AiDOOS Virtual Delivery Center

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

Annotations already indicate this is a mutation (readOnlyHint=false, idempotentHint=false) and non-destructive (destructiveHint=false). The description adds valuable behavioral context by outlining the output structure (teams, roles, AI agents, work modules, timeline, plan size) and the plan_id return value. It does not contradict any annotations and complements them with specific information about what is produced, earning a 4.

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 and front-loaded with the core purpose. It uses multiple sentences but each carries meaningful information: what it does, what it returns, and when to use it. It avoids unnecessary filler but contains a slight redundancy between 'Create a structured delivery plan for an initiative the user describes' and 'Given a plain-language description of something to build...' which is minor. Overall, it is well-structured and 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?

With an output schema present, the description does not need to detail return values, and it appropriately mentions the plan contents and plan_id. The tool has one required parameter and two optional ones, all explained in the schema. The description provides sufficient context for an agent to understand when and how to call it, including that it is a creation step for other tools. No critical operational details are missing for correct invocation.

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

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

The input schema has 100% parameter description coverage, so the schema fully documents all three parameters (initiative, industry, company_size). The description does not add any extra parameter semantics beyond what's in the schema, such as default values or format expectations. Since the schema does the heavy lifting, a 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 the tool's purpose: 'Create a structured delivery plan for an initiative the user describes.' It specifies the verb (create), resource (delivery plan), and the content of the plan (teams, roles, AI agents, Delivery Units, timeline, plan size). It distinguishes itself from siblings implicitly by mentioning it produces a plan_id used by other tools, but does not explicitly name alternatives. This is clear and specific, though not explicitly differentiated from refine_delivery_plan.

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?

Explicit when-to-use guidance is provided: 'Use this tool when a user describes a project or initiative and wants to understand the team, scope, timeline, or cost to deliver it.' This gives clear context and intent for invoking the tool. However, it does not mention when not to use it or list alternative tools (e.g., refine_delivery_plan for modifications), so it lacks explicit exclusions or named alternatives, scoring a 4 rather than 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?

Annotations already carry the safety profile (destructiveHint=false, openWorldHint=true, idempotentHint=false), so the bar is lower. The description adds useful context about the output shape, but since an output schema exists that content is largely redundant, and it never addresses the non-idempotent hint or that estimates may vary between calls due to external calibration.

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?

Four short sentences, zero filler, and the core purpose and return shape are front-loaded before the routing guidance. 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?

An output schema exists, so the description needn't document return values, and it correctly covers purpose, triggering condition, and the sibling alternative. Nothing an agent needs to call this correctly with a valid modules list is missing.

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 itself supplies examples ('Tenant onboarding flow with SSO integration'). The description adds only the framing that items are short deliverable descriptions, which the schema already states. Baseline 3 is appropriate where the schema does the heavy lifting.

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

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

States a specific verb and resource ('estimate the size and cost of a specific list of work items') and enumerates what comes back: per-item Delivery Units, a total, an indicative cost, and a recommended plan size. It also explicitly distinguishes itself from the sibling create_delivery_plan, so an agent can route without opening either schema.

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?

Gives both a positive trigger ('when the user has already broken the work into specific items and wants sizing') and a negative one with a named alternative ('when the user describes an overall goal without a breakdown, use create_delivery_plan instead'). This is exactly the when/when-not/alternative structure that enables correct selection.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it 'Returns the plan's current status and contents,' giving a slight behavioral detail beyond the annotations. It is consistent with annotations and does not contradict them, though it doesn't go into depth about edge cases—acceptable given the 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?

The description is three short sentences, with the core purpose front-loaded in the first sentence, followed by a brief note on return value and a usage hint. Every sentence earns its place; there is no fluff or 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 that the tool has only one parameter, an output schema is present, and annotations cover safety and idempotency, the description fully addresses what an agent needs: what it does, what it returns, and when to use it. Nothing essential is missing for correct invocation.

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

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

Schema description coverage is 100%—the plan_id parameter already has a detailed description in the schema ('The plan_id from a prior create_delivery_plan or refine_delivery_plan call'). The tool description merely repeats 'by its plan_id' without adding new meaning. Since the schema carries the full semantic load, the description provides no extra value, warranting the baseline score 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 states a specific verb ('Retrieve'), a specific resource ('previously created delivery plan'), and the key parameter (plan_id). It clearly distinguishes from siblings like create_delivery_plan and refine_delivery_plan by focusing on retrieval of an existing plan, leaving no ambiguity about the tool's role.

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 'Use this tool when the user wants to revisit or summarize a plan created earlier in the conversation,' providing clear context for when to invoke it. It does not explicitly name alternatives, but the sibling tool names (create, refine, estimate, recommend) make the distinction obvious. The guidance is sufficient for an agent to make the right selection.

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

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so safety is covered. The description still adds real value beyond them: it states the tool is advisory only, takes no payment, completes no purchase, and routes users to external AiDOOS referral links.

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?

Four sentences, each doing distinct work: purpose, return contents, trigger condition, and the payment/write boundary. Front-loaded with the core action, and nothing is redundant.

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 one-parameter, read-only, advisory tool with annotations and an output schema, the description covers purpose, trigger, and boundary conditions without needing to describe return formatting. Nothing an agent needs to select or call it correctly is missing.

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?

There is a single parameter with 100% schema description coverage, and the schema already says the plan_id comes from prior create/refine calls. The description restates that provenance without adding format, validation, or lookup semantics beyond the schema, so the 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?

The description names a clear action and resource (summarize next steps for a delivery plan) and enumerates what the call returns: plan size, indicative cost, tiers, and referral links. It implicitly separates itself from create/refine siblings by being advisory, but never explicitly contrasts with get_delivery_plan, the closest sibling.

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 gives an explicit trigger: use when the user asks how to proceed or what the next step is for a plan created earlier in the conversation. The 'advisory only' clause adds a boundary, but no alternative tool is named for when a user wants raw plan data instead of a recommendation.

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 it 'replaces the stored plan with the revised version,' which aligns with the destructiveHint annotation and adds specific behavioral context beyond the raw annotation. It also notes it returns the updated plan. This is valuable transparency for a destructive operation, though it does not cover rollback or error conditions. No contradiction with annotations.

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 concise sentences: purpose, mechanism, and usage condition. Every sentence adds distinct value without redundancy. It is front-loaded with the core action and includes a practical usage note. There is no fluff or unnecessary detail.

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 presence of an output schema, the description does not need to explain return values. It covers the tool's destructive nature, the required parameters, and the appropriate usage condition. It implies the plan must already exist but does not state this explicitly; however, this is a minor gap relative to the overall 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 description coverage is 100%, and both plan_id and feedback have detailed descriptions in the schema, including examples. The description in the tool text essentially echoes this information without adding new meaning. Since the schema does the heavy lifting, the 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 a specific verb ('Revise an existing delivery plan') with the resource and context. It differentiates from sibling tools like create_delivery_plan (creation) and get_delivery_plan (retrieval) by focusing on modification. The mention of 'requested changes' and specific adjustment examples makes the purpose unmistakable.

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

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

The description gives an explicit when-to-use condition: 'Use this tool when the user wants to modify a plan created earlier in the conversation.' This clearly distinguishes it from creation or retrieval. However, it does not explicitly name alternative tools or state when not to use it, 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.