1Stay Hotel Booking

Server Quality Checklist

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Latest release: v1.2.0
Disambiguation5/5
Each tool has a clearly distinct purpose: search_hotels finds properties, get_hotel_details retrieves rates, book_hotel creates bookings, cancel_booking removes them, lookup_booking and get_booking retrieve booking info with different access levels, resend_confirmation emails confirmations, and search_tools lists available tools. No two tools overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., book_hotel, cancel_booking, search_hotels). The naming is predictable and uniform across the entire set.
Tool Count5/5
With 8 tools, the server covers the main hotel booking workflow (search, details, book, cancel, lookup, resend) plus a meta-tool for discovery. This is well-scoped and not excessive or insufficient for the domain.
Completeness3/5
The core operations are covered (search, read, create, delete), but there is no tool to modify an existing booking. The documentation suggests a workaround (re-book then cancel), which is an obvious gap. A modify/update tool is missing, reducing completeness.
Average 4.6/5 across 8 of 8 tools scored. Lowest: 4/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 3 community issues answered or closed in the last 6 months
- 6 commits in the last 12 weeks
- Last stable release on May 26, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under Unlicense - libtelnet variant.
This repository includes a README.md file.
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context: payment flows (guest pays hotel, 1Stay fee added), loyalty points eligibility, and room type clarifications (run-of-house, suite definition). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is brief, front-loaded with main purpose, and uses separate paragraphs for payment and room notes. Each sentence adds value, though the room type explanations could be slightly trimmed. No wasted words.
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?
Despite lacking an output schema, the description lists all return elements (room types, rates, amenities, policies, rate_codes) and adds payment and eligibility context. For a simple 5-parameter tool, this is comprehensive.
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% with each parameter descriptively named. The description adds no extra meaning beyond the schema for parameters; it only reiterates date format and defaults, which the schema already includes. 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 rates and room details for a specific hotel, enumerating return fields (room types, live rates, amenities, cancellation policies, rate_codes) and explicitly linking rate_codes to the sibling tool book_hotel, which distinguishes it from search_hotels and booking tools.
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 when to use (before booking, to get rate_codes) but does not explicitly state when not to use or compare with alternatives like search_hotels for listing hotels. The sibling list exists but no direct guidance in description.
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?
Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description adds value by disclosing that the guest pays the hotel directly, the hotel provides the confirmation number, and loyalty points apply. This contextualizes the search results beyond the safety profile, though it does not cover rate limits or auth requirements.
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 three sentences: the first clearly states the function and output, the second and third provide behavioral context about payment and loyalty. It is front-loaded, concise, and every sentence adds value without redundancy.
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 has 13 parameters and no output schema, the description covers core functionality and payment details. It does not mention pagination behavior even though cursor/search_id parameters exist, nor does it explain default values for guests_per_room or rooms. However, annotations and schema fill some gaps, making it fairly complete for a search tool.
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%, with detailed parameter descriptions (e.g., chain_code, radius, pagination fields). The description adds payment context but does not elaborate on parameter usage beyond what the schema provides. Baseline score of 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches and books hotels by location and dates, and returns available properties with nightly rates across various brands, distinguishing it from sibling tools like book_hotel (for actual booking) or get_hotel_details (for specific details). It uses specific verbs ('Search and book') and resources ('hotels'), making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching hotels by location and dates, but does not explicitly state when to use this tool versus alternatives like book_hotel or get_hotel_details. It provides context about what it returns but no direct exclusions or scenario comparisons. Clear but could be more explicit.
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?
Annotations (readOnlyHint: false, destructiveHint: false, openWorldHint: true) indicate a non-read, non-destructive but open-world operation. The description reinforces this by stating it sends an email and explains the email address handling. It adds context beyond annotations by specifying the side effect of sending and the optional re-routing.
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 concise with three sentences, front-loaded with the main purpose, and includes necessary usage details without extraneous information. Every sentence adds value.
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 two-parameter tool with no output schema, the description covers the primary use case, explains the optional parameter, and mentions a prerequisite tool (lookup_booking). It is sufficiently complete for an agent to use correctly.
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 both parameters. The description adds practical use-case detail for updated_email (typo or inaccessible email), which is helpful but not essential beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 action ('Resend a hotel reservation confirmation email') and the specific resource (confirmation email). It also distinguishes from sibling tools by instructing to use after verifying identity with lookup_booking, providing a clear sequential context.
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 advises using this tool after looking up the guest's identity, and explains when to use the updated_email parameter (typo or inaccessible email). While it doesn't list alternative tools for when not to use it, the context is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive and idempotent hints. The description adds critical context: the action cannot be undone, non-refundable rates forfeit full amount, and confirmation is emailed. This goes beyond annotations without contradiction.
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?
Five sentences with clear front-loading of purpose. Each sentence adds value, with no redundancy or fluff. Well-organized.
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?
Given no output schema and moderate complexity, the description covers cancellation policy, consequences, and best practices for date changes. It is complete for agent guidance.
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 description coverage is 100%, so baseline is 3. The description lists required fields but does not add extra detail beyond what the schema provides (e.g., format, examples).
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 cancels a hotel reservation, listing required fields. It distinguishes from sibling tools like book_hotel and get_booking 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 Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions when to use (cancellation), warns about non-refundable rate forfeiture, and provides an alternative pattern for date changes to avoid losing the room. Also advises ensuring guest awareness of cancellation policy.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations show readOnlyHint=true, destructiveHint=false. Description adds behavioral context: 'no identity verification' and lists return fields. No contradiction.
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 for main purpose, one sentence for usage guidance. No fluff, front-loaded with key information.
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?
Single parameter, no output schema, but description covers what is returned, parameter format, and provides alternative tool. Fully adequate for the tool's simplicity.
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% with description for booking_id. Description merely restates the parameter's purpose and gives example format, adding minimal value beyond 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 'Look up a reservation by booking ID (stk_bk_xxxx) or hotel confirmation number. Returns full booking details...' It specifies the verb 'look up', the resource 'reservation', and lists return fields. It also distinguishes from sibling 'lookup_booking' by noting identity verification.
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 says 'Developer-level lookup tool with no identity verification' and directs to 'use lookup_booking which enforces identity verification' for guest-facing lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description and annotations align perfectly. Annotations indicate readOnlyHint: true and destructiveHint: false, and the description adds that the tool lists and filters tools. No contradictions, and the behavior is fully disclosed.
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 with no unnecessary words. Front-loaded purpose and immediately actionable. Every word earns its place.
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 list tool with one optional parameter and no output schema, the description is fully adequate. It tells the agent exactly what the tool does and how to use it.
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 baseline 3. The description adds value by providing examples of acceptable keyword values and stating the effect of omitting keyword, going beyond the 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 it lists available 1Stay hotel booking tools and can filter by keyword. It distinguishes itself from sibling tools like book_hotel and cancel_booking by being a meta-tool for discovery.
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 guidance on filtering by keyword with examples ('search, book, cancel, details') and says to omit keyword to list all. Lacks explicit when-not-to-use or alternatives, but given its meta-purpose, the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and readOnlyHint=false. The description adds that payment is handled externally via checkout URL, no need to collect payment info, a booking fee is added, and loyalty points apply. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loaded with the main action, and uses concise sentences without redundancy. Every part adds value.
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?
Given 8 parameters and no output schema, the description covers key behaviors: return type, payment flow, prerequisite, and idempotency. It is complete enough for correct tool invocation.
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 baseline is 3. The description adds context for external_reference_id (idempotency and retrieval) and mentions rate_code expiration. However, most parameters are adequately described in the 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 'Book a hotel room' and explains it returns a secure checkout URL. It distinguishes from siblings like cancel_booking and get_hotel_details by specifying the booking action and prerequisite (rate_code).
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?
Provides explicit instructions: do not collect payment info, requires rate_code from get_hotel_details which expires in ~15 min, and suggests calling get_hotel_details again if expired. Also mentions alternatives indirectly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context beyond the annotations, including the identity verification process, required prerequisites, and that it returns confirmation number and booking summary. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. The first sentence conveys the core purpose, followed by clear prerequisite bullet points and then related tool references. Every sentence adds value, and the information is front-loaded.
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?
The description is complete for the tool's complexity: it covers all six parameters, explains the verification requirements, and states the return value (confirmation number and booking summary). No output schema is present, but the description adequately sets expectations.
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%, but the description adds significant meaning: it explains that first_name and last_name are required, and at least one of confirmation_number, email, or last_four_card (with check_in_date) must be provided as a verification factor. This goes beyond the schema's field descriptions.
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: 'Look up a reservation by verifying the guest's identity. Returns the confirmation number and booking summary.' It specifies the action (look up) and resource (reservation), and distinguishes from sibling tools like cancel_booking and resend_confirmation by mentioning them as alternatives.
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?
The description provides explicit when-to-use and when-not-to-use guidance: it lists prerequisites (guest full name and at least one verification factor) and states that if the guest cannot provide any verification, the reservation cannot be looked up. It also mentions alternatives: use resend_confirmation after identity verification or cancel_booking.
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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