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

No annotations are provided, so the description must cover behavioral traits. It mentions data structure matching and auto-generated keys, but lacks details on side effects, error handling (e.g., duplicate keys), permissions, or idempotency.

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, front-loaded with the core action, and contains no unnecessary words. Every sentence 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?

The description provides adequate context for a simple creation tool, but lacks details on return values, behavior when a key is provided that already exists, and error conditions. No output schema exists to fill these gaps.

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%, but the description adds meaningful context: 'data' must match the data store's structure, and 'key' is optional with auto-generation. This goes beyond the schema's basic descriptions.

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 'Add a new record to a Make.com data store', specifying the verb and resource. It distinguishes from sibling tools like delete, update, and get by focusing on creation.

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 for adding records but does not explicitly state when to use this tool versus alternatives (e.g., update_record). Sibling names provide context, but no direct guidance.

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 full burden and does well: it discloses that the operation does not affect the live scenario, explains that states=true copies execution state like last trigger position, and default false gives a clean copy. It also mentions the fallback logic for team/org IDs. However, it does not disclose potential side effects (e.g., whether a new scenario ID is returned, costs, or permission requirements), so it is not fully 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 two sentences with no wasted words. The first sentence establishes the primary purpose and safety context; the second covers the important parameter behaviors. It is front-loaded with the essential information and remains highly readable.

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 (5 params, no output schema, no annotations), the description provides sufficient context: purpose, safe usage, fallback logic, and state-copying behavior. It lacks some details like the return value or permission prerequisites, but for the likely use case (cloning a scenario), it is reasonably complete.

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%, and the schema already explains states, name, scenario_id, and the fallback behavior for team_id/organization_id. The description repeats some of this (e.g., states default, fallbacks) without adding new detail. Thus the description adds no significant semantic value beyond the schema, meeting the baseline of 3.

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 a specific verb 'Clone' and identifies the resource 'Make.com scenario' and the result 'a new one with a given name.' It clearly differentiates from siblings by positioning cloning as 'the safe way to test structural changes' and explicitly references make_update_blueprint as an alternative, making the 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 explicitly states when to use this tool: as a safe method to test structural changes before make_update_blueprint, without touching the live scenario. It also clarifies fallback behavior for team_id/organization_id, giving clear context for when those optional parameters are needed. No alternatives are excluded, but the usage context is strong and actionable.

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 transparency burden. It discloses the selective nature of deletion ('ONLY those are removed') and the intentional safety guardrail against bulk deletion. It does not mention potential side effects or return behavior, but for a delete tool the key behavioral traits are clearly stated.

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, front-loaded with the primary purpose, and every sentence adds value. The safety exclusion and id source are compressed into a compact, readable structure without 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?

For a simple 2-parameter deletion tool, the description covers all essential context: what it does, how to obtain the ids, and the limiting constraint. No output schema is present, but the behavior is simple enough that return values are not critical. The description is self-sufficient.

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 parameters are already described. The description adds value beyond the schema by explaining that 'dlq_ids' must come from 'make_list_incomplete' and by reinforcing that only the passed ids are removed. This enriches the semantic understanding of the parameters.

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 states a specific verb ('Delete') and resource ('specific incomplete/failed execution(s) (DLQ items)'), with clear qualifiers: 'by id' and 'from a given scenario'. It also explicitly distinguishes itself from bulk deletion by stating that deleting ALL incomplete executions is intentionally unsupported, which sets it apart from a generic 'delete' tool.

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 notes when to use this tool (for specific DLQ items) and when not (not for deleting all incomplete executions), with a safety rationale. It also references a sibling tool ('make_list_incomplete') as the source for the exact ids, providing practical usage context.

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 adds value by clarifying the exact scope of deletion and the safety limitation. However, it lacks details on error behavior or idempotency.

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 well-structured sentences with front-loaded verb and resource, zero wasted words. Concisely conveys core purpose and constraint.

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?

Covers key behavioral constraints but does not describe return value or error handling, which would be desirable given no output schema.

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% and the description effectively paraphrases the schema's parameter descriptions without adding new semantic details beyond the key constraint.

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?

Explicitly states 'Delete SPECIFIC record(s) from a Make.com data store by key(s)', using a specific verb and resource. The clarification that deleting all records is not supported distinguishes it from potential bulk operations.

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?

Clearly indicates usage for deleting specific records only and explicitly says deleting all records is not supported, providing a clear usage boundary. However, it does not name alternative tools for bulk 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 explicitly states the tool retrieves a JSON structure equivalent to Make's editor canvas, which conveys that it is a read operation and what the output represents. It does not mention rate limits, auth, or potential size, but for a simple GET-style tool this is acceptable and goes beyond a bare 'get' statement.

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, front-loaded with the core action, and uses two sentences to convey both what the tool returns and its practical use case. No word is wasted, and the canvas analogy effectively sets expectations without digression.

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?

For a simple get tool with one parameter and no output schema, the description fully explains what the return value contains (modules, parameters, filters, connections) and its relationship to Make's editor. It provides enough context for an agent to decide when to invoke it and what to expect, without needing additional structured fields.

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 only parameter, scenario_id, is properly described as 'The scenario ID' in the schema. The tool description does not add any extra meaning about the parameter (e.g., how to locate it), so the baseline of 3 applies.

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 a specific verb ('Get') and resource ('full blueprint of a Make.com scenario'), and goes beyond a simple label by detailing what the blueprint contains (modules, parameters, filters, connections). It clearly distinguishes this from sibling tools like make_get_scenario or make_update_blueprint by focusing on the complete module graph as rendered by Make's own editor.

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 the tool: 'Use it to inspect exact module configuration without asking the user for screenshots.' This implies a specific use case (inspecting configuration) but does not explicitly name alternative tools or exclusions, so it stops short of a 5.

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 explains that the tool retrieves historical input/output values behind a failed execution, which is useful behavioral context. However, it does not mention whether the operation is read-only, possible response size, or any permissions needed. This is a minor gap for a 'get' tool.

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 tightly written sentences that front-load the main purpose, provide a concrete use case, and cross-reference the sibling tool. Every phrase earns its place with zero 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?

Given the simple tool (one parameter, no output schema) and sufficient annotations absence, the description covers what the tool does, why to use it, and how to get the ID. It doesn't describe the return structure in detail, but for this level of complexity the guidance is largely complete.

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%: the single parameter dlq_id is already described as 'The incomplete-execution (DLQ) id from make_list_incomplete'. The description reiterates this context, but adds no new syntax or format details. Baseline 3 is appropriate given the schema fully documents the parameter.

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?

Clearly states the verb 'Get' and the specific resource: the data bundle being processed at the moment of a scenario execution failure. It distinguishes itself from sibling tools by referencing make_list_incomplete and emphasizing the actual input/output values, not just execution status or error messages.

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?

Provides explicit context for when to use the tool ('real diagnosis instead of guessing from error messages alone') and implies the prerequisite of calling make_list_incomplete to obtain the dlq_id. While no formal alternative or exclusion is given, the guidance is clear and practically useful.

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 is the sole source. It states the tool returns details but does not disclose whether it is read-only, authentication requirements, rate limits, or side effects. For a get operation, 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 sentence that front-loads the purpose and includes key details. Every word contributes value, with no unnecessary content.

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?

For a simple retrieval tool with no output schema, the description lists return fields (status, operations, etc.) and required IDs. It is mostly complete, though could briefly note the tool is read-only.

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 baseline 3. The description adds context by linking execution_id to make_list_executions, but does not provide additional semantic detail beyond the schema.

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 'Get' and resource 'execution/log', specifies the details returned (status, operations, duration, error info), and differentiates from siblings like make_list_executions and make_get_scenario.

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?

It explicitly mentions that scenario_id and execution_id come from make_list_executions, providing clear context. However, it does not include when not to use this tool or specify 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.

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

Without annotations, the description carries full responsibility for behavioral disclosure. It reveals that results are capped with a default of 100 and that each record has a 'key' and 'data' object. However, it does not mention pagination, ordering, or error conditions, which would further enhance transparency for a read 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 long, with the first sentence front-loading the core purpose and the second adding key details about record structure and limits. Every word serves a purpose, and there is no redundancy or 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 description covers the basic return structure (key and data) and the limit behavior, but lacks details about the response format (e.g., array vs. object), error handling, or pagination. Given the tool's simplicity and lack of output schema, the description is adequate but could be more complete.

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 baseline is 3. The description adds no meaningful new information about parameters beyond what the schema provides. It repeats the limit default but does not clarify the data_store_id format or provide additional 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 clearly states the verb 'List' and the resource 'records in a Make.com data store', making the purpose explicit. It also distinguishes from sibling tools like make_add_record and make_delete_record by focusing on listing. The additional detail about records having a 'key' and 'data' object further clarifies what is returned.

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 provide any guidance on when to use this tool versus alternatives. It merely states what the tool does, leaving the agent to infer usage context from the sibling list. No explicit 'when-not-to-use' or alternative tool references are given.

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 the description carries full burden. It describes the operation as 'get full details' (read-only), but does not disclose authentication needs, rate limits, or any side effects. For a simple get, this is adequate 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?

Single sentence that is front-loaded and conveys the essential purpose and scope without unnecessary words. Every part of the sentence provides 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?

For a simple get tool with one parameter and no output schema, the description covers the main purpose and lists example fields returned. Could hint at response structure, but overall sufficiently complete for an AI to understand the tool's function.

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?

With 100% schema coverage (scenario_id described as 'The scenario ID'), the description adds no additional context beyond the schema. No format or source guidance is provided, so baseline 3 applies.

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?

Description uses specific verb 'get' and resource 'scenario', indicating retrieval of full details including status, scheduling, team, description, etc. It clearly distinguishes from list tools and execution-specific tools among siblings.

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 states the tool is for getting details by ID, implying prerequisite knowledge of the ID. It does not explicitly mention when not to use or alternatives, but the context is clear given sibling tools.

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 full responsibility. It discloses that the tool reads connections and returns id, name, and app, with team_id fallback. However, it does not mention potential limitations like pagination, rate limits, or whether the operation requires any authentication beyond defaults.

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 with no wasted words. It efficiently conveys the action, result, and important fallback logic, making it 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 simplicity (no output schema, one optional parameter), the description is largely complete. It explains what is returned and the fallback behavior. Minor omissions include any mention of pagination or ordering, but these are less critical for this type of 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% coverage for the single parameter team_id. The description adds value by explaining the fallback behavior (configured team or only team), which is not present in the schema. This goes beyond the bare parameter description.

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 lists Make.com connections (linked app accounts) for a team, providing id, name, and app. It differentiates from sibling list tools by specifying the resource type and return fields.

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 indicates the tool is useful for seeing which integrations are connected, giving a clear use case. It also explains the fallback behavior for team_id. However, it does not explicitly compare to alternatives or state when not to use this tool.

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

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

With no annotations, the description carries full burden. It indicates a read-only listing operation (via 'List') and explains parameter behavior (team_id fallback, limit default). It does not disclose rate limits or side effects, but for a list tool this is adequate.

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 that efficiently conveys purpose, resource context, and parameter behavior without 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?

For a simple list tool with 2 optional parameters and no output schema, the description adequately covers what it returns, team_id fallback, and limit default. It could mention pagination or that it lists all stores, but overall it is sufficient.

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 baseline is 3. The description adds value by explaining the team_id fallback and limit default, but does not provide deep semantic details beyond what the schema already includes.

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 'Make.com data stores', explains it's a lightweight database, and distinguishes itself from sibling tools (e.g., make_get_records) by specifying it returns id, name, and record info.

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 for listing data stores but does not explicitly state when to use or when not to use, nor does it reference alternative tools. The team_id fallback is mentioned, providing some context.

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 burden of behavioral disclosure. It mentions listing newest first and showing success/failure, but does not explicitly state that it is read-only, describe error handling, pagination, or rate limits. The description adequately conveys core read behavior 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 adding value. It is front-loaded with the main action and immediately provides key details. No 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 absence of output schema, the description explains what is shown (success/failure and time) but does not specify the exact return format or pagination details. It is mostly complete for a list tool but omits mention of error cases or how to handle large result sets.

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 description adds meaning beyond the schema by explaining the status filter values (1=success, 2=warning, 3=error) and the ordering 'newest first', which is not in the schema. The limit parameter is already well-described in the schema.

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', the resource 'execution history (logs)' of a Make.com scenario, the ordering 'newest first', and what it shows (success/fail and time). It distinguishes from sibling tools like make_get_execution which likely retrieves a single execution detail.

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 for viewing execution history with optional status filtering, but does not explicitly state when to use this tool versus alternatives like make_get_execution, nor does it discuss when not to use it or prerequisites.

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 full responsibility. It does not disclose whether the operation is read-only, destructive, or has any side effects, rate limits, or authentication requirements. While listing is typically safe, the description should explicitly state its read-only nature.

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, no wasted words. Essential information (action, output, parameter behavior, sibling reference) is front-loaded and efficiently communicated.

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?

For a list tool with no output schema, the description adequately covers the return fields and references a sibling tool. The parameter explanation is sufficient. It could mention if pagination exists or if it's limited, but overall it is complete for its complexity.

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 one parameter with 100% description coverage. The description adds context about the fallback behavior, which is consistent with the schema. However, it does not provide additional details beyond what the schema already conveys. 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 'list', the resource 'webhooks for a team', and specifies the returned fields (id, name, webhook URL). It also differentiates this tool from the sibling 'make_trigger_webhook' by noting the URL is used by that tool. No ambiguity.

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 that the output includes the webhook URL used by make_trigger_webhook, implying a use case. It also clarifies the fallback behavior for team_id. However, it does not explicitly state when not to use this tool or mention alternative tools for similar purposes.

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 carries burden. It describes the tool as listing errored executions but does not disclose pagination, rate limits, auth needs, or return structure. Adequate for a simple read 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?

Two sentences with no redundancy. Front-loaded with verb and resource, immediately clear. Every sentence earns its place.

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?

For a simple list tool with 2 parameters and no output schema, description provides sufficient context: what is listed, condition, and usage hint. Lacks mention of return fields but acceptable.

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 descriptions for both parameters. Description adds no additional parameter-specific information beyond schema, so baseline score 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?

Clearly states it lists incomplete/failed executions (DLQ) of a Make.com scenario, specifying these are errored runs waiting. Distinguishes from siblings like make_list_executions.

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?

States 'Use this before retrying' giving explicit usage context. Lacks explicit when-not-to-use but purpose is specific enough to differentiate from 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?

No annotations provided, so description carries full burden. It states returns 'id + name' but lacks details on pagination, rate limits, or authentication. Adequate for a simple read-only list tool.

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

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

Two concise sentences: first states action and resource, second gives usage hint. 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 zero parameters, no output schema, and low complexity, the description fully covers what the tool does, what it returns, and when to use it.

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?

No parameters exist, so baseline is 4. Description does not add parameter information, but none is needed.

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?

Clearly states 'List all Make.com organizations the API token has access to', specifying verb and resource. Distinguishes from sibling tools which deal with executions, scenarios, teams, etc.

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?

Explicitly advises 'Use this first if you don't know the organization_id', providing clear context for when to use this tool before others that require an organization ID.

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. Description mentions result capping and fallback behavior. Does not explicitly state read-only nature or authentication needs, but implies non-destructive listing.

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 clear, efficient sentences. Every sentence adds value without 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?

Covers key aspects: what it lists, filtering options, pagination awareness (capped). No output schema, but response indicator is mentioned. Adequate for a list 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?

Schema coverage is 100% so baseline 3. Description adds context on fallback and 'capped' indicator, but not significantly beyond schema descriptions.

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?

Clearly states 'List Make.com scenarios (automations) for a team or organization.' Specific verb+resource+scope. Differentiates from siblings like make_get_scenario (single) and make_list_executions.

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?

Provides guidance on providing team_id or organization_id, fallback behavior, and active_only parameter. Does not explicitly mention when not to use, but context is clear given siblings.

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 full burden. It discloses basic behavior (lists id+name, parameter fallback) but lacks details on side effects, authentication, rate limits, or response format. Minimal but adequate.

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, no redundancy. Every word adds value, including the cross-reference to make_list_scenarios.

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 description covers purpose, parameter behavior, and a sibling link. No output schema exists, but the tool is simple. Missing pagination or ordering details, but likely sufficient for an AI agent.

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 mostly restates the schema's description ('optional; falls back to configured MAKE_ORG_ID') without adding significant new meaning.

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) and resource (teams inside a Make.com organization). It also specifies the output fields (id + name) and links to a sibling tool (make_list_scenarios), distinguishing it from other list 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 the tool (to list teams) and provides guidance on the optional organization_id parameter (fallback behavior). However, it does not explicitly exclude cases or mention alternative tools.

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 opening in default browser but does not disclose potential limitations (e.g., requires browser, headless environments). For a simple action, it is adequately transparent but could improve.

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, clear sentence (18 words) with no wasted words. It is well-structured and front-loaded.

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 simplicity of the tool and the presence of many sibling tools, the description adequately covers the tool's purpose. No output schema is needed, but a brief note on when to use this over API-based tools would enhance 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?

Schema coverage is 100% and the description adds value by specifying the URL type ('Make.com URL, e.g., scenario editor link'), which goes beyond the schema's generic 'The URL to open'.

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 (open URL in browser), the resource (Make.com URL), and provides an example (scenario editor link). It distinguishes itself from sibling tools that fetch data or control scenarios.

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 (opening UI links) but does not explicitly state when to use or not use this tool, nor does it mention alternatives among siblings.

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 states the tool re-runs a failed execution, implying mutation, but does not detail side effects, idempotency, permissions required, or failure modes. The description is too sparse to adequately inform an agent about behavior beyond the basic action.

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: two short sentences with no unnecessary words. It front-loads the key information (verb + resource) and then emphasizes the re-run nature. Every sentence is essential.

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 only one parameter, no output schema, and the description explains the source of the id, it covers the basics. However, it lacks information about expected output, error handling, or success/failure indicators, which would be helpful for a tool that re-runs executions. It is adequate but not thorough.

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 only parameter, dlq_id, is described as 'The incomplete-execution (DLQ) id from make_list_incomplete'). The description adds context that the id is from make_list_incomplete, but this is already present in the schema. Baseline 3 is appropriate since the description provides minimal additional meaning beyond the schema.

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 a specific verb 'Retry' and clearly identifies the resource as 'incomplete/failed execution (DLQ item)'. It distinguishes from siblings by referencing make_list_incomplete as the source of the id, and explicitly states 'This RE-RUNS the failed execution', leaving no ambiguity.

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 that the id must come from make_list_incomplete, providing a prerequisite. However, it does not explicitly state when to use this tool versus alternatives (e.g., make_run_scenario), nor does it mention when not to use it. The guidance is implicit rather than explicit.

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

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

Discloses wait behavior, timeout (~40s), fire-and-forget mode, and error condition. No annotations provided, so description covers key behaviors well, though lacks details like rate limits or idempotency.

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 about 5 sentences, front-loaded with main action. Each sentence adds value, though could be slightly more concise.

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?

Covers essential usage and return behavior, but lacks description of output format (no output schema) and what happens with invalid scenario_id. Adequate for a moderate complexity 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?

Schema coverage is 100%, so baseline is 3. Description adds meaning beyond schema by explaining the wait parameter's effect on return value and the data parameter's conditional relevance.

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 runs a Make.com scenario on demand. It distinguishes from siblings like make_start_scenario by noting the scenario must be active, implying this tool is for execution not activation.

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?

Explicitly states when to use (on demand) and when not (scenario must be active), with direct reference to make_start_scenario for activation. Also explains wait parameter options and data parameter relevance.

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 carries full burden. It indicates a state change (activation) but does not disclose side effects, reversibility, ownership requirements, or impact on existing executions.

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?

Single clear sentence with 13 words, no redundancy, front-loaded action. Every word earns its place.

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?

With no output schema or annotations, description lacks return value details, error conditions, or usage context relative to siblings. Does not help an agent decide between make_start_scenario and make_run_scenario.

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 single parameter described as 'The scenario ID to activate'. Description adds no further detail beyond the schema's description, achieving the baseline for full 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?

Description clearly states the tool activates a Make.com scenario to run on its schedule or trigger, using a specific verb and resource. It distinguishes from siblings like make_run_scenario which likely triggers immediate execution.

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 explicit when-to-use or when-not-to-use guidance. The description does not contrast with sibling tools like make_run_scenario or mention prerequisites 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?

No annotations are provided, so the description carries the full burden. It clearly states the effect (turns off the scenario), but does not disclose whether currently running executions are affected, if the action is reversible, or any permission requirements. The description is adequate but minimal for a simple state change.

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?

A single sentence that is front-loaded and efficient, containing no extraneous 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 (one parameter, no output schema), the description covers the essential purpose. It does not explain return behavior or error cases, but for a straightforward toggle action, it is sufficiently complete.

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 baseline is 3. The description does not add extra meaning for the one parameter beyond what is in the schema (the scenario ID). No additional context on format or how to obtain the ID is provided.

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 a specific verb ('Deactivate') and resource ('scenario'), clearly stating the tool's function. It distinguishes from siblings like make_start_scenario which performs the opposite action.

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 when to use (to stop a scenario from running on schedule/trigger) but does not provide explicit guidance on when not to use or mention alternatives like 'make_run_scenario' for one-time execution. No prerequisites or conditions are stated.

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?

Discloses re-checking credentials and return of 'verified' status. No annotations provided, so description carries burden; it adequately describes the behavior without contradictions.

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?

Single, front-loaded sentence with no unnecessary words. Every part adds meaning.

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?

Simple tool with one param and no output schema; description fully explains purpose, behavior, and return. No gaps.

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?

Single parameter is fully described in schema (100% coverage). Description adds value by hinting at source function (make_list_connections).

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?

Clearly states the tool verifies a Make.com connection's validity using specific verb 'verify' and resource 'connection'. Distinguishes from siblings like make_list_connections which list connections without testing.

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?

Implied usage for checking connection validity before operations, but no explicit when-not-to-use or alternatives. Context from siblings helps differentiate.

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 the description carries the full burden. It states the action 'FIRES the scenario for real' indicating mutation, but lacks details on rate limits, side effects, or error handling. Adequate but not rich.

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

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

Two sentences with no wasted words. The main action is front-loaded, and the optional data parameter is clarified efficiently.

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, zero output schema, and no annotations, the description covers the essential context: source of URL, action, and parameter overload. A mention of response behavior would improve completeness, but it is nearly sufficient.

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%, and the description repeats the schema's parameter descriptions almost verbatim. No additional meaning is added beyond the schema, meeting the baseline of 3.

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 (Trigger), resource (Make.com scenario), and mechanism (POST to webhook). It specifies the URL comes from make_list_hooks, distinguishing it from siblings like make_run_scenario.

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?

It implies using make_list_hooks first to get the URL, but does not explicitly state when not to use this tool vs alternatives like make_run_scenario. Context is clear but exclusions are missing.

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 fully discloses the mutating nature, high-risk implications, snapshot taken before applying, and the 'before_blueprint' recovery mechanism. It also reveals that the confirmed gate is this tool's own safety measure, not required by Make's API, and notes the snapshot does not block or compare.

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 long paragraph but front-loaded with 'HIGH RISK' and a clear purpose. It is dense with critical information but could be better structured with bullet points. It is not excessively verbose given the complexity.

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?

Despite lacking output schema and annotations, the description covers purpose, mandatory workflow, safety requirements, mutability, and recovery options. It is complete enough for an agent to safely use this high-risk mutation 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?

Schema coverage is 100% for all 6 parameters, each with descriptions. The description adds context for 'confirmed' as a safety gate and mentions 'blueprint' structure, but does not substantially add parameter-level meaning beyond 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 updates a scenario's blueprint (module structure/params/filters/connections), scheduling, name, and/or folder via PATCH, modifying REAL scenario structure. This specific verb+resource clearly distinguishes it from read-only siblings like make_get_blueprint and make_clone_scenario.

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?

It explicitly provides mandatory workflow: call make_get_blueprint first, get user approval of the diff, prefer testing on a clone (make_clone_scenario), and requires confirmed:true as proof. This gives clear when-to-use and alternative guidance.

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 must fully disclose behavior. It does note that the record is REPLACED (not merged), which is a key behavior. However, it omits details like required preconditions (key must exist), destructive nature, and response format.

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, no redundancy, key information front-loaded. Every sentence 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?

For a simple replace operation with three required parameters, the description is mostly complete. It explains the core behavior and key parameter semantics. It could mention what happens on success or error, but given no output schema, this is acceptable.

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 descriptions already exist. The description adds that 'data' must be the full new object, which provides clarity beyond the schema's 'The new record fields as an object'. This is helpful but not extensive.

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 replaces an existing record by key, using a full new object. It distinguishes from adding (make_add_record) and deleting (make_delete_record) with the explicit verb 'replace'.

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 for replacing records by key, but does not explicitly state when to use versus alternatives or when not to use. The purpose is clear enough for an agent to decide.

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