations, and presence of an output schema, the description covers the basic operation and parameters. However, it lacks usage guidance and behavioral details, leaving gaps for an agent to safely invoke the tool without further 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?
Schema description coverage is 0%, so the description must compensate. It provides brief definitions for each parameter, such as 'Name of the pack to update' and 'New list of servers (optional)'. However, it does not clarify critical semantics like whether the 'servers' list replaces or appends to existing servers, which limits its value.
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 tool updates an existing pack, using a specific verb+resource construction. It distinguishes from sibling tools like create_pack, install_pack, and uninstall_pack by focusing on modifying an existing entity.
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 use for modifying pack configuration, but provides no explicit instructions on when to use this tool versus alternatives like add_server_to_pack or remove_server_from_pack. It does not mention any exclusions or preferred scenarios.
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 only mentions the return dictionary and does not disclose side effects, permissions, idempotency, or failure conditions. For a mutation tool, 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 concise and well-structured with an opening sentence, Args, and Returns sections. Every part earns its place with no redundancy.
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 simple tool with an output schema, the description covers the basics but misses usage context and behavioral details. It is adequate but incomplete given the lack of annotations.
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. The Args section provides basic explanations like 'Name of the server to add', which adds meaning beyond the schema titles but remains minimal.
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 'Add a server to an existing pack' with a specific verb and resource. It distinguishes from siblings like create_pack and remove_server_from_pack by specifying 'existing pack'.
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?
No explicit guidance on when to use this tool vs alternatives, and no prerequisites or exclusions are mentioned. The phrase 'to an existing pack' implies the pack must exist, but this is not stated as usage guidance.
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 the full burden of behavioral disclosure. It only states that it creates a pack and returns a dictionary, but omits critical behaviors such as whether creation is idempotent, what happens if the pack name already exists, whether servers must be pre-existing, or what permissions are required.
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 concise and well-structured: a single clarifying sentence followed by a clear Args section and a Returns note. Each parameter is listed with a brief, purposeful explanation, and there is no redundant filler.
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 simple 4-parameter create tool with an output schema, the description covers the main essentials: purpose, parameters, and return type. However, it lacks integration with sibling tools (e.g., how this relates to install_pack or create_company_pack_template), any behavioral constraints, and does not explain what constitutes a valid server list.
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 descriptions of pack_name, description, servers, and tags add essential meaning beyond the bare schema. The examples for pack_name and the note that tags are optional for categorization are helpful. However, it could specify more about valid server names or whether pack_name has format 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 opening sentence 'Create a new company/team pack with specific MCP servers' uses a specific verb and resource, clearly distinguishing it from sibling tools like update_pack, list_packs, and add_server_to_pack. This makes the tool's sole purpose unmistakable.
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 such as update_pack or create_company_pack_template. It does not mention prerequisites, exclusions, or typical scenarios, leaving the agent to infer usage solely from the tool name.
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 must disclose behavioral traits, but it only states the removal action and return type. It does not mention whether the operation is destructive, reversible, requires permissions, or what happens if the server or pack does not exist, creating ambiguity 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 extremely concise, with a clear structure: one sentence for purpose, an Args section, and a Returns section. Every word earns its place, and there is no fluff or repetition.
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 simple two-parameter tool, the description covers purpose, parameters, and return type. However, it omits error conditions, prerequisites, and effects on the server or pack state. Given the absence of annotations and the presence of an output schema, a bit more detail on behavior would improve completeness, but it is minimally viable.
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 brief one-line meanings for each parameter ('Name of the pack', 'Name of the server to remove'), which is slightly more than the schema titles 'Pack Name' and 'Server Name'. However, it lacks format, constraints, or relationships between the parameters, only marginally compensating for the 0% schema description coverage.
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 a server from an existing pack', identifying the verb and both resources (server and pack). This is specific and distinguishes it from sibling tools like add_server_to_pack and disable_server.
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 its usage through the action but provides no explicit context on when to use it or alternatives. It does not mention prerequisites (e.g., the pack must exist) or contrast with add_server_to_pack, leaving the agent to infer.
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 only states the action and return type, without disclosing side effects, reversibility, error behavior, or whether the provider must already be authorized. This is too thin for a mutation operation.
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 concise, front-loads the purpose, and uses a clear Args/Returns structure. Every sentence earns its place with no filler or redundancy.
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 simple tool with an output schema, the description covers purpose, arguments, and return value. However, it lacks guidance on edge cases, behavioral side effects, and when this tool is appropriate relative to siblings, which limits its 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?
The input schema has zero description coverage, so the description must compensate. It does add meaning by providing examples ('github', 'gdrive'), but it does not enumerate all possible providers or clarify constraints like whether the provider must be previously authorized.
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 'Revoke OAuth authorization for a provider,' using a specific verb and resource. It unambiguously distinguishes itself from sibling tools like authorize_oauth and list_oauth_providers.
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 this tool is for revoking OAuth access but does not explicitly state when to use it instead of alternatives, nor does it mention any exclusions or prerequisites. The context is clear but lacks explicit guidance.
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 side effects. It does state that uninstall works by disabling all servers and returns a dictionary with results, but it doesn't clarify whether the pack is deleted or merely deactivated, nor reversibility or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: one sentence of purpose, then an Args/Returns structure with no fluff. Every word earns its place.
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?
The tool is simple, but the description omits important details about side effects and prerequisites. The mention of output schema covers return format, but the ambiguity between uninstall and disable leaves a gap. For an agent, it's probably sufficient to select the tool, but not fully complete.
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?
Description says 'Name of the pack to uninstall', which adds context to the schema's title 'Pack Name'. However, it's minimal and essentially restates the obvious; no format or constraints are added.
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?
Clearly states the action (uninstall) and the resource (a pack), and specifies the mechanism (disabling all servers), which distinguishes it from siblings like install_pack and disable_server.
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 vs alternatives like remove_server_from_pack or disable_server. The description is self-contained but does not mention 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?
With no annotations provided, the description carries the full burden for behavioral disclosure. It states the action and return type but does not mention potential side effects of calling arbitrary tools (some may be mutating), error handling, auth requirements, or the need for the tool to be enabled/listed. The phrase 'enabled Docker MCP servers' hints at a constraint but is insufficient for a tool that can execute any 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 extremely concise: a single opening sentence plus terse Args and Returns sections. No wasted words, and the structure is clear and scannable. Every sentence earns its place.
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 this tool dynamically invokes arbitrary tools, the description should provide more context about verifying the tool is enabled, the variability of results, and potential errors. The output schema existence reduces the need to explain returns, but the description only says 'Dictionary with tool execution result' without guidance on how to handle failure or indirection. The tool would benefit from referencing sibling tools like list_enabled_tools or noting that results vary by target 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 input schema has 0% description coverage, so the description must compensate. It does: it defines tool_name with concrete examples ('create_issue', 'search_repositories') and clarifies that arguments is a dictionary of arguments, adding meaning beyond the bare schema. The parameter semantics are well addressed, though it could elaborate on argument structure for specific tools.
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 'Call a tool from enabled Docker MCP servers' with a specific verb ('call') and resource ('tool from enabled Docker MCP servers'). This distinguishes it from sibling tools that manage servers, OAuth, or packs. The examples for tool_name further clarify the intended use.
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 context 'from enabled Docker MCP servers' implies a prerequisite (servers must be enabled) but does not explicitly instruct when to use this tool versus alternatives like list_enabled_tools or discover_gateway_tools. No exclusions or alternative tool references are provided, so usage guidance is implied rather than explicit.
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 for behavioral disclosure. It mentions the return type but does not explicitly state that the tool has no side effects, whether authentication is required, or what errors might occur. The non-destructive nature is only implied.
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 concise and front-loaded: it states the purpose in one short sentence and the return type in a second. No unnecessary words or redundancy.
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?
For a simple zero-parameter status check with an output schema, the description covers the core purpose and return type. However, it lacks explicit mention of no side effects or when to prefer this over sibling tools. Given the simplicity, it is nearly complete but not fully.
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, and the baseline score is 4. The description adds context about the target resource (Docker MCP Gateway), but no parameter explanations are needed since none exist.
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 ('Check the status') and the target resource ('Docker MCP Gateway'). It is distinct from sibling tools like start_gateway, stop_gateway, and reset_all_servers, which perform modifications.
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 given on when to use this tool versus alternatives. It does not mention that this is a read-only status check or that other tools modify the gateway state. Usage is only implied by the word 'Check'.
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 the full burden of behavioral disclosure. It mentions the return type but does not explicitly state whether the operation is read-only, requires any credentials, or has side effects. The verb 'check' is suggestive but not an explicit safety guarantee.
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 short and structured with Args/Returns, but it slightly repeats 'authentication requirements and status' in the title and the returns section. Still, it's efficient.
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?
For a simple one-parameter tool, the description covers purpose, parameter, and return. However, it lacks any mention of error conditions or prerequisites, and since an output schema exists, some return details are unnecessary.
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 compensates by defining the 'server_name' parameter with examples ('github', 'slack'), giving clear semantic meaning beyond the bare schema.
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 states a clear verb ('check') and a specific resource ('authentication requirements and status for a server'). It distinguishes from sibling tools by focusing on auth inspection rather than enabling/disabling or listing servers.
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 a use case (checking auth status) but does not explicitly state when to use it over alternatives. No exclusions or comparisons with sibling tools are 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?
With no annotations, the description carries the full burden of behavioral disclosure. It only provides a vague return format ('Dictionary with success status and server removal details') and does not clarify whether the action is reversible, what happens if the server is already disabled, or any side effects. The term 'removal details' is ambiguous and could mislead.
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 concise and well-structured: a one-sentence purpose followed by organized Args and Returns sections. No unnecessary words or repetition.
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 simple one-parameter tool, the description covers the purpose, parameter, and return shape. However, it lacks usage guidance and behavioral transparency, and the ambiguity around 'removal' leaves gaps in understanding the tool's full effect. The presence of an output schema reduces the need to explain return values in detail, but the description still does not fully contextualize the operation.
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 one required parameter with no description. The description compensates by explaining server_name as the name of the server to disable and gives concrete examples ('github', 'slack', 'notion'), adding meaning beyond the schema.
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 states a clear action ('Disable') and a specific resource ('a specific Docker MCP server by name'), distinguishing it from sibling tools like enable_server and list_enabled_servers.
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: you disable a server by name, likely when you want to turn off a currently enabled server. However, it does not explicitly state when to use it versus alternatives, nor does it mention 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?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions the return value (dictionary with success status and gateway details) but does not disclose side effects, idempotency, prerequisites (e.g., Docker daemon), or behavior if the gateway is already running. This is a state-changing operation, so more transparency is needed.
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 succinct, front-loaded with the primary purpose, and the return format is cleanly separated. Every sentence earns its place without extraneous detail.
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?
The description covers the core function and return shape, and an output schema exists, so return-value documentation is not necessary. However, it lacks important contextual details: when to use this tool relative to start/stop/status siblings, prerequisites, and idempotency concerns. For a simple side-effectful tool, this is adequate but not complete.
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, so the baseline is 4. The description correctly provides no parameter information, and the input schema confirms no parameters are required.
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 ('Start') and the specific resource ('Docker MCP Gateway') intended for tool execution. This distinguishes it from siblings like stop_gateway and gateway_status.
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 phrase 'for tool execution' implies this is a prerequisite for running tools, but there is no explicit guidance on when to choose this over alternatives or what conditions must be met beforehand. No exclusionary or alternative-tool guidance 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 present, so the description must carry the behavioral disclosure burden. It does add useful context by noting 'OAuth-first authentication' and describing the return dictionary, but it does not explain side effects, reversibility, or whether any prerequisite like a running gateway is required.
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 brief, front-loaded with the core action, and uses a clean Args/Returns structure. Every line adds meaningful information without unnecessary padding.
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?
For a one-parameter tool with an output schema, the description covers the essential purpose, parameter, and return shape. The missing usage guidance and deeper side-effect details are notable, but the tool's simplicity and the provided OAuth context keep the description reasonably complete.
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%, and the description compensates by defining server_name as the name of the server to enable and providing concrete examples like 'github', 'slack', and 'notion'. This is sufficient for a single required parameter, though it could have referenced list_available_servers for valid names.
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 opens with 'Enable a specific Docker MCP server by name', giving a specific verb and resource. The OAuth-first qualifier and the contrast with sibling tools like disable_server and list_enabled_servers make the tool's purpose unmistakable.
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 when-to-use or when-not-to-use guidance is provided. The description does not mention alternative tools such as authorize_oauth, check_server_auth, or list_available_servers, and it lacks preconditions or context for when enabling is appropriate.
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 transparency burden. It discloses that the tool returns a list of pack configurations with server details, implying a read-only operation. However, it does not explicitly state safety, authorization requirements, or any potential side effects, leaving some ambiguity.
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 concise and front-loaded with the main action ('List all available company/team packs'), followed by a brief return summary. It contains no superfluous words and is well-structured for quick parsing.
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?
For a simple list tool with an output schema and no parameters, the description is largely sufficient. It explains the resource and what is returned. However, it does not clarify what 'available' means in relation to installed/enabled states, which could be ambiguous given sibling tools like list_enabled_tools.
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, so the baseline score is 4. The description does not need to compensate for parameter information since there are none, and the empty schema already indicates no inputs are required.
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 uses a specific verb 'List' and clearly identifies the resource as 'available company/team packs'. It distinguishes this tool from siblings like get_pack_info (singular) and create_pack (creation) by indicating a list operation.
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 regarding when to use this tool versus alternatives such as get_pack_info for a single pack or list_enabled_tools for enabled tools. The description lacks any context about preferred use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action and return format but does not disclose reversibility, prerequisites, authorization needs, or side effects of disabling all servers. For a bulk mutation tool, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with one clear sentence for the action and a single line for the return format. Every word earns its place, and the key information is front-loaded.
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 the tool's low complexity (0 params) and the presence of an output schema, the description adequately covers the purpose and expected return. Minor gaps exist in behavioral detail, but these are arguably covered under transparency. The description is complete enough for an agent to understand the tool's primary function.
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, and the input schema is trivially complete. The rubric gives a baseline of 4 for zero-param tools, and there is no parameter documentation burden for the description to overcome.
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 uses a specific verb ('Disable') and resource ('all currently enabled MCP servers'), clearly distinguishing it from sibling 'disable_server' which targets a single server. The phrase 'company reset functionality' adds context, making the purpose unmistakable.
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 through 'company reset functionality' but does not explicitly state when to use this tool over alternatives like disable_server. No exclusions or alternative tools are mentioned, leaving usage implicit rather than explicit.
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 disclose behavioral traits itself. It only mentions the action and return type, but omits important side effects like disconnection of clients, reversibility, or whether the gateway must be running. This leaves the tool's behavior largely opaque for a mutation-like operation.
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 two short sentences, directly stating the action and the return value. It is concise, well-structured, and contains no unnecessary information.
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 the tool's simplicity (zero params, no nested objects) and the presence of an output schema, the description covers the essential action and return. However, it does not mention prerequisites or the impact on running sessions, which would improve completeness slightly.
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 and the input schema is empty, so the baseline of 4 applies. The description adds no parameter information, but none is needed given the absence of 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 states the specific action 'Stop the Docker MCP Gateway', which is a clear verb+resource pair. It distinguishes well from sibling tools like start_gateway and gateway_status, making the tool's purpose unambiguous.
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?
Usage context is only implied by the verb 'Stop'. There is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The agent can infer the intended use from the name and sibling context, but no direct guidance is 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?
With no annotations, the description carries the full burden of disclosing side effects and required permissions. It only mentions a return dictionary and does not explain that starting an OAuth flow typically involves external interactions, potential user involvement, or state changes. No permissions or rate limits are mentioned. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured with an Args section and Returns section. It avoids unnecessary detail and is easy to skim, making it efficient for an agent to parse.
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?
The tool has an output schema, so return values are covered. However, the description lacks essential context around prerequisites (e.g., whether a provider must be pre-configured), the nature of the OAuth flow (interactive, redirects, external calls), and any postconditions. For a complex tool like OAuth authorization, this leaves the agent under-informed.
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 parameter 'provider' is given clear semantics and examples ('github', 'gdrive') in the description, which the schema does not provide (only 'Provider'). This helps the agent select appropriate values, though the description could have listed more provider options or referenced the list_oauth_providers tool.
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 tool's action (start OAuth authorization flow) and its target (a provider like 'github' or 'gdrive'). It distinguishes itself from sibling tools like revoke_oauth, which performs the opposite action, and list_oauth_providers, which merely lists providers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to initiate OAuth authorization for a provider. However, it does not explicitly mention alternatives or exclusions, such as 'use revoke_oauth to undo' or 'only works for providers listed in list_oauth_providers'. This is sufficient but not fully explicit.
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 carry the full burden of behavioral disclosure. It only states the return value ('Dictionary with pack creation results') and does not mention side effects, permissions, reversibility, or resource impact. As a creation tool, this is a significant gap—the agent cannot infer whether this is a mutating operation or has 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, using an Args/Returns format that front-loads the essential purpose and parameter details. Every sentence serves a purpose: the main description, parameter explanation with enumerated valid values, and return type. No wasted words.
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?
The tool has a single parameter and an output schema, so the description need not detail return values extensively. However, it lacks guidance on when to use this tool versus alternatives (e.g., create_pack) and does not disclose behavioral side effects. For a simple create tool, the description is adequate but has clear gaps in usage context and transparency.
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 adds substantial meaning to the schema's template_name parameter by listing all valid values ('frontend-stack', 'backend-stack', etc.). Since schema coverage is 0%, this enumeration compensates for the lack of schema-level documentation. It does not explain what each template does, but the list provides concrete guidance for selecting a valid input.
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 tool's purpose: 'Create a predefined company pack from templates'. The term 'predefined' and 'from templates' distinguishes it from sibling tools like create_pack, which likely handles custom packs. Including the list of template names further clarifies the specific resource being acted upon.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: when creating a company pack from a predefined template. However, it does not explicitly mention alternatives (e.g., create_pack for custom packs) or state when not to use it. This is a clear context but lacks explicit exclusions.
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 present, so the description must carry the full burden. It discloses the return type (a dictionary) and content (pack information and server status), but it does not explicitly state that the operation is read-only or describe error behavior. This is adequate for a simple getter 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with three clear sections (purpose, args, returns). Every sentence contributes value, and there is no fluff or repetition. It uses a standard docstring format that is easy to parse.
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?
For a simple one-parameter getter tool, the description is largely complete. It names the parameter and gives a high-level return explanation. The existence of an output schema reduces the need to detail return fields. However, it does not clarify what 'server status' specifically refers to, which leaves a small ambiguity.
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 zero description coverage (only a title 'Pack Name'), but the tool description adds 'Name of the pack to inspect', which clarifies the parameter's meaning. Since there is only one parameter, this compensation is sufficient.
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 'Get detailed information about a specific pack', which is a specific verb+resource pattern. The word 'specific' distinguishes it from sibling tools like list_packs, and the mention of 'server status' adds specificity about what details are returned.
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 for inspecting a single pack by name, but it does not explicitly compare to alternatives such as list_packs or update_pack. No 'when-not-to-use' guidance is provided, so the usage context is implied rather than explicit.
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 of disclosing behavior. It states the tool returns a list of providers and authorization status, implying a read-only operation without explicitly saying so. It adds no context about prerequisites, side effects, or limitations, but the simplicity of a list tool reduces the need for extensive disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but contains redundancy: the first and second sentences both state it lists providers and authorization status. The usage sentence adds value, but the 'Returns a list' sentence is unnecessary and could be merged or removed. The structure front-loads the core purpose, but the redundancy detracts from conciseness.
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?
For a simple, parameterless list operation with an output schema, the description adequately conveys purpose, output scope, and a use case. It does not explicitly differentiate from sibling tools, but the clarity of the purpose is sufficient for an agent 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.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so the baseline is 4 per the rubric. The description's use of 'available' adds minor semantic context about filtering, which is more than required. No parameter explanation is needed.
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 tool lists available OAuth providers and their authorization status, using the specific verb 'List' and a distinct resource. This differentiates it from action-oriented siblings like authorize_oauth and revoke_oauth. The purpose is unambiguous and not tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides a use case: 'Use this to see which services support OAuth and whether they're authorized,' giving clear when-to-use guidance. However, it does not mention alternatives or exclusions, such as when to use check_server_auth instead, so it falls short of the highest level.
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 full burden. It discloses the return format ('list of tool dictionaries with name, description, and server info') and hints at behavior by stating it reflects currently enabled servers. However, it does not explicitly confirm a read-only, side-effect-free operation or discuss any potential latency or server communication, leaving some transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary purpose. The first sentence states what the tool does, the second explains the return value and usage context. No wasted words.
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?
For a zero-parameter tool, the description is complete: purpose, return value, and when to use it. An output schema exists, but the description already covers return details. It could be slightly richer about whether it causes any state change, but overall it is adequate.
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 accepts zero parameters, and the input schema is empty. The baseline for 0 params is 4, and the description does not need to add parameter detail. It correctly focuses on behavior and return values.
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 is explicit: 'List all available tools from currently enabled servers.' It uses a specific verb and resource, and distinguishes from sibling tools like list_available_servers (which lists servers, not tools) and discover_gateway_tools (which is gateway-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Use this after enabling servers to see what tools are available.' This implies a workflow step and differentiates from alternative tools for listing servers. It does not explicitly mention when not to use it, but the guidance is sufficient.
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, the description carries full burden. It discloses that installation works by enabling all servers, that OAuth prompting may occur, and that the return includes auth requirements. It does not mention reversibility, permissions, or partial success, but the core behavioral traits are transparently presented.
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 concise and well-structured: a clear one-line summary followed by Args and Returns sections. Every line serves a purpose, and the information is front-loaded. No filler or redundancy.
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?
The description adequately covers the input parameters, the action, and the return value. While it does not mention edge cases like partially enabled servers or prerequisites, the presence of an output schema reduces the need to elaborate on return details. For a moderately complex tool, this is sufficient but could mention when it might prompt for OAuth.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains both parameters beyond the schema: pack_name with an example ('frontend-stack') and enable_oauth with the condition 'if needed.' Since schema description coverage is 0%, the description fully compensates by providing meaningful semantic context for each parameter.
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 verb and resource: 'Install a pack by enabling all its servers.' This distinguishes it from sibling tools like create_pack (which creates a definition) or uninstall_pack (which removes), and also specifies the mechanism (enabling servers). The one-line summary is specific and unambiguous.
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 by stating the tool installs a pack, but it does not explicitly say when to use this over alternatives like enable_server or add_server_to_pack. No exclusions or alternative tools are mentioned. It does provide clear context about what the tool does, but lacks direct guidance on selection.
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 provided, the description carries the full burden. It states the tool returns a list of server dictionaries with name, description, and status, which adds useful context about the output format. However, it does not explicitly state that it is a read-only operation with no side effects, nor does it mention any authentication or rate-limit considerations. For a simple list operation, this is 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: first sentence states the action, second sentence describes the return value, third sentence gives usage guidance. Every sentence earns its place, with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (zero parameters, no nested objects) and the presence of an output schema, the description is complete. It includes the source (Docker MCP catalog), the return structure, and the intended use case. No additional context is necessary for an agent to correctly invoke this 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 tool has zero parameters, so the schema already fully documents parameters. The description adds no parameter information, but none is needed. Baseline for 0 parameters is 4, and the description does not mislead or miss anything.
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 identifies the tool's function: listing all available MCP servers from the Docker MCP catalog. It distinguishes from siblings like list_enabled_servers by specifying 'available' servers, and it names the specific resource (Docker MCP catalog). The verb 'list' is precise and the resource is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'Use this to see what servers you can enable with enable_server.' This tells the agent when to use the tool (before enabling a server), effectively linking it to a related tool. However, it does not explicitly mention alternatives like list_enabled_servers, so it lacks a direct exclusions statement.
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 behavioral disclosure burden. It adequately explains the return output (list of dictionaries with name, status, container info) and implies a non-mutating read operation. It does not mention authentication, but this is not critical 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences covering purpose and return format. No wasted words, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters) and the presence of an output schema, the description is complete. It covers the essential information without redundancy.
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, so the description need not explain parameter meaning. The baseline for zero-parameter tools is 4, and the description is consistent with this.
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 uses a specific verb ('List') and resource ('currently enabled MCP servers'), making the tool's function clear. It also distinguishes from sibling tools like list_available_servers by specifying 'enabled'.
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?
While the description clearly states what it does, it does not explicitly mention when to use this tool versus alternatives such as list_available_servers. The usage context is implied by the word 'enabled' but not directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Wirasm/orbit-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server