Asana

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

Annotations are empty, so description carries full burden. It discloses that the tool returns specific fields (GID, name, permalink) and implies creation, but does not mention required permissions, side effects (e.g., notifications), or idempotency. Minimal but not misleading.

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?

Description is two sentences and to the point, front-loading the action and return value. No wasted words. Could be slightly improved by adding a usage hint, but remains efficient.

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 has 6 parameters, no output schema, and no annotations, the description is adequate but not complete. It states what is returned but does not cover error conditions, partial success, or limits. For a creation tool, more context (e.g., whether workspace is required) would be helpful.

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 coverage is 100%, so the description adds minimal value beyond the schema. It does not explain parameter semantics further (e.g., that projects can be comma-separated, or that assignee can be email). Baseline of 3 is appropriate.

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 it creates a task in Asana and specifies what is returned (GID, name, permalink URL). This is a specific verb+resource, and distinguishes it from sibling tools like asana_get_task and asana_list_tasks.

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 does not explicitly state when to use this tool versus alternatives. It implies creation but offers no guidance on prerequisites or conditions (e.g., workspace required vs auto-resolved). No exclusions or when-not-to-use are provided.

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 provided, but the description explicitly states it returns full task details including specific fields, which informs the agent about the return content. It does not mention any side effects or access restrictions, but for a read operation this is acceptable.

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?

Two sentences that are efficient and front-loaded with the core action. Could be slightly more concise by removing redundant phrase 'by its GID' but overall good.

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 low complexity (1 parameter, no output schema), the description adequately covers the purpose and return content. It lacks guidance on error cases or pagination, but those are not critical for a simple get operation.

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 coverage is 100% with the task_gid parameter already described. The description does not add additional meaning beyond what the schema provides, so baseline 3 is appropriate.

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 it retrieves a single task by its GID and lists the full details returned, distinguishing it from siblings like asana_search_tasks and asana_list_tasks which return multiple tasks.

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 implies usage when a specific task is needed by GID, but does not explicitly contrast with siblings or mention when not to use 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?

Annotations are empty, so the description carries full burden. It states the tool is read-only (list), but does not disclose potential behavior like whether it only returns active projects, or any rate limits. Given no annotations, a 3 is adequate for a straightforward list 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 two sentences, no fluff. All information is front-loaded. Every word adds value.

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 low complexity (2 params, no required, no output schema), the description is reasonably complete. It lists key return fields, but could mention pagination behavior or default ordering.

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 coverage is 100% (both parameters documented), so baseline is 3. The description adds no further meaning beyond what the schema already provides (e.g., no format constraints or usage tips).

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'), resource ('projects in an Asana workspace'), and key return fields ('project GID, name, and archived status'). However, it does not differentiate from sibling tools like asana_list_tasks or asana_search_tasks, which also list resources.

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 such as asana_list_tasks or asana_search_tasks. There is no mention of prerequisites, pagination, or when to specify workspace versus relying on auto-resolution.

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?

Annotations are empty, so the description carries the full burden. It states it returns specific fields and accepts parameters, but does not disclose pagination behavior, rate limits, or authentication needs. This is adequate but minimal.

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

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

The description is a single concise sentence with a follow-up list of return fields. Every word is useful, no fluff.

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?

The tool is relatively simple with 3 parameters and no output schema. The description explains return fields adequately but lacks information about pagination, ordering, or error handling.

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 baseline is 3. The description does not add additional meaning beyond what the schema provides for parameters. It does not explain the format of 'completed_since' or 'limit' further.

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 the resource 'tasks in an Asana project'. It lists the specific fields returned, distinguishing it from sibling tools like asana_create_task or asana_search_tasks.

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 implies usage context but does not explicitly state when to use this tool versus alternatives like asana_search_tasks. No exclusions or conditions are provided.

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 burden. It states it lists workspaces accessible to the authenticated user, implying a read-only operation. However, it does not disclose rate limits, pagination behavior, or potential filtering limitations.

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?

Two concise sentences, front-loaded with the key action and resource. Every sentence adds value with no redundancy.

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 zero parameters, no output schema, and simple list functionality, the description is complete enough. It explains the purpose and what the result contains. Additional details like authentication context are implicit.

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 tool has no parameters, so the input schema is empty with 100% coverage. The description adds meaning by stating what the tool returns (workspace GIDs), which helps the agent understand the output.

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 action (list), resource (workspaces), and context (accessible to authenticated user). It also explicitly mentions the purpose (discover workspace GIDs), which distinguishes it from sibling tools like asana_list_projects.

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 implies usage: use to discover workspace GIDs, but does not provide when-not-to-use or mention alternatives. Since it's a straightforward list tool with no required parameters, the guidance is adequate but minimal.

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. It correctly states it is a search (read) operation, but does not mention whether it respects rate limits, pagination behavior beyond the limit parameter, or any other side effects. The description is adequate but not exhaustive.

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 sentence that efficiently conveys purpose and return fields. It is front-loaded with the action and resource. No unnecessary words.

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 has a straightforward search function with a clear schema and no output schema, the description is mostly sufficient. However, it lacks guidance on when to use this vs other task tools, and does not mention any constraints like workspace auto-resolution behavior.

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 already provides descriptions for all three parameters (100% coverage). The description adds minimal value by mentioning return fields, but does not elaborate on the parameters beyond what is in the schema. Baseline 3 is appropriate.

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 searches for tasks by text and lists the return fields (GID, name, completed status, assignee). It distinguishes from siblings like asana_list_tasks (which lists all tasks) and asana_get_task (single task retrieval), though it could explicitly name the distinction.

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 implies use when text search is needed, but does not specify when not to use it or contrast with alternatives. For example, it does not mention that asana_list_tasks is for listing all tasks in a project or that asana_get_task is for fetching a single task by GID.

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?

The description discloses that Pipeworx 'picks the right tool, fills the arguments, and returns the result,' explaining internal behavior beyond what annotations (none provided) offer. This is transparent about its autonomous selection and invocation of other tools.

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 concise (three sentences) and front-loaded with the core purpose. Every sentence provides useful information: what it does, how it works, and examples.

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 simple input schema (one string parameter), no output schema, and no annotations, the description is complete. It explains the autonomous behavior and provides clear examples, fully satisfying the need for 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 coverage is 100% for the single parameter, which already has a clear description in the schema. The description adds value by explaining the natural language nature and giving examples, but doesn't add new semantic details beyond what the schema provides.

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 accepts plain English questions and returns answers using the best data source, distinguishing it from sibling tools that are specific to Asana or memory operations. The verb 'ask' and resource 'Pipeworx' are specific, and examples clarify scope.

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 explicitly says 'no need to browse tools or learn schemas' and provides examples of what to ask, indicating broad use cases. It does not explicitly say when not to use it, but the context of sibling tools (Asana-specific, memory) implies this is the general query tool.

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. It indicates the tool searches and returns results, which is straightforward. However, it does not disclose details like whether it modifies state, how it handles empty queries, or if there are authentication requirements. It is adequate but lacks depth beyond the basic search 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 three sentences long, with the first sentence immediately stating the purpose. Each sentence is essential: first states what it does, second specifies return type, third gives usage context. No fluff or redundant information.

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 has a simple purpose (search catalog), no output schema, and annotations are missing, the description covers the core functionality well. It explains the input format and return type (names and descriptions). It could mention that results are ranked by relevance or that query supports natural language, but the examples provided mitigate this. Completeness is high for a simple search tool.

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, so parameters 'query' and 'limit' are already well-documented. The description adds context by explaining that 'query' should be a 'natural language description' and provides examples, which goes beyond the schema. This adds meaningful value, justifying a 4.

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 'Search' and the resource 'Pipeworx tool catalog', and specifies that it returns 'the most relevant tools with names and descriptions'. It distinguishes itself by being the tool to call first when needing to find the right tool among many, setting it apart from sibling tools like asana_create_task or ask_pipeworx.

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 explicitly says 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This gives clear when-to-use guidance and implies it should be used before invoking other specific tools, providing a strong usage guideline.

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 provided, so description must disclose behavioral traits. It states 'delete' implying irreversible action, but does not confirm if the operation is destructive or if it has side effects. Lacks details on authorization needs or error handling.

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?

Extremely concise: single sentence with no wasted words. Front-loads the core action and resource.

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 low complexity (1 param, no nested objects, no output schema), the description is too minimal. It lacks behavioral details like confirmation of deletion or return value (e.g., success status). Completeness is inadequate.

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 coverage is 100% with a description for the 'key' parameter. The tool description does not add meaning beyond what the schema provides, but the schema is sufficient. Baseline 3 is appropriate.

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 action (delete) and the resource (a stored memory by key). It is distinct from sibling tools like recall and remember, which handle retrieval and storage.

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 on when to use this tool vs alternatives like recall or remember. Does not specify prerequisites (e.g., memory must exist) or warn about irreversible deletion.

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, the description carries the full burden. It states that the tool retrieves or lists memories, but does not disclose details such as whether retrieval is destructive, session-persistence behavior, or any side effects. It adds value beyond the schema by explaining the optionality of 'key', but lacks depth.

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 two sentences, each serving a distinct purpose: first explaining the core action, second providing context for use. No wasted words.

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 a simple tool with one optional parameter, the description is largely complete. It explains both modes (specific retrieval vs listing all). However, it does not describe the return format or any error cases, which would be helpful.

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% (the 'key' parameter is described in the schema). The description adds meaning by explaining that omitting key lists all memories, which is not in the schema. This is adequate but does not exceed baseline.

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 uses specific verbs ('retrieve', 'list') and clearly identifies the resource ('stored memory by key'). It distinguishes itself from siblings like 'remember' (store) and 'forget' (delete), making its purpose unambiguous.

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 when to use this tool ('retrieve context you saved earlier'). It implicitly excludes listing all memories by noting 'omit key to list all keys', but does not explicitly mention when not to use it or alternatives.

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?

The description discloses behavioral traits such as persistence differences for authenticated vs anonymous sessions and a 24-hour expiration for anonymous sessions. Since no annotations are provided, the description carries the full burden and does well.

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?

Three sentences, front-loaded with the core action, then usage guidelines, then persistence details. Every sentence adds value; no wasted words.

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 (2 params, no output schema, no nested objects), the description fully covers purpose, usage, and behavioral traits. Complete for this 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?

Input schema has 100% coverage with good descriptions for both parameters. The description adds some context about the type of values (findings, addresses, preferences, notes) but not much beyond what the schema provides.

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 action (store a key-value pair), the resource (session memory), and the purpose (save intermediate findings, user preferences, context across tool calls). It distinguishes from siblings by naming 'forget' and 'recall' as related tools.

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 explains when to use it (to save intermediate findings, preferences, context) and provides context about persistence (authenticated vs anonymous). However, it does not explicitly say when not to use it or mention alternatives beyond the sibling list.

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