Northside Intelligence WebMCP

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

With no annotations provided, the description carries the full behavioral disclosure burden. It explicitly reveals the call has no side effects (no booking, no charge) and that payment/account creation happens externally on match-fit.net. This is the most critical behavioral trait for an agent to know, and it is stated clearly.

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 short sentences front-load the primary action and then add essential scope clarification. There is no redundancy, and each sentence contributes distinct 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?

For a single-parameter, side-effect-free link fetcher, the description gives the essential context: purpose, external dependency, and lack of side effects. The only minor gap is the exact shape of the returned link or response payload, but the absence of an output schema makes this less critical.

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

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

The schema coverage is 100%, and the only parameter coach_id is already well-described as 'Coach username from mf_search_coaches'. The description adds no further parameter-level detail, so the baseline 3 is appropriate since the schema does the heavy lifting.

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

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

The description opens with a specific verb and resource ('Get the link to book a Match Fit coach'), immediately conveying the tool's purpose. It further disambiguates the scope by stating that nothing is booked or charged, separating it from reservation and ordering siblings even without naming them.

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 clearly implies when to use the tool: when a booking link for a specific coach is needed. It also provides a clear boundary ('nothing is booked or charged by this call'), which tells the agent not to expect this call to complete a transaction. However, it does not explicitly name alternative tools such as mf_search_coaches for prerequisite steps.

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 annotations already declare readOnlyHint=true, and the description adds the 'Free' attribute and nationwide scope, providing useful context beyond the schema. It does not describe return format or limits, but given the read-only annotation, the bar is lower and 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 short sentences with zero wasted words. The core purpose is front-loaded, and the 'Free' note is a useful extra that doesn't clutter the description.

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 search tool with two optional parameters and no output schema, the description provides enough to invoke it correctly. It lacks explicit return value details, but that is not critical for a search 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?

The input schema covers both parameters with descriptions (100% coverage), and the description does not add additional meaning or formatting details. Per the baseline rule, a score of 3 is appropriate when the schema handles parameter documentation.

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 action (search) on a specific resource (Match Fit fitness coaches) with scope (nationwide) and filtering criteria (specialty, monthly budget). It distinguishes itself from the sibling mf_book_coach by implying this is the discovery step before booking.

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 the context (searching for coaches) but does not explicitly state when to use this tool versus alternatives like mf_book_coach or other search tools. It does not mention exclusions or prerequisites, so the guidance is implied 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?

With no annotations, the description carries the full behavioral burden. It discloses that the tool initiates a paid process (pricing mentioned), returns a checkout_url and order_id, and that the actual result is only available after payment via another tool. This is a critical transactional trait. It does not mention failure modes, side effects, or rate limits, but the core behavior is transparently described.

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, well-structured sentence that front-loads the purpose, then provides pricing, return values, and the next-step instruction. Every clause earns its place with no redundancy or filler. It is concise 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?

Given there is no output schema and no annotations, the description does a good job explaining the return (checkout_url, order_id) and the sequential workflow. It also names the follow-up tool. It lacks details on acceptable workflow_type values and potential error conditions, but for a tool that initiates a purchase, the core flow is adequately covered.

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 50% (workflow_type has a minimal description, tier has none). The description adds meaning to the tier parameter by mapping 'standard' to $33 and 'agentic' to $49.50, which is helpful. However, workflow_type remains vague—only described as 'Type of workflow to modernize' without examples or constraints. The description partially compensates for the tier parameter but does not fully address workflow_type.

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 action: 'Get a plan to connect a legacy business workflow to modern AI agent endpoints.' It names the resource (legacy workflow modernization), the verb (get a plan), and distinguishes itself by mentioning the return of a checkout_url and order_id, which is distinct from sibling tools like ni_order_status or ni_store_order. The purpose is 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 a clear use case (connecting legacy workflows to AI endpoints) and even specifies the follow-up action ('after payment call ni_order_status with order_id'). It does not explicitly state when not to use it or name alternatives for the same purpose, but the scenario is specific enough that an agent can infer appropriate usage. The pricing tiers (Standard vs Agentic) also help select parameters.

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 responsibility for behavioral disclosure. It does well by revealing the $18 cost, the immediate return of checkout_url and order_id, and the fact that results require a separate paid follow-up call. This gives the agent crucial behavioral context beyond the bare schema.

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, information-dense sentences fully describe the action, pricing, immediate response, and required next step. Every sentence earns its place and the core purpose is 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 there is no output schema and no annotations, this description is remarkably complete: it states the required input domain, the cost, the immediate outputs, and the necessary follow-up call to retrieve the result. An agent has enough information to invoke the tool correctly and understand the paid-async workflow.

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 only parameter, target_domain, is clearly documented in the schema as 'Domain of target company to audit.' The description reinforces this with 'target company website' but adds no additional semantic meaning beyond the schema's own 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 states a specific verb ('Run') and resource ('evidence-backed digital gap report on a target company website'), which clearly distinguishes it from sibling tools like ni_order_status or ni_bridgeai_run. It immediately communicates what the tool accomplishes.

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: when a digital gap report on a target domain is needed. It also gives a direct follow-up instruction to call ni_order_status after payment, which guides the agent through the expected workflow. It does not explicitly list when not to use it or compare against alternative gap-report tools, but the context is strong enough for 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?

With no annotations present, the description carries the full behavioral burden. It discloses a non-obvious transactional behavior: the tool returns checkout details, and results are only available after payment through a separate call. It could go further by explaining what ni_order_status returns, but the core workflow is transparent.

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 fluff: the first states the primary purpose, and the second captures the required follow-up workflow. Every clause contributes actionable information, and key price and next-step details are front-loaded logically.

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 an output schema and annotations, the description covers the essential calling contract: returns checkout_url and order_id, and tells the agent to call ni_order_status afterward. It doesn't describe failure modes or the exact format of final results, but the workflow is sufficiently complete 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 coverage is 50%: discipline is described in the schema, but tier is only an enum/default with no explanation. The description adds meaning to tier by mapping 'standard' and 'agentic' to prices, but it does not explain the substantive difference between the tiers, leaving some semantic ambiguity.

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 action ('Search open grant opportunities'), a clear scope ('for a discipline'), and the outcome ('matched listings'), so an agent knows exactly what this tool is for. It further distills the paid workflow by naming the tier options, making it distinct from generic search tools among the 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 gives clear context for when to use the tool: to search grant opportunities and obtain a checkout_url and order_id. It also points to the next step, calling ni_order_status after payment, which provides routing guidance, though it does not explicitly contrast this tool with other search-like siblings such as ni_store_search.

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 only declare readOnlyHint=true. The description adds behavioral value by disclosing that the tool both checks payment status and returns the purchased result once paid, implying a polling/re-check pattern. It does not contradict the read-only annotation and gives useful context beyond the structured fields.

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 with zero waste: it front-loads the action, identifies the input source, and states the eventual outcome. Every word earns its place and no redundant details are present.

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 one-parameter tool with no output schema, the description covers what it does, what input it expects, and what is eventually returned. It doesn't explicitly describe the unpaid/error response, but 'once paid' implies a status check cycle. Sufficiently complete for the tool's simplicity.

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 already explains order_id as 'returned with a checkout_url'. The tool description's 'returned by any paid tool' reinforces the same idea but adds no new format, constraints, or examples. Baseline 3 is appropriate since schema does the heavy lifting.

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

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

The description names a specific action ('Check payment status') and resource ('order returned by any paid tool'), and adds the key outcome ('receive the purchased result once paid'). This clearly distinguishes it from sibling tools that run or store jobs, leaving no ambiguity about what it does.

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 phrase 'returned by any paid tool' establishes the context: use this when you have an order_id from a checkout_url. It implies the workflow (payment polling) but does not explicitly name alternatives or state when not to use it. Clear context, but no exclusions.

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

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

No annotations are provided, so the description carries the full burden of disclosure. It does add a meaningful behavioral constraint: the free tier is limited to 10 replies per agent per day and subscribing unlocks more. However, it does not disclose whether the tool only generates a draft or also sends it, nor does it describe response shape or other side effects.

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 tightly written sentences: the first states the core purpose, and the second provides a concrete usage limit. There is no fluff, and 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 three-parameter generation tool, the description covers the main action and a key constraint. However, there is no output schema and no statement about what the tool returns, whether the reply is drafted or sent, or how failures/limits surface. This leaves some contextual gaps for an agent to infer.

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 67% schema description coverage, the schema already explains lead_message and context, while tone is enumerated with a default. The description itself adds no parameter-level detail, but the existing schema coverage is sufficient for an agent to construct a valid call. The tone values are also self-explanatory.

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 action and resource: generate a personalized reply to a lead message using ReplyFlow. It is not a tautology and gives enough to know what the tool does, though it does not explicitly differentiate itself from sibling tools like ni_replyflow_subscribe.

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 opening clause implies this is the tool for replying to lead messages, and the 'subscribe for more' phrase hints at quota-related usage. However, it never explicitly states when to use this tool over alternatives or when not to use it, leaving usage guidance mostly implied.

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 bears the full burden of behavioral disclosure. It reveals that this is a purchase action (billed monthly by card), returns a checkout_url for external payment, and yields the final result only after a follow-up call to ni_order_status. This effectively communicates the async and externally-dependent nature of the operation, though it omits details like failure modes, idempotency, or whether a subscription auto-renews.

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 compact sentences, front-loaded with the core action ('Subscribe to ReplyFlow') and immediately followed by the plan/billing scope, return values, and a precise next-step pointer. Every phrase earns its place; there is no filler, repetition, or off-topic 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 no output schema and no annotations, the text adequately covers the tool's purpose, plan options, billing mechanism, return payload, and the exact follow-up call. Minor omissions exist—it does not explicitly state that the subscription is only active after payment completes, nor that checkout_url is a Stripe payment link (though this is implied by the schema and wording). These are relatively small gaps for a 2-parameter purchase 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%, both parameters have descriptions, and the tier parameter already has an enum and default. The description adds billing context ('billed monthly by card') and ties tier values to the 'Solo, Team or Agency' plan names, which slightly enriches the parameter semantics. It does not, however, add new constraints or format details beyond what the schema already states, so a 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?

The description states a specific verb and resource: 'Subscribe to ReplyFlow, the automated lead DM and email reply engine.' It clearly defines the plan options (Solo, Team, Agency) and billing method (monthly by card), plus the return payload (checkout_url, order_id). It also distinguishes itself from the sibling ni_order_status by explicitly naming it as the follow-up call, making the tool's role 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 the tool: to subscribe to ReplyFlow and obtain a checkout URL and order ID. It gives a direct workflow instruction—'after payment call ni_order_status with order_id to get the result'—which tells the agent the next step. However, it does not explicitly state when NOT to use this tool vs. alternatives like ni_replyflow_generate, leaving some sibling differentiation implicit.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it excels: it states the non-refundable deposit, card being saved, balance charged upon completion, final price confirmed after scoping, and the return of checkout_url and order_id. This thoroughly informs the agent of side effects and required follow-up actions.

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 and every sentence contributes necessary information: pricing and deposit terms in the first, payment flow and follow-up in the second. It is slightly dense due to the price list, but it contains no filler, so it remains appropriately sized and front-loaded with the core purpose.

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

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

For a tool with no annotations and no output schema, the description is remarkably complete: it explains the deposit mechanics, pricing, what is returned (checkout_url and order_id), and the next step to check order status. An agent has enough to invoke the tool correctly and manage the follow-up workflow.

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 all parameters, so the baseline is 3. The description adds value by mapping service_type enum values to specific prices (e.g., 'intelligence audit $410'), which helps the agent select the correct service package. This goes beyond the schema's generic 'Selected service package' 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's action ('Reserve a Northside Intelligence service project') and its resource, and includes specific pricing for each service type, making it distinct from sibling tools like ni_order_status or ni_store_order. It also explicitly names the follow-up tool, further clarifying its role in the workflow.

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 clear context for when to use this tool (to reserve a service with a deposit) and directs the agent to ni_order_status after payment, but it does not provide explicit exclusions or alternatives beyond that follow-up step. The workflow instruction is helpful, yet the 'when-not-to-use' guidance is implied rather than 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?

With no annotations, the description carries the full burden, and it discloses key behaviors: cost ($24), return values (checkout_url, order_id), and the asynchronous result retrieval via ni_order_status. It doesn't mention failure modes or timing, but it outlines the essential workflow.

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-loading the core purpose before cost and next steps. Every clause adds value, with no verbose or redundant 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 2-parameter tool with no output schema, the description is fairly complete: it states purpose, cost, return fields, and the follow-up tool. It omits details like how payment completion is confirmed or what the final brief looks like, but an agent has enough to invoke it correctly.

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 echoes 'signals you supply' but doesn't add new meaning beyond the schema's existing parameter descriptions. It neither corrects nor significantly extends 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 ('Get') and resource ('prioritized market signal brief') with a clear subject ('industry vertical') and source ('built from signals you supply'). It clearly distinguishes this tool from siblings like ni_order_status and ni_store_order by establishing its unique paid-brief purpose.

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 use: you supply signals, pay $24, receive a checkout_url/order_id, then use ni_order_status. It doesn't name explicit alternatives or exclusions, but the call-to-action and follow-up are unambiguous.

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 must carry the behavioral burden, and it does add useful context: payment and shipping are handled via Stripe checkout, and the tool returns checkout_url and order_id. But it stops short of disclosing the side effects of creating an order, whether payment is completed synchronously, or what state the order is in before checkout completion.

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 dense sentence leads with the action and constraint, then covers payment method and return values. Every clause earns its place and there is no redundant restatement of the input schema.

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 gives the two important outputs and the payment context, which is helpful. Still, for a side-effectful purchase tool with no annotations and no output schema, it omits the order lifecycle, what to do with checkout_url, and practical prerequisites such as sourcing a valid SKU or respecting the US-shipping constraint.

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 only 33%, and the description does not clarify item_sku or quantity or explain the shipping_address object structure. Worse, saying shipping details are 'collected on Stripe checkout' can confuse an agent into thinking shipping_address is not required, even though the schema lists it as a required input.

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 opens with a concrete verb ('Buy') and a clear target resource ('item from the Northside Intelligence Smart Store'), plus an important scope constraint ('US shipping'). This makes the tool's purpose immediately distinguishable from sibling tools like ni_store_search and ni_order_status.

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 intended use is implied by 'Buy an item', so an agent can infer this is the purchase tool. However, there are no explicit conditions, prerequisites, or alternatives mentioned, such as using ni_store_search to find an SKU first or ni_order_status to track the resulting order.

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 annotation readOnlyHint=true already discloses that this is a read-only operation. The description adds scoping context ('trending products and verified dropship inventory'), which is a mild behavioral constraint about what the search targets. Yet it does not elaborate on pagination, rate limits, authentication, or response behavior. With annotations covering the safety profile, a 3 is appropriate for the added scoping context but no richer behavioral disclosure.

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, front-loaded sentence that states the action and resource immediately. There is zero filler or redundancy—every word contributes to understanding the tool's purpose.

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 read-only search tool with only two optional, schema-documented parameters, the description gives enough context to call it correctly. There's no output schema, but the purpose is clear and the annotations cover the read-only aspect. The only missing piece is any mention of response format or sorting, but this is minor given the low 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?

Schema description coverage is 100%, so both query and max_price are already documented in the input schema. The description adds no parameter-specific meaning beyond what the schema provides—it doesn't clarify formats, defaults, or relationships. Baseline 3 applies because the schema does the heavy lifting.

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

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

The description clearly states a specific action ('Search') against a specific resource ('Northside Intelligence Smart Store catalog') and scopes it to 'trending products and verified dropship inventory.' This distinguishes it from sibling search tools like mf_search_coaches or ni_grantbot_search by naming a unique resource and domain.

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 implied usage is clear: use this when you need to search the smart store catalog. However, there is no explicit guidance about when to prefer this over alternatives like ni_store_order (ordering) or ni_order_status (status), and no exclusions or prerequisites are mentioned. The verb 'Search' does imply the read-only use case, but not enough for a 4.

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