@striderlabs/mcp-marriott

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action (login, search, select, checkout, etc.) with clear boundaries. No two tools overlap in purpose.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., search_hotels, get_hotel_details, cancel_reservation). Single-word tools like status and login fit the verb style.
Tool Count4/5
16 tools cover a comprehensive hotel booking workflow from login to check-in and loyalty management. Slightly above the typical 3-15 range, but still well-scoped and each tool earns its place.
Completeness4/5
Covers authentication, search, details, room selection, extras, booking, modifications, cancellations, check-in, and loyalty. Minor gaps like viewing account profile, but core booking lifecycle is complete.
Average 4/5 across 16 of 16 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must convey behavioral traits. It only states the action ('Add') without disclosing if extras are confirmed immediately, if charges apply, or if it modifies an existing reservation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise, lists examples efficiently. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimally complete: states what it does but lacks context on when to use (e.g., requires active booking). No output schema, but acceptable given tool simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with enum values. The description adds context by saying 'optional extras to your booking', tying it to a reservation. This adds meaning beyond the schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add') and the resource ('optional extras to your booking') and lists examples, making it distinct from sibling tools like modify_reservation or select_room.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., modify_reservation). No mention of prerequisites like having an active booking.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It hints at return values (room number, key availability) but does not discuss side effects, required authentication, or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. The key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema and annotations. While the description indicates return values, it does not cover error conditions or preconditions like login status or check-in window timing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already well-documented. The description adds a concrete example for 'roomPreferences', providing slight additional context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('complete mobile check-in') and the resource ('upcoming Marriott reservation'). This distinguishes it from siblings like 'get_reservation' and 'select_room'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as 'select_room' or 'modify_reservation'. No prerequisites or conditions for use are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It lists returned information categories but omits critical behavioral details: whether authentication is required, rate limits, error handling, or that the tool is strictly read-only. The name suggests idempotence but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that front-loads the core purpose and lists key details. No wasted words; every phrase adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter and no output schema, the description adequately covers the return categories. However, it does not specify the output format (single object), reinforce that the ID should come from search_hotels, or mention error scenarios. Minor gaps but mostly sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, with a clear schema description. The tool description does not add meaning beyond that—it only reiterates that the parameter can be a code or URL. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves detailed hotel information and enumerates specific categories (description, amenities, policies, check-in/out times, parking, pet policy). This distinguishes it from sibling tools like search_hotels (list) and get_room_options (room-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a search (since hotelIdOrUrl can be a URL from search_hotels), but does not explicitly state when to use it versus alternatives or any prerequisites like being logged in. No exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It states it's a view operation and requires login, but does not disclose potential side effects, rate limits, or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no unnecessary words. Purpose is front-loaded and information is efficiently conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with one optional parameter and no output schema. Could add default sort order or pagination info, but not critical given context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema describes the limit parameter fully (100% coverage). Description adds no extra detail about the parameter, but baseline 3 is appropriate since schema does the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool views past Marriott stays and lists included data (dates, hotels, points, costs). Distinct from siblings like get_reservation (single stay) or status (current stay).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions a prerequisite (logged in) but lacks explicit when-to-use or when-not-to-use guidance. No comparison to sibling tools like search_hotels or get_reservation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. It only hints at a mutation ("book") but fails to specify authorization needs, side effects (e.g., does it hold the room?), or what happens upon success or failure. This is insufficient for an agent to correctly understand behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence states the purpose, the second gives usage sequence. Every word earns its place. Ideal conciseness for a tool description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and moderate complexity (3 params, 2 required), the description provides the essential sequential context but omits return value or confirmation details. It is minimally viable but leaves gaps about what the agent can expect after calling the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions, but the tool description adds valuable context: roomCode and ratePlanCode come from get_room_options, linking them to a prior step. This goes beyond the schema's standalone descriptions, helping the agent understand data dependencies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action "Choose a room type to book" with a specific verb and resource. It also provides sequential context: to be called after get_room_options and before checkout, which distinguishes it from sibling tools like get_room_options and checkout. However, it could more explicitly differentiate from other selection tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to call this after get_room_options and before checkout, providing clear usage context. It does not mention when not to use or list alternatives, but the sequential guidance is effective for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions returns fields (names, brands, ratings, locations, rates) but does not disclose ordering, pagination, authentication requirements, or limitations (e.g., only Marriott hotels). The description is adequate but lacks depth for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with verb and resource. Every sentence adds value: first defines action and input, second defines output. No redundant or missing words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, no output schema, no annotations, and 15 sibling tools, the description is fairly complete for a search tool. It specifies output fields and input scope. However, it lacks details on default ordering, error conditions, and integration with other tools (e.g., after search, select_room).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all 7 parameters. The description adds context by specifying that it returns hotel names, brands, ratings, etc., but does not add meaning to individual parameters beyond what the schema provides. The mention of 'Marriott hotels' adds slight value not in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'Marriott hotels', with specific scope by destination and dates, and lists return fields (hotel names, brands, ratings, locations, nightly rates). It distinguishes from siblings like get_hotel_details or get_room_options, which are more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for initial search, but does not explicitly state when to use this tool vs alternatives like select_room or get_reservation. No exclusions or prerequisites are mentioned, which would help an agent choose correctly among 16 sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses reading env vars and returning a URL, but omits details like success behavior (e.g., token storage) and error handling (e.g., missing env vars).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Purpose first, then behavioral detail. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers essential behavior given no parameters or output schema. Missing post-login state changes (e.g., session handling) but adequate for a simple login tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so the description adds no param info beyond the schema. Baseline 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool logs in to Marriott Bonvoy and specifies it reads environment variables or returns a URL for manual login. This differentiates it from sibling tools like logout.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use before other authenticated actions but does not explicitly state when to use versus alternatives. It lacks guidance on when manual login is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that setting confirm=true completes the redemption and requires user confirmation. Also notes that false/omit returns award rates. Lacks mention of side effects (e.g., irreversible booking), but adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Essential warning is front-loaded. Highly efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description hints return of award rates. Does not describe response format for booking phase (confirm=true). Adequate for a simple tool but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage for 6 parameters. Description adds emphasis on confirm warning and hints about roomCode (lowest-points option). Adds marginal value over schema, meeting baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool books a hotel stay using points and shows award rates. It distinguishes from sibling tools like search_hotels and get_room_options by specifying points redemption and two-phase behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit instruction: 'Set confirm=true only after getting explicit user confirmation.' Also implies two-phase use (view rates then confirm). Does not compare to alternatives directly, but offers clear context for when to proceed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description clearly indicates it is a read-only query by stating it 'returns' data, without any mention of side effects, though it does not discuss authentication or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description sufficiently lists what the tool returns (room names, bed types, prices, cancellation policies, Bonvoy point rates), though it lacks details on pagination or sorting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters are fully described in the input schema with 100% coverage, and the description adds no additional parameter-specific context beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it views room types and rates for a specific hotel and date range, with a specific list of output fields, distinguishing it from sibling tools like search_hotels and select_room.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it should be used after selecting a hotel and date range, but does not explicitly state when not to use it or mention alternatives like search_hotels for initial hotel search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It adequately discloses the core behavior (changing dates/room type) and the confirm flag's effect (preview vs apply). However, it could mention potential side effects (e.g., price changes, cancellation of associated services) or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no filler. The crucial warning about confirm is front-loaded after the purpose statement. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and a key behavioral detail, but given 6 parameters and no output schema, it lacks explanation of what the preview returns or the actual modification's consequences (e.g., price recalculation, impact on existing extras). This leaves gaps for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds critical semantics for the confirm parameter (NEVER set without user confirmation), which goes beyond the schema's own description. This added value justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Change dates or room type for an existing reservation,' clearly specifying the verb (change) and resource (existing reservation). It distinguishes from sibling tools like cancel_reservation (cancellation) and get_reservation (read-only).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a critical guideline: 'Set confirm=true only after getting explicit user confirmation.' While it doesn't explicitly compare to siblings, the sibling list is available, and the usage context is clear enough for an agent to infer when to use modify vs alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full behavioral transparency. It discloses that cancellation fees may apply and explains that confirm=true performs cancellation while confirm=false/omitted returns a preview. It does not mention reversibility or idempotency, which is acceptable for this tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, with zero fluff. The important note about confirmation is front-loaded with 'IMPORTANT', improving usability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description does not explain return values for preview or final cancellation. It also does not mention prerequisites like login status. While mostly complete for core functionality, these gaps reduce overall completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds significant value beyond the schema by providing strong behavioral guidance (NEVER set confirm=true without user confirmation) and hinting at preview behavior. This helps the agent use parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Cancel an existing Marriott reservation' with specific verb and resource. It distinguishes from sibling tools like 'modify_reservation' and 'checkout' by focusing solely on cancellation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for cancellation, but does not explicitly mention when not to use it or compare to alternatives like modify_reservation. It does include a strong usage guideline about user confirmation for confirm=true.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses the critical behavioral difference between confirm=true (charges) and false/omit (preview). It could mention if other side effects occur (e.g., email sending), but the core behavior 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. The first sentence states the purpose, the second adds the crucial usage rule. Perfectly front-loaded and concise for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 params, but only 2 required) and no output schema, the description covers the essential behavior and the critical confirm parameter rule. It could specify what the preview or confirmation output looks like, but it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by emphasizing the confirm parameter's role, but that is already in the schema's description. Other parameters are not elaborated beyond the schema, so no additional semantic improvement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Complete a Marriott hotel booking' which is a specific verb+resource. It also distinguishes between preview and actual completion based on the confirm parameter, setting it apart from sibling tools like search_hotels or select_room.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use guidance with the IMPORTANT note: 'Set confirm=true only after getting explicit user confirmation. Without confirm=true, returns a booking preview instead of charging.' This clearly instructs the agent on the correct usage pattern.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description carries full burden. Discloses authentication requirement and lists what the tool returns. Does not mention error handling or side effects, but for a read-only tool with no parameters, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states the main action and lists outputs, second adds auth requirement. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema, but description enumerates return fields. Could mention error conditions (e.g., not logged in) but missing that is minor. Overall sufficient for a simple read-only tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline is 4. Description adds no param info, but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it checks Marriott Bonvoy loyalty status and lists specific data points (points, tier, nights, progress, activity). Distinguishes from siblings like get_reservation (specific booking) and status (possibly generic).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly requires being logged in. Does not contrast with sibling tools like 'status', but purpose is clear enough that an agent would know to use this for loyalty status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It states 'Requires being logged in' and implies read-only behavior by saying 'Retrieve' and 'Returns upcoming reservations'. This is sufficient for a simple retrieval tool, though an explicit read-only hint would be ideal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loaded with purpose. Every sentence provides essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional param, no output schema), the description is complete: it states the action, prerequisites, and the two result types. It does not explain return values, but retrieval tools are generally self-explanatory.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for the only parameter. The description adds context beyond the schema: 'Omit to get all upcoming reservations' clarifies the dual behavior. This adds value beyond the basic schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve existing Marriott reservation details', specifying the resource (reservation) and action (retrieve). It distinguishes from siblings like cancel_reservation, modify_reservation, etc., which are mutation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a prerequisite ('Requires being logged in') and explains the two modes: retrieve all upcoming reservations or a specific one by confirmation number. However, it does not explicitly tell when to avoid using this tool compared to alternatives like get_stay_history or status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a read-only behavior (checking status) without contradicting any structured data. However, it does not specify the return format or whether the session info includes detailed data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and outcome. Every sentence is necessary and contributes to understanding, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is largely complete. It covers purpose and usage context. A minor gap is the lack of detail on the session info returned, but for a zero-parameter status check, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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. As per the guideline, baseline is 4. The description adds no parameter details, but none are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check Marriott login status and Bonvoy session info.' It also distinguishes from sibling tools like login and logout by specifying its use for verification before other actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage guideline: 'Use this to verify authentication before performing other actions.' This effectively tells the agent when to use the tool, though it does not explicitly exclude alternative tools like get_bonvoy_status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses the behavioral effect: it clears session and cookies, which indicates destructive action on authentication state. This provides sufficient transparency for a logout tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The description is front-loaded with the core action and purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter tool with no output schema or annotations, the description fully covers the purpose and effect. No additional context is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema coverage is 100%. The description adds no parameter details, but none are needed. Baseline 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Clear', 'log out', 'reset') and the resource ('saved Marriott session and cookies'). It distinguishes itself from sibling tools like 'login' by specifying the action of clearing authentication state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('to log out or reset authentication state'). While it does not mention when not to use it, the context is clear and no alternatives are needed for this simple action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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