Google Tag Manager MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific resources and actions in Google Tag Manager, such as create_tag, get_tag, update_tag, and delete_tag for tags, with no overlap or ambiguity. The tools are organized around core entities like accounts, containers, workspaces, tags, triggers, and variables, making it easy for an agent to select the correct one.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern throughout, such as create_container, get_tag, list_variables, and update_trigger, with no deviations in style or convention. This predictability enhances readability and usability for agents interacting with the server.
Tool Count3/5
With 26 tools, the count is on the higher side for a typical MCP server, which may feel heavy and potentially overwhelming for agents. While it covers a comprehensive domain, a more streamlined set could improve coherence without sacrificing functionality.
Completeness5/5
The tool set provides complete CRUD/lifecycle coverage for Google Tag Manager entities, including authentication, account management, and operations for containers, workspaces, tags, triggers, and variables. There are no obvious gaps, and agents can perform all essential workflows without dead ends.
Average 2.9/5 across 26 of 26 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI 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.json to 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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Creates a new trigger' implies a write/mutation operation, but the description doesn't mention whether this requires specific permissions, what happens on success/failure, whether the trigger is immediately active, or any side effects. For a creation tool with 27 parameters and no annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (one sentence), this is a case of under-specification rather than effective brevity. The single sentence doesn't earn its place by providing any meaningful information beyond the tool name. For a complex tool with 27 parameters, this level of conciseness is detrimental to understanding.
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?
This is a creation/mutation tool with no annotations, no output schema, and 27 parameters. The description is completely inadequate for the complexity involved. It doesn't explain what a trigger is, what system it operates in, what happens after creation, or provide any context about the rich parameter set. Given the absence of structured metadata, the description should do much more heavy lifting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all 27 parameters are documented in the input schema itself. The description adds zero additional information about parameters, not even mentioning that different parameters apply to different trigger types. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description provides no value beyond what's already in the structured data.
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 '新しいトリガーを作成します' (creates a new trigger) is a tautology that essentially restates the tool name 'create_trigger'. It doesn't specify what kind of trigger, what system it's for, or how it differs from sibling tools like 'update_trigger' or 'delete_trigger'. While it contains a verb and resource, it's too generic to be helpful for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like authentication), when to choose this over 'update_trigger', what happens after creation, or any context about the trigger lifecycle. Given the complex sibling toolset including authentication and other trigger operations, this is a critical omission.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'タグを削除します' indicates a destructive mutation operation, but it doesn't disclose whether deletion is permanent/reversible, what permissions are required, whether it affects other entities, or what the response looks like. For a destructive operation with zero annotation coverage, this is a significant gap in behavioral 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 - a single Japanese phrase that directly states the action. There's no wasted verbiage or unnecessary elaboration. However, this conciseness comes at the cost of completeness, as it provides minimal contextual information beyond the basic action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive mutation tool with 4 required parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the deletion's consequences, required authentication state, error conditions, or what identifiers are needed. The agent would struggle to use this tool correctly without significant trial and error or external documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all 4 parameters are documented in the schema itself (accountId, containerId, workspaceId, tagId). The description adds no additional parameter information beyond what's in the schema - it doesn't explain the hierarchical relationship between these IDs or provide usage examples. With complete schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'タグを削除します' (deletes a tag) clearly states the verb ('削除します' - delete) and resource ('タグ' - tag), which is better than a tautology. However, it doesn't differentiate from sibling tools like 'delete_trigger' or 'delete_variable' - it only states the generic action without specifying what makes tag deletion unique compared to other deletion operations in this system.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like needing authentication first), when deletion is appropriate versus updating a tag with 'update_tag', or what happens to associated resources when a tag is deleted. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention permissions needed, side effects, error conditions, or what happens on success/failure. For a creation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese with zero wasted words. It's appropriately sized and front-loaded, though it could benefit from more detail given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what a 'tag' is in this context, what happens after creation, or provide any context about the broader system (e.g., Google Tag Manager). The agent must rely entirely on the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining relationships between parameters or providing examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '新しいタグを作成します' (creates a new tag) states a clear verb+resource action but is vague about what kind of tag or in what context. It doesn't distinguish from sibling tools like 'create_container' or 'create_trigger' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'update_tag' or 'list_tags'. The description doesn't mention prerequisites, dependencies, or contextual constraints, leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose whether this is a write operation (implied by 'create'), what permissions are needed, how errors are handled, or what the response looks like (no output schema). This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese ('新しい変数を作成します'), which is appropriately sized and front-loaded with the core action. There's no wasted text or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It lacks context on the domain (e.g., Google Tag Manager variables), behavioral traits, usage scenarios, or expected outcomes, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly (e.g., 'type' includes examples like 'c' for constant). The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '新しい変数を作成します' (creates a new variable) clearly states the verb+resource action, but it's vague about what kind of variable is being created (e.g., for Google Tag Manager, as implied by sibling tools). It doesn't distinguish from sibling tools like 'create_tag' or 'create_trigger' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, account/container/workspace setup) or differentiate from similar tools like 'update_variable' or 'delete_variable' in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action is deletion, implying a destructive operation, but doesn't mention whether this is permanent, reversible, requires specific permissions, or has side effects (e.g., impact on associated workflows). For a destructive tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence in Japanese that efficiently conveys the core action without unnecessary words. It's front-loaded with the key information (deleting a trigger) and has zero waste, making it highly concise and well-structured for its minimal content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive tool with no annotations, no output schema, and 4 required parameters, the description is incomplete. It doesn't address behavioral aspects like permanence or permissions, provide usage context, or explain return values. The high schema coverage helps with parameters, but overall, the description lacks sufficient detail for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with all four parameters documented in Japanese (accountId, containerId, workspaceId, triggerId). The description adds no additional parameter information beyond what's in the schema, such as format examples or relationships between IDs. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'トリガーを削除します' (Deletes a trigger) clearly states the action (delete) and resource (trigger), but it doesn't distinguish this tool from sibling tools like 'delete_tag' or 'delete_variable' that perform similar deletion operations on different resources. The purpose is understandable but lacks differentiation from related deletion 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing triggerId from list_triggers or get_trigger), nor does it specify when deletion is appropriate versus updating with 'update_trigger'. There's no context about alternatives 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 is deletion, implying a destructive operation, but doesn't disclose critical behavioral traits such as whether deletion is permanent, requires specific permissions, has side effects, or returns any confirmation. This is a significant gap for a destructive tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence in Japanese ('変数を削除します'), which is front-loaded and wastes no words. It efficiently conveys the core action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with 4 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, return values, error conditions, or usage context, leaving significant gaps for an AI agent to understand and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all four parameters (accountId, containerId, workspaceId, variableId) documented in the schema. The description adds no additional meaning beyond the schema, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '変数を削除します' (Deletes a variable) clearly states the action (delete) and target resource (variable), which is adequate. However, it doesn't differentiate from sibling tools like 'delete_tag' or 'delete_trigger' beyond the resource name, and it lacks specificity about what kind of variable (e.g., in what context or system).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing authentication first), when not to use it, or how it relates to sibling tools like 'get_variable' or 'update_variable'. The description is standalone without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation but doesn't specify if it requires authentication, has rate limits, returns structured data, or handles errors. For a tool with four required parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (four required IDs, no output schema, no annotations), the description is insufficient. It doesn't explain what 'details' include, how to obtain the required IDs, or the expected return format. For a retrieval tool in a system with authentication and multiple entities, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all four parameters documented in the schema. The description adds no additional parameter semantics beyond implying that 'triggerId' identifies the target, which is already clear from the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '指定されたトリガーの詳細を取得します' (Get details of the specified trigger) clearly states the verb '取得' (get) and resource 'トリガー' (trigger), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_triggers' or 'update_trigger', which would require more specificity about scope or granularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites like authentication, distinguish it from 'list_triggers' for bulk retrieval, or indicate that it's for fetching a single trigger by ID rather than creating or updating one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('get a list') without mentioning permissions needed, pagination behavior, rate limits, or response format. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose. It is appropriately sized and front-loaded with no wasted words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a list operation with three required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like pagination, sorting, or error handling, nor does it explain the return values, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage (all three parameters are documented in Japanese), so the baseline is 3. The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between accountId, containerId, and workspaceId, or providing examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '指定されたワークスペースの変数一覧を取得します' (Get a list of variables for the specified workspace) clearly states the verb ('取得します' - get) and resource ('変数一覧' - list of variables), but it doesn't distinguish this tool from its sibling 'get_variable' which retrieves a single variable. The purpose is understandable but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_variable' (for single variables) or other list tools (e.g., 'list_tags', 'list_triggers'). It mentions the workspace scope but offers no explicit usage context, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. '作成します' (creates) implies a write operation, but the description doesn't disclose any behavioral traits such as permissions required, whether creation is idempotent, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose. It's appropriately sized and front-loaded with no unnecessary words or structural issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool (creating a container) with no annotations and no output schema, the description is incomplete. It doesn't explain what a container is in this context, what the creation entails, or what to expect as a result. The agent lacks crucial context for proper tool invocation despite the good schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information beyond what the input schema provides. Schema description coverage is 100%, with all three parameters (accountId, name, usageContext) documented in the schema. The baseline score of 3 is appropriate as the schema does the heavy lifting, but the description doesn't add any contextual meaning about parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '新しいコンテナを作成します' (creates a new container) clearly states the action (creates) and resource (container). It distinguishes from siblings like 'get_container' or 'list_containers' by specifying creation rather than retrieval. However, it doesn't specify what type of container or differentiate from other creation tools like 'create_tag' or 'create_variable' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when not to use it, or how it relates to sibling tools like 'get_container' or 'list_containers'. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'creating a version for publication preparation,' which implies a write operation, but doesn't disclose behavioral traits like whether this is destructive (e.g., overwrites existing versions), requires specific permissions, has side effects (e.g., locks the workspace), or rate limits. The description is too vague to guide safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence in Japanese that directly states the tool's purpose. It's front-loaded with the main action and avoids unnecessary words. However, it could be slightly more informative without losing conciseness, such as by clarifying what 'version' means in this system.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a write operation (creating a version) with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., version ID, status), error conditions, or how it interacts with other tools (e.g., after creating a version, what next?). For a mutation tool with 5 parameters, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with all parameters documented in Japanese (e.g., accountId, containerId, workspaceId as required; name and notes as optional). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Since schema coverage is high, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create a version') and the target ('workspace changes'), making the purpose understandable. It distinguishes from siblings like create_container or create_tag by specifying it's about versioning workspace changes. However, it doesn't explicitly mention what a 'version' entails in this context (e.g., a snapshot, release candidate).
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 minimal guidance, only implying this is for 'preparing for publication' of workspace changes. It doesn't specify when to use this versus alternatives like directly publishing or saving drafts, nor does it mention prerequisites (e.g., needing a workspace with changes). No explicit when-not-to-use or sibling tool comparisons 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 provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('取得します'), but doesn't cover other important aspects like whether it requires authentication, what happens if the container doesn't exist, rate limits, or the format of returned details. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without any unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what '詳細' (details) includes, whether authentication is required, error conditions, or how this differs from sibling list operations. The context signals show this is a simple tool, but more behavioral context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (accountId and containerId) clearly documented in the schema. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high coverage, resulting in the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('取得します' - get/retrieve) and resource ('指定されたコンテナの詳細' - details of the specified container), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_containers' or 'get_workspace', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_containers' (for listing multiple containers) or 'get_workspace' (for workspace details). It also doesn't mention prerequisites such as authentication or account access, which are implied by the required accountId parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states what the tool does (get details) but doesn't disclose behavioral traits: whether this is a read-only operation, what format/details are returned, error conditions, authentication requirements, rate limits, or whether it's idempotent. For a tool with 4 required parameters and no annotations, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose. It's appropriately sized for a simple retrieval tool and front-loads the essential information. There's zero wasted verbiage or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'tag details' include, how tags relate to containers/workspaces, authentication requirements, or error handling. For a tool in what appears to be a tag management system with multiple sibling tools, more context about the tag resource and its relationships would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all 4 parameters clearly documented in Japanese (accountId, containerId, workspaceId, tagId). The description adds no parameter semantics beyond what the schema provides - it doesn't explain relationships between parameters (e.g., tagId is scoped within container/workspace) or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'get details of a specified tag' (指定されたタグの詳細を取得します), which is a specific verb+resource combination. It distinguishes from sibling tools like list_tags (which lists multiple tags) and update_tag/delete_tag (which modify tags). However, it doesn't explicitly mention what 'details' include or differentiate from get_container/get_trigger/get_variable which fetch other resource types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like authentication), when to use get_tag versus list_tags (for single vs multiple tags), or any context about tag hierarchy (tags belong to containers/workspaces). The agent must infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions retrieving details but doesn't disclose behavioral aspects like whether it's read-only, requires authentication, has rate limits, or what format/details are returned. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 4 required parameters, the description is incomplete. It doesn't explain what 'details' are returned, error conditions, or dependencies on other tools (e.g., needing IDs from 'list_variables'). For a retrieval tool in this context, more information is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters. The description doesn't add any meaning beyond the schema, such as explaining relationships between parameters or usage context. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieve/get) and the resource ('変数の詳細' - variable details), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_variables' or 'get_container', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'list_variables' or other 'get_' tools. The description only states what it does, not when it's appropriate or what prerequisites exist.
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 it retrieves details but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what 'details' include. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a description that only states the basic purpose, this is incomplete. It lacks information on authentication, response format, error cases, and how it differs from sibling tools, which is insufficient for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the three required parameters (accountId, containerId, workspaceId). The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieve/get) and resource ('ワークスペースの詳細' - workspace details), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_container' or 'list_workspaces' beyond specifying it retrieves details for a specific workspace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'list_workspaces' or 'get_container'. The description implies it's for retrieving details of a specific workspace but doesn't mention prerequisites (e.g., needing authentication) or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states this is a retrieval operation ('取得します'), implying read-only behavior, but doesn't disclose any behavioral traits like pagination, rate limits, authentication requirements, error conditions, or what happens if the account doesn't exist. For a tool with zero annotation coverage, this is insufficient disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose. There's no wasted words or unnecessary elaboration. It's appropriately sized for a simple list operation and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the output contains (e.g., container metadata, pagination tokens), authentication requirements, error handling, or how it differs from other list operations. Given the lack of structured data, the description should provide more context about the tool's behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'accountId' documented in the schema. The description doesn't add any parameter semantics beyond what's in the schema - it mentions '指定されたアカウント' (specified account) which corresponds to the accountId parameter, but provides no additional context about format, validation, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieves/gets) and resource ('コンテナ一覧' - container list) for a specified account. It distinguishes itself from siblings like 'get_container' (singular) and 'list_accounts' (different resource), but doesn't explicitly differentiate from other list operations like 'list_tags' or 'list_triggers' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (like authentication), nor does it differentiate from similar list operations for other resources. It simply states what the tool does without context about when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It indicates a read operation ('取得します') but doesn't disclose pagination, rate limits, permissions needed, error conditions, or what format the tag list returns. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose. It's appropriately sized for a simple list operation, though it could be slightly more informative without losing 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?
For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the returned tag list looks like, how results are structured, or any behavioral constraints. Given the sibling tools include various tag operations, more context about this tool's role would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional meaning about the parameters beyond implying they specify a workspace. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - get/retrieve) and resource ('タグ一覧' - list of tags) with scope ('指定されたワークスペース' - specified workspace). It distinguishes from siblings like 'get_tag' (singular) and 'create_tag', but doesn't explicitly contrast with other list operations like 'list_containers' or 'list_workspaces'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites (like authentication), when this should be used instead of 'get_tag', or how it relates to other list operations. It simply states what the tool does without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It states it retrieves a list but doesn't disclose pagination, sorting, rate limits, permissions needed, or response format. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without redundancy. It's front-loaded with the core action and resource, making it easy to parse. No unnecessary words or structural issues are present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It covers the basic purpose but misses critical context: behavioral traits (e.g., read-only nature implied but not stated), output details, and usage guidelines. Given the complexity and lack of structured data, more information is needed for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all three parameters (accountId, containerId, workspaceId) documented in the schema. The description adds no parameter-specific information beyond implying workspace context. Baseline 3 is appropriate since the schema handles parameter documentation adequately, but the description doesn't enhance understanding of parameter relationships or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieve) and resource ('トリガー一覧' - list of triggers) with scope ('指定されたワークスペース' - specified workspace). It distinguishes from siblings like 'get_trigger' (singular) and 'create_trigger' by focusing on listing multiple triggers. However, it doesn't explicitly differentiate from other list tools like 'list_tags' or 'list_variables' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), compare with siblings like 'get_trigger' for single trigger retrieval, or specify use cases (e.g., browsing vs. detailed inspection). The agent must infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states this is a retrieval operation ('取得します'), implying it's read-only, but doesn't disclose behavioral traits like whether it requires authentication, returns paginated results, has rate limits, or what happens if parameters are invalid. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's function. It's front-loaded with the core action and resource, with no redundant information. Every word contributes to understanding the purpose, making it appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a read operation with 2 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover authentication needs, error handling, return format, or behavioral constraints. For a tool in a server with authentication-related siblings (e.g., 'authenticate'), this omission is significant, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantic context beyond the input schema. It mentions '指定されたコンテナ' (specified container), which aligns with the 'containerId' parameter, but doesn't explain the relationship between 'accountId' and 'containerId' or provide usage examples. With 100% schema description coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - get/retrieve) and resource ('ワークスペース一覧' - list of workspaces) with a specific scope ('指定されたコンテナの' - of the specified container). It distinguishes from sibling tools like 'get_workspace' (singular) and 'list_containers' (different resource), though it doesn't explicitly contrast them. The purpose is specific but could be more precise about what a 'workspace' entails in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), compare to siblings like 'get_workspace' for single workspace retrieval, or indicate scenarios where listing workspaces is appropriate. The description only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Update' implies a mutation operation, but the description doesn't specify whether this requires special permissions, what happens on success/failure, whether changes are reversible, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose with zero wasted words. It's appropriately sized for a basic update operation and front-loads the essential information immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 8 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't address behavioral aspects like permissions needed, error conditions, or what the update affects. While concise, it fails to provide the contextual information an agent needs to use this tool effectively and safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain relationships between parameters like accountId/containerId/workspaceId hierarchy, what 'tag type' means, or how 'parameter array' should be structured. With complete schema coverage, baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('update') and resource ('existing tag') in Japanese, making the purpose immediately understandable. It distinguishes itself from sibling tools like 'create_tag' and 'delete_tag' by specifying it's for updating rather than creating or deleting. However, it doesn't specify what aspects of the tag can be updated beyond the general concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing an existing tag), when not to use it, or direct comparisons to sibling tools like 'create_tag' or 'delete_tag'. The agent must infer usage from the tool name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'update' implies a mutation operation, the description doesn't address critical behavioral aspects: whether this requires specific permissions, if changes are reversible, what happens to unspecified fields, error conditions, or rate limits. It mentions what CAN be updated but not HOW the update behaves.
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 appropriately concise - a single sentence that gets straight to the point. It's front-loaded with the core purpose and provides examples of updatable settings. However, the 'etc.' at the end is slightly vague, and the structure could be improved with clearer separation between purpose and capability examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 28 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes a successful update, error responses, side effects, or dependencies between parameters. The agent lacks crucial context about how this operation behaves in practice despite the comprehensive parameter documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 28 parameters thoroughly. The description adds minimal value by mentioning 'filter, autoEventFilter, waitForTags, etc.' as examples of updatable settings, but this doesn't provide semantic context beyond what's in the parameter descriptions. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('update') and resource ('existing trigger'), making the purpose understandable. It distinguishes from siblings like 'create_trigger' by specifying it updates existing triggers rather than creating new ones. However, it doesn't explicitly differentiate from other update tools like 'update_tag' or 'update_variable' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing an existing trigger ID), when-not-to-use scenarios, or how it differs from other update operations. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While '更新します' (updates) implies a mutation, the description doesn't specify permissions required, whether changes are reversible, rate limits, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'updating a variable' entails (e.g., which fields can be modified, side effects), leaving critical behavioral and output details unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 7 parameters (e.g., accountId, variableId, name). The description doesn't add any additional meaning about parameter usage, dependencies, or examples beyond what's in the schema, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '既存の変数を更新します' (Updates an existing variable) clearly states the verb (update) and resource (variable), making the purpose understandable. However, it doesn't differentiate from sibling tools like update_tag or update_trigger, which follow the same pattern for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like create_variable or get_variable. It doesn't mention prerequisites (e.g., needing an existing variable ID) or contextual constraints, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks authentication status but doesn't reveal any behavioral traits—such as whether it's read-only, what data it returns (e.g., user info, expiry), error conditions, or rate limits. For a tool with zero annotation coverage, this lack of detail is a significant gap, though it doesn't contradict anything.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without any fluff or redundancy. It's front-loaded with the core action ('check') and resource ('authentication status'), making it easy to parse. Every word earns its place, achieving optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple status check) but lack of annotations and output schema, the description is incomplete. It doesn't explain what the check entails, what information is returned, or how to interpret results. For a tool that likely returns authentication state (e.g., valid/invalid, user details), more context is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it doesn't introduce any confusion. A baseline of 4 is appropriate as the description is adequate for a parameterless tool, though it could theoretically mention why no inputs are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'check current authentication status' (現在の認証状態を確認します), which is a specific verb ('check') and resource ('authentication status'). It distinguishes itself from siblings like 'authenticate', 'get_auth_url', and 'reset_auth' by focusing on status verification rather than initiation, URL retrieval, or resetting. However, it doesn't explicitly contrast with all siblings, keeping it at 4 instead of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when authentication status checking is needed (e.g., before operations requiring auth), what triggers its use, or how it differs from related tools like 'authenticate' or 'reset_auth'. Without such context, users must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does ('retrieves account list') without describing how it behaves: no information about pagination, sorting, filtering, rate limits, authentication requirements, or what the return format looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple list operation with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is minimally complete but lacks important context. As a list operation with no annotations, it should ideally mention something about the return format or authentication requirements to help the agent understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description doesn't need to add parameter information, and it appropriately doesn't mention any parameters. Baseline for 0 parameters with full schema coverage is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieves/get) and resource ('Google Tag Managerのアカウント一覧' - Google Tag Manager account list), making the purpose understandable. However, it doesn't explicitly differentiate from sibling list tools like list_containers or list_workspaces, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., authentication), context for when listing accounts is appropriate, or comparison to other list tools in the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does ('reset saved authentication information') but doesn't explain what 'reset' entails (e.g., does it delete credentials, revoke tokens, require re-authentication?), potential side effects, or any permissions/rate limits needed. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence in Japanese that directly states the tool's purpose without any fluff or redundancy. It's front-loaded and efficiently conveys the core action, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, no output schema, and no annotations, the description is minimally adequate for a simple reset operation. However, as a mutation tool with no behavioral details (e.g., what 'reset' means, effects on other operations), it lacks completeness for safe and informed use by an AI agent, especially compared to siblings like 'authenticate'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied for zero-parameter tools when the schema is fully covered.
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 states a clear action ('reset') on a specific resource ('saved authentication information'), which is more specific than just restating the tool name. However, it doesn't distinguish this tool from potential sibling alternatives like 'delete_auth' or 'clear_auth', though no such siblings exist in the provided list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication must exist), consequences (e.g., what happens after reset), or related tools like 'authenticate' or 'check_auth_status' from the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description states it 'gets' an OAuth2 authentication URL and that the URL should be accessed to complete authentication, but it doesn't disclose important behavioral traits like whether this initiates a new auth flow, if it requires prior setup, what happens after URL access, rate limits, or error conditions. For a security-related tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just two sentences in Japanese that directly state what the tool does and what to do with its output. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for a simple tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool returns (an OAuth2 authentication URL) and what to do with it (access to complete authentication). However, for an authentication tool in a security context, it should ideally provide more context about the OAuth2 flow, scopes, or how this integrates with other auth tools like 'authenticate' and 'check_auth_status'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage. The description doesn't need to explain parameters since none exist. It appropriately focuses on the tool's purpose without attempting to document non-existent parameters. The baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'OAuth2認証URLを取得します' (Get OAuth2 authentication URL). It specifies the verb ('取得します' - get/obtain) and resource ('OAuth2認証URL' - OAuth2 authentication URL). However, it doesn't explicitly distinguish this from sibling tools like 'authenticate' or 'check_auth_status', which appear to be related authentication tools.
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 provides some usage context: 'このURLにアクセスして認証を完了してください' (Access this URL to complete authentication). This implies when to use the tool - as part of an OAuth2 flow to obtain an authentication URL. However, it doesn't explicitly state when to use this vs. alternatives like 'authenticate' or 'check_auth_status', 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the action ('complete authentication') and usage flow, but lacks details on behavioral traits such as error handling, response format, side effects (e.g., session creation), or security implications. This is a significant gap for an authentication tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, consisting of two sentences that efficiently explain the purpose and usage. Every sentence earns its place by providing essential information without redundancy, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (authentication with OAuth2), lack of annotations, and no output schema, the description is moderately complete. It covers the basic purpose and usage flow but misses key contextual details like expected outcomes, error cases, or integration with other auth tools (e.g., 'check_auth_status'). This leaves gaps for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'code' parameter fully documented as 'OAuth2 authentication code (value after "code=" in the redirect URL).' The description adds minimal value beyond this, only reinforcing the code's source. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'complete authentication using an authentication code.' It specifies the verb ('complete authentication') and resource ('authentication code'), making the function understandable. However, it doesn't explicitly distinguish this from sibling tools like 'get_auth_url' or 'reset_auth' beyond mentioning 'get_auth_url' in usage context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when and how to use this tool: 'Use the authentication code obtained from the redirect URL after accessing the URL from get_auth_url.' It names the prerequisite tool ('get_auth_url') and specifies the source of the code, offering clear context for usage without alternatives needed.
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:

[![GTM-MCP MCP server](https://glama.ai/mcp/servers/ambit1977/GTM-MCP/badges/card.svg)](https://glama.ai/mcp/servers/ambit1977/GTM-MCP)

Score Badge

Copy to your README.md:

[![GTM-MCP MCP server](https://glama.ai/mcp/servers/ambit1977/GTM-MCP/badges/score.svg)](https://glama.ai/mcp/servers/ambit1977/GTM-MCP)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/ambit1977/GTM-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server