GitLab Forum MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the query language syntax and mentions 'Results are permission-aware,' which adds important context about access control. However, it lacks details on error handling, rate limits, or performance characteristics that would enhance transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core purpose. It efficiently packs detailed query syntax into a single sentence, though the dense listing of options might be slightly overwhelming. Every sentence contributes essential information without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of the query language and lack of annotations or output schema, the description does a decent job covering input semantics and behavioral context. However, it doesn't explain the return format (e.g., paginated list structure) or error cases, leaving gaps for a tool with rich filtering capabilities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 parameters. The description adds value by explaining the 'filter' parameter's query language in detail, but it doesn't provide additional meaning for 'page' or 'per_page' beyond what the schema states. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Filter topics with a concise query language.' It specifies the resource (topics) and verb (filter) precisely, and distinguishes it from siblings like discourse_search (which might be broader) and discourse_list_categories/tags (which list rather than filter).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for usage by detailing the query language and filterable attributes, implying it's for complex topic filtering. However, it doesn't explicitly state when to use this tool versus alternatives like discourse_search or discourse_read_topic, which could help differentiate further.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'Get basic user info,' which implies a read-only operation. It doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'basic' includes, leaving significant gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. 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.

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 simple tool with one parameter, the description is incomplete. It doesn't explain what 'basic user info' returns, potential errors, or usage context, leaving the agent under-informed for effective tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it adds no parameter information. The single parameter 'username' is undocumented in both schema and description. Baseline is 3 due to only one parameter, but the description provides no semantic value beyond what the schema name implies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get basic user info' states the action ('Get') and resource ('user info'), but is vague about what 'basic' entails and doesn't differentiate from potential sibling user-related tools (none listed, but could exist). It's not tautological but lacks specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, leaving the agent with no usage direction beyond the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'visible to the current auth context', hinting at permission-based filtering, but lacks details on rate limits, pagination, error handling, or response format. For a read operation with zero annotation coverage, this leaves significant gaps in understanding tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the purpose without waste. It's front-loaded with the core action and includes a relevant constraint ('visible to the current auth context'). Every word earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 simple read operation, the description is incomplete. It lacks details on what the list returns (e.g., format, fields), how results are ordered or limited, and any behavioral nuances. While the tool is simple, the description doesn't provide enough context for reliable agent use beyond the basic action.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, avoiding redundancy. A baseline of 4 is applied since no parameters exist, and the description doesn't attempt to compensate unnecessarily.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('categories'), making the purpose understandable. It specifies 'visible to the current auth context', which adds useful scope. However, it doesn't explicitly differentiate from sibling tools like 'discourse_list_tags' or 'discourse_filter_topics', which could provide similar listing functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal guidance—it implies usage when categories need listing in the current auth context, but offers no explicit when-to-use vs. alternatives (e.g., compared to 'discourse_list_tags' or 'discourse_search'). No exclusions or prerequisites are mentioned, leaving the agent with little direction on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'if enabled,' hinting at a dependency or condition, but doesn't explain what this means (e.g., admin permissions, site configuration). It lacks details on output format, pagination, rate limits, or error handling, which are critical for a list operation with no parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise with a single sentence 'List tags (if enabled).' It's front-loaded with the core action, and there's no wasted text. However, it could be more informative without sacrificing brevity, such as by clarifying the conditional.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 incomplete. It doesn't explain what 'tags' are in this context, how the list is returned, or what 'if enabled' entails. For a tool that might have dependencies or return structured data, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is given as it doesn't need to compensate for any gaps, but it doesn't exceed expectations by providing extra context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List tags (if enabled)' states the basic action (list) and resource (tags), making the purpose understandable. However, it's vague about scope and doesn't differentiate from sibling tools like 'discourse_list_categories' or 'discourse_search' which might also list content. The conditional '(if enabled)' adds some nuance but doesn't specify what 'enabled' refers to.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 sibling tools like 'discourse_list_categories' for listing categories or 'discourse_search' for broader searches, nor does it specify prerequisites or contexts where listing tags is appropriate. The conditional '(if enabled)' implies a dependency but doesn't explain it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'Read a specific post' but doesn't clarify if this is a safe read operation, what permissions are required, what data is returned (e.g., content, author, timestamps), or any rate limits. This leaves significant gaps for a tool that likely interacts with user data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence, 'Read a specific post.', which is front-loaded and wastes no words. Every part of the sentence directly contributes to the tool's purpose, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a read operation with 1 parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety or permissions, parameter details, or return values, leaving the agent with insufficient context to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, and the description adds no meaning beyond what the schema provides. It doesn't explain what 'post_id' represents (e.g., a numeric identifier, where to find it, or its format), failing to compensate for the lack of schema documentation. With 1 parameter, this is a notable oversight.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Read a specific post' clearly states the verb ('Read') and resource ('post'), but it's vague about what 'read' entails (e.g., retrieving content, metadata, or both) and doesn't distinguish it from sibling tools like 'discourse_read_topic'. It avoids tautology by not merely restating the name/title.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 a valid post_id), exclusions, or comparisons to siblings like 'discourse_read_topic' or 'discourse_search', leaving the agent to 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only operation but doesn't disclose authentication needs, rate limits, error conditions, or what happens if parameters are invalid. The phrase 'first N posts' hints at pagination but lacks details on ordering or truncation behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality. Every word earns its place without redundancy, making it easy to parse quickly. No extraneous details or verbose explanations are included.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a 3-parameter tool with no annotations and no output schema, the description is insufficient. It doesn't explain return values, error handling, or important constraints like what 'metadata' includes or how posts are ordered. For a read operation with multiple 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low at 33%, with only 'start_post_number' described. The description adds value by clarifying that 'first N posts' corresponds to the 'post_limit' parameter, but doesn't explain 'topic_id' semantics or default behaviors. It partially compensates for the coverage gap but leaves key parameters underspecified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Read') and resource ('topic metadata and first N posts'), making the purpose understandable. It distinguishes from siblings like discourse_read_post (which reads a single post) and discourse_filter_topics (which lists topics). However, it doesn't explicitly mention what 'metadata' includes or how it differs from full topic content, keeping it from a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 to choose discourse_read_topic over discourse_read_post for post content, or how it complements discourse_filter_topics for topic discovery. There's no context about prerequisites or typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. 'Search site content' implies a read-only operation, but it doesn't specify permissions needed, rate limits, pagination behavior, or what 'with_private' entails (e.g., access to private content). For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with just three words: 'Search site content.' It's front-loaded and wastes no space, making it easy to parse. Every word contributes directly to the purpose, earning its place without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a search tool with 3 parameters), no annotations, no output schema, and low schema coverage (33%), the description is incomplete. It doesn't explain return values, error conditions, or how results are structured. For a tool that likely returns search results, more context is needed to use it effectively, making it inadequate for the given context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 33% (only 'query' has a description), so the description must compensate but doesn't. It mentions no parameters, leaving 'with_private' and 'max_results' undocumented. Since schema coverage is low (<50%), the baseline isn't met, but the description adds no value beyond the schema. However, with 3 parameters and minimal schema info, it's not entirely inadequate, warranting a middle score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Search site content' clearly states the verb (search) and resource (site content), but it's vague about what 'site content' specifically refers to. It doesn't distinguish this tool from potential siblings like 'discourse_filter_topics' or 'discourse_read_post', which might also involve content retrieval. The purpose is understandable but lacks specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'discourse_filter_topics' and 'discourse_read_post' available, there's no indication of whether this is for general searches, filtered searches, or specific content types. No exclusions, prerequisites, or context for usage are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'validate and select' but doesn't disclose behavioral traits such as what validation entails (e.g., checking site accessibility, permissions), whether this persists across sessions, or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence: 'Validate and select a Discourse site for subsequent tool calls.' It is front-loaded with the core purpose and includes essential context without any wasted words, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It states the purpose and usage but lacks details on validation behavior or output. Without annotations or an output schema, more context on what 'select' entails (e.g., returns a site ID or confirmation) would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'site' parameter documented as 'Base URL of the Discourse site.' The description doesn't add meaning beyond this, as it doesn't clarify URL format requirements or validation specifics. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Validate and select a Discourse site for subsequent tool calls.' It specifies the action (validate and select) and the resource (Discourse site). However, it doesn't explicitly differentiate from siblings like 'discourse_filter_topics' or 'discourse_list_categories', which operate on already-selected sites rather than selecting one.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'for subsequent tool calls.' This indicates when to use it (before other operations that require a site context) and implies alternatives (other tools likely require this selection first). It effectively sets the context for its role in the toolchain.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.