Connect AI assistants to Paxaver, the School Community Operating System, for authorized access to school lunch menus, student lunch orders, wallet balances, school events, restaurants, and school-community operations.
Cancels a finalized order if labels have not been sent yet. Refunds the wallet. This is a DESTRUCTIVE operation - always confirm with the user before cancelling. If labels have already been sent, the cancellation will be rejected. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes | Order ID to cancel |
| Name | Required | Description |
|---|---|---|
| id | No | |
| status | No | |
| refundCents | No | |
| balanceCents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark destructiveHint=true, and the description reinforces this by stating the operation is DESTRUCTIVE and refunds the wallet. It also discloses the rejection condition (labels already sent) and idempotency, both beyond the 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 compact, with the core purpose and condition in the first sentence followed by safety-critical caveats. Every sentence adds information: refund, destructive confirmation, rejection condition, idempotency.
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 tool with a high-coverage schema and output schema present, the description covers the key behavioral aspects: scope, refund, destruction, rejection, idempotency, and user confirmation. No important gaps are evident.
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 single parameter order_id is fully documented in the schema (100% coverage), so the description doesn't need to add param detail. It provides no extra meaning beyond the schema, matching 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?
States a specific verb 'Cancels' with resource 'finalized order' and a condition ('if labels have not been sent yet'), which distinguishes it from order-creation/finalization siblings. The behavior is unambiguous even without reading the 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?
Description explicitly scopes valid use: only finalized orders, and only before labels are sent; it warns that cancellation is rejected if labels have already been sent. It also instructs to always confirm with the user before cancelling, giving clear operational guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Creates a draft lunch order for a student. Requires student_id, school_slug, menu_date, and items array. Each item needs menu_item_id, menu_item_name, price_cents, and quantity. The draft is not finalized - call finalize_order to commit the order and deduct payment. This is a FINANCIAL + WRITE operation - always confirm the order details with the user before calling. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | ||
| menu_date | Yes | YYYY-MM-DD | |
| student_id | Yes | Student ID | |
| school_slug | Yes | School slug |
| Name | Required | Description |
|---|---|---|
| id | No | |
| items | No | |
| status | No | |
| menuDate | No | |
| studentId | No | |
| schoolSlug | No | |
| itemTotalCents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly discloses that this is a FINANCIAL + WRITE operation, requires user confirmation, is idempotent, and does not finalize or deduct payment until finalize_order is called. This adds meaningful behavioral context beyond the minimal 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 compact and well-structured: it states the core operation, explains the lifecycle with finalize_order, and adds a critical safety reminder. Each sentence serves a distinct purpose with no unnecessary filler.
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 essential operational context: draft behavior, follow-up commit step, financial/write nature, confirmation requirement, and idempotency. It is complete for a draft-order tool, though clearer differentiation from order_lunch would further strengthen 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?
Schema coverage is 75%, so the description is not fully responsible for parameter documentation. The description reiterates the required top-level fields and item fields, but adds little semantic meaning beyond what the schema already provides, such as price_cents being in cents or menu_date format.
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 ('Creates a draft lunch order for a student') and the exact resource it operates on. It also distinguishes the tool from siblings by explicitly noting the draft is not finalized and that finalize_order is the commit step.
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 strong usage context: it explains that finalize_order should be called afterward to commit and deduct payment, and it instructs the agent to always confirm order details with the user before calling. It does not explicitly contrast with the sibling order_lunch, so exclusion guidance is slightly incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Finalizes a draft order, deducting payment from the wallet. Optionally include tip_cents (donated to the school's PAC). This is a FINANCIAL + WRITE operation - always confirm with the user before calling. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes | Order ID from create_draft_order | |
| tip_cents | No | Tip in cents (donated to school PAC) |
| Name | Required | Description |
|---|---|---|
| id | No | |
| status | No | |
| tipCents | No | |
| totalCents | No | |
| balanceCents | No | |
| itemTotalCents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, it explicitly flags this as a FINANCIAL + WRITE operation, mandates user confirmation, and states idempotency. These are material behavioral disclosures that an agent needs, and they do not contradict the readOnlyHint/destructiveHint 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?
Four short sentences: core purpose, optional parameter, critical warning, and idempotency. Everything earns its place and is front-loaded for quick scanning.
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 financial write operation it covers the action, payment effect, user-confirmation requirement, idempotency, and optional tip. With an output schema available and only two well-documented parameters, nothing essential 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 coverage is 100%, and the description adds no meaning beyond the schema's parameter descriptions. It mentions the option to include tip_cents and its PAC donation purpose, matching the schema, but doesn't enrich parameter semantics further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action (finalizes), a precise resource (draft order), and the key effect (deducts payment from wallet). This clearly differentiates from sibling tools like create_draft_order or order_lunch by focusing on the finalization/payment step.
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 instruction to confirm with the user before calling provides a clear trigger condition for this financial/write action. It doesn't explicitly name alternatives or state when not to use it, but the draft-order scoping and optional tip parameter make the intended context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a monthly summary of orders. Optionally filter by month (YYYY-MM) and student. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| month | No | YYYY-MM | |
| student_id | No | Filter to a specific student (must be your own) |
| Name | Required | Description |
|---|---|---|
| orders | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the behavior is partially known. The description adds 'Read-only' (repeating the annotation) and the notion of a summary, but does not disclose how missing month is handled, what the summary contains (counts, revenue, statuses), or any other behavioral traits. No contradiction, but little novel 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 three short, purposeful sentences. The main purpose is front-loaded, followed by the key filtering options and the read-only guarantee. Every sentence earns its place with no redundant filler.
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 tool with two optional parameters, a fully described schema, and an output schema present, the description is mostly complete. The only notable gap is the unspecified behavior when no month is provided (e.g., current month vs. all months), but that is a minor ambiguity rather than a blocking omission.
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%, with the schema already documenting 'YYYY-MM' and 'must be your own'. The description merely restates the existence of optional filters without adding format, constraints, or default behavior. Baseline of 3 is appropriate since the schema carries the semantic load.
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 specific verb and resource: 'Returns a monthly summary of orders.' This distinguishes it from sibling tools like get_orders (likely more granular) and get_daily_menu by the temporal aggregation level.
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 through 'monthly summary' and optional filters, but it never explicitly contrasts with alternatives like get_orders or states when to prefer this tool. There is no when-to-use versus when-not-to-use guidance, leaving the agent to infer based on the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns recent lunch orders for the authenticated user's students. Read-only. Optionally filter by student_id.
| Name | Required | Description | Default |
|---|---|---|---|
| student_id | No | Filter to a specific student (must be your own) |
| Name | Required | Description |
|---|---|---|
| orders | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and non-destructive behavior, so the description only needs to add context beyond that. It adds that orders are scoped to the authenticated user's students and limited to 'recent,' which is useful. However, it does not define 'recent' or disclose ordering/pagination, so the added behavioral context is moderate.
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 short and front-loaded with the core purpose. Minor redundancy exists because 'Read-only' restates an annotation, but it is still economical and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one optional parameter and an output schema, the description provides enough to invoke it correctly. The only notable gap is the undefined meaning of 'recent,' but that is not likely to prevent correct usage given the output schema and annotations.
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 already covers student_id with 100% description coverage, including the constraint that it must be the user's own student. The tool description merely restates 'Optionally filter by student_id' without adding any new meaning, 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 states a specific verb and resource: it returns recent lunch orders for the authenticated user's students. It also distinguishes itself from siblings like get_monthly_orders (recent vs. monthly) and order_lunch (returns vs. creates), so the agent can tell it apart.
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: it is for reading recent lunch orders and optionally filtering by a student. It does not explicitly mention when not to use it or name alternatives such as get_monthly_orders for a broader history, so it stops short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns upcoming events for the user's active school. Optionally filter by date range (start_date / end_date, YYYY-MM-DD). Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | YYYY-MM-DD | |
| start_date | No | YYYY-MM-DD |
| Name | Required | Description |
|---|---|---|
| events | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry readOnlyHint=true and destructiveHint=false, so the safety profile is externally supplied. The description adds the active-school scoping and optional date-range filtering, but it does not disclose ordering, pagination, or how 'upcoming' is bounded. This is useful context but not rich 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?
Two sentences, action-first phrasing, and the optional filter details are packed into a single clear clause. There is no filler or redundant explanation beyond the brief read-only note, which remains useful if the description is read standalone.
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 read-only tool with two optional parameters and an output schema, the description covers the target, scope, filter options, and safety profile. An agent can correctly decide whether to call it and construct a valid request without missing critical information.
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 each parameter already documents the YYYY-MM-DD format. The description adds that start_date and end_date form an optional date range, but this is largely inferable from the parameter names and the optionality is already present in the schema. The added semantic value is moderate.
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 action ('Returns upcoming events') and a precise scope ('user's active school'), distinguishing it from sibling tools about orders, menus, and wallet data. It also contrasts with register_event, which is an event write operation rather than a read.
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 context is clear: use this to fetch upcoming events for the active school, with optional start/end date filtering. However, it does not explicitly name an alternative for other event-related operations or state when not to use this tool, so it stops short of fully explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the authenticated Paxaver user context: their name, active school, students they are a guardian for, and available roles. ALWAYS call this first before any other tool to establish context. This is a read-only operation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| roles | No | |
| lastName | No | |
| students | No | |
| firstName | No | |
| schoolName | No | |
| schoolSlug | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already signals a safe read operation, and the description reinforces this by stating 'This is a read-only operation.' The description adds context about authentication and the returned user context, but does not disclose additional behavioral details such as failure modes or authentication requirements beyond what annotations imply.
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 and every sentence earns its place. The core return value is front-loaded, followed by a direct and unambiguous usage instruction. There is no filler or repetition that detracts from its clarity.
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 no parameters and an output schema is present, the description covers what an agent needs: what the tool returns, that it is read-only, and that it should be called first. It is complete for its simplicity and effectively orients the agent within the sibling tool set.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema coverage is 100%, so there is no parameter ambiguity for the description to resolve. With 0 params, a baseline score of 4 is appropriate; the description correctly focuses on the output and usage rather than trying to document nonexistent inputs.
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 ('Returns') and names a clear resource: the authenticated Paxaver user context. It enumerates the exact contents (name, active school, guardian students, available roles), making its purpose unmistakable and distinct from the sibling 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 provides an explicit usage directive: 'ALWAYS call this first before any other tool to establish context.' This clearly tells the agent when to invoke it and establishes its role as a prerequisite for using other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the current wallet balance for the authenticated user at their active school. Read-only. Use this to check funds before ordering lunch.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| currency | No | |
| balanceCents | No | |
| balanceFormatted | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'Read-only.' It adds useful scoping context about the authenticated user and active school, but it does not disclose anything beyond that, such as whether balance can be zero, stale, or require refresh. With annotations already covering the safety profile, a 3 is appropriate.
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 compact sentences deliver the core function, scoping, read-only nature, and usage context. Every sentence earns its place, and the main verb and resource are 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?
For a simple zero-parameter, read-only getter with an output schema already present, the description is fully sufficient. It states what is returned, for whom, at what scope, and when to use it. No critical information 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?
The tool has zero parameters and the input schema is empty, so there is nothing missing from the description. The description correctly implies the only implicit inputs are the authenticated user and active school context. Baseline 4 is appropriate for a zero-parameter tool.
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 and resource: 'Returns the current wallet balance for the authenticated user at their active school.' It is distinct enough from siblings like get_wallet_status, but it never explicitly contrasts itself with that sibling, so some ambiguity remains about why both wallet tools exist.
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 usage context: 'Use this to check funds before ordering lunch.' While this is a strong signal for when to call the tool, it does not name alternatives or provide when-not-to-use guidance, 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.
Returns the wallet balance plus recent transactions and pending deposits. Read-only. Use this for a wallet overview.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| balance | No | |
| balanceCents | No | |
| transactions | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's 'Read-only' adds little. It does add value by specifying the returned components (balance, transactions, pending deposits), but no additional behavioral traits such as freshness, limits, or error conditions are disclosed.
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 no wasted words. The main return content is front-loaded, and the usage hint is appended cleanly.
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 zero-parameter read-only tool with an output schema and clear annotations, the description is essentially complete. The only minor gap is not explicitly distinguishing when to prefer get_wallet_balance over this tool, but the content difference is implied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no schema burden to compensate for. The description appropriately avoids inventing parameter details.
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 ('Returns') and resource (wallet status) with a clear scope: balance, recent transactions, and pending deposits. This differentiates it from sibling get_wallet_balance, which presumably returns only the balance.
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?
'Use this for a wallet overview' gives clear context for when the tool is appropriate. It does not explicitly exclude get_wallet_balance or name an alternative condition, but the overview framing is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Places a lunch order for a student the authenticated user is a guardian of. Requires menu_item_id (from get_daily_menu) and menu_date (YYYY-MM-DD). Optionally specify student_id (defaults to the user's first student if only one). Payment is deducted from the wallet. This is a FINANCIAL + WRITE operation - always confirm the order details (student, item, date, quantity) with the user before calling. Idempotent: duplicate calls with the same idempotency context will not create duplicate orders.
| Name | Required | Description | Default |
|---|---|---|---|
| quantity | No | Number of servings (default 1) | |
| menu_date | Yes | YYYY-MM-DD | |
| student_id | No | Student ID (must be your own student; from get_user_info) | |
| menu_item_id | Yes | Menu item ID from get_daily_menu |
| Name | Required | Description |
|---|---|---|
| id | No | |
| items | No | |
| status | No | |
| menuDate | No | |
| studentId | No | |
| schoolSlug | No | |
| itemTotalCents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavior beyond annotations: payment is deducted from the wallet, it is a financial + write operation, and it is idempotent so duplicate calls will not create duplicate orders. This is valuable transparency for a tool with financial side effects and minimal annotation guidance.
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 compact and front-loaded: it opens with the core action, then covers prerequisites, optional parameters, financial impact, confirmation requirement, and idempotency in a few sentences. 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?
Given the output schema exists and annotations are simple, the description covers the key operational context: who can order, what inputs are required and where they come from, the wallet side effect, confirmation obligation, and idempotency behavior. Nothing critical is missing for safe 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?
With 100% schema coverage, the baseline is 3. The description adds extra meaning by linking menu_item_id to get_daily_menu, clarifying the menu_date format, and explaining student_id default behavior. These enrich the schema rather than merely repeating it.
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 starts with a specific verb and resource: 'Places a lunch order for a student the authenticated user is a guardian of.' It clearly establishes scope, prerequisites, and the financial nature, making it easy to distinguish from sibling tools like create_draft_order or finalize_order.
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 clear preconditions: requires menu_item_id from get_daily_menu and menu_date in YYYY-MM-DD format. It also provides a safety instruction to confirm details before calling. It does not explicitly mention when not to use this tool or compare it to draft/finalize alternatives, but the context is strong enough to guide an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Registers the authenticated user for a school event. Requires event_id. Optionally specify quantity (default 1). This is a WRITE operation - confirm with the user before registering. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| event_id | Yes | Event ID | |
| quantity | No | Number of tickets |
| Name | Required | Description |
|---|---|---|
| id | No | |
| status | No | |
| eventId | No | |
| quantity | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavioral traits beyond the annotations: it explicitly says this is a WRITE operation, instructs the agent to confirm with the user, and states idempotency. These are exactly the kind of side-effect and retry-safety details that annotations alone do not convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no wasted words, front-loading the core purpose and then giving the essential invocation and safety information. The structure is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with only two flat parameters and an existing output schema, the description covers all needed context: required input, optional input, default behavior, write side effect, user confirmation, and idempotency. Nothing material 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%, so the schema already documents both event_id and quantity. The description restates the requirement and default but adds no new semantic meaning beyond what the structured schema provides, so the baseline score 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 ('Registers') and clearly names the resource and scope: the authenticated user for a school event. It also implicitly distinguishes itself from sibling event tools like get_upcoming_events and sign_up_to_volunteer by establishing registration-for-a-school-event semantics.
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 tells the agent that event_id is required and quantity is optional with a default of 1. It also clearly instructs that this is a WRITE operation requiring user confirmation, which is strong guidance for invocation. It does not explicitly name alternatives, but the usage context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Signs up the authenticated user as a volunteer for a specific shift. Requires shift_id (from get_upcoming_events or event detail). This is a WRITE operation - confirm with the user before signing up. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| shift_id | Yes | Volunteer shift ID |
| Name | Required | Description |
|---|---|---|
| id | No | |
| status | No | |
| shiftId | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavior beyond the annotations: it warns this is a WRITE operation that requires user confirmation, states the operation is idempotent, and notes the user must be authenticated. These are important behavioral traits not captured by readOnlyHint, openWorldHint, or destructiveHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tight sentences: purpose, required parameter source, write/confirmation warning, and idempotency. No filler or repetition, and the most operationally important warnings are 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?
For a single-parameter tool with an output schema present, the description covers the essential context: authenticated user, parameter provenance, write side effect, confirmation requirement, and idempotency. Nothing critical is missing for an agent to invoke the tool 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?
The schema already covers shift_id fully at 100% coverage. The description adds extra value by explaining where to obtain shift_id ('from get_upcoming_events or event detail'), which helps the agent choose the correct value. It doesn't specify formatting details, but the schema already describes it as a string.
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 ('Signs up the authenticated user as a volunteer'), the resource ('a specific shift'), and the required input ('shift_id'). It also distinguishes this from siblings by referencing volunteer shifts and sourcing shift IDs from get_upcoming_events, which separates it from register_event and order_lunch.
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 usage context: use it to sign up for a volunteer shift and pull shift_id from get_upcoming_events or event detail. It does not explicitly name alternative tools or state when not to use it, so it falls short of a 5, but the guidance is concrete and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
cancel_ordercreate_draft_orderfinalize_orderget_daily_menuget_monthly_ordersget_ordersget_upcoming_eventsget_user_infoget_wallet_balanceget_wallet_statusorder_lunchregister_eventsign_up_to_volunteerClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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Claim ownership of the server listing
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Add one secure layer between your agents and this server.
Most tools target distinct resources and actions clearly, but get_wallet_balance and get_wallet_status overlap heavily since one is essentially a subset of the other. The draft/finalize/order_lunch workflow is also a potential source of confusion, though descriptions help clarify the difference.
All tool names follow a consistent snake_case verb_noun pattern, such as cancel_order, get_daily_menu, and register_event. Naming conventions are predictable and uniform across the entire set.
With 13 tools, the server is well-scoped for its domain of lunch ordering, wallet management, and school events. Each tool serves a clear functional purpose without excessive redundancy or unnecessary bloat.
The core workflows are well covered: menu lookup, order creation/finalization/cancellation, wallet visibility, event registration, and volunteer sign-up. Minor gaps exist, such as no event detail tool specifically for shift_id retrieval and no cancellation for event registrations, but agents can work around these.