timergy
Server Quality Checklist
Latest release: v0.2.1
- Disambiguation5/5
Each tool has a distinct purpose: creating polls, getting info, voting, viewing results, finalizing. No overlap.
Naming Consistency5/5All tools follow a consistent verb_noun_snake_case pattern, e.g., create_poll, get_results.
Tool Count5/5Five tools cover the essential poll lifecycle without being too many or too few.
Completeness4/5Covers the main workflow from creation to finalization. Missing update/delete operations, but not critical for scheduling polls.
Average 4.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explains the tool returns voting results per time slot but does not detail the response format, error conditions, or any side effects. It provides a high-level outcome but lacks specifics needed for full behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first sentence states the purpose, and the second provides usage guidance. Every sentence is valuable, and there is no redundancy or waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter and no output schema, the description provides adequate context: purpose, when to use, and subsequent action. It lacks a detailed description of the return format, but the mention of 'showing who voted yes/maybe/no for each time slot' gives a sufficient high-level picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description does not add significant new meaning about the pollId parameter beyond what the schema already provides. The description gives context on what the results contain, but that relates to output semantics rather than the parameter itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'voting results for a Timergy poll', and specifies it shows who voted yes/maybe/no for each time slot. It effectively distinguishes the tool from siblings like create_poll and finalize_poll.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this after participants have voted' and provides a use case for determining the most available slot. It also guides the next step: call finalize_poll with the optionId. However, it does not explicitly compare to alternatives or mention when not to use it.
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 carries the burden. It discloses that the tool returns a shareable URL and admin passphrase, and that the passphrase is remembered for finalize_poll. It does not mention authorization or rate limits, but the behavior is adequately described for a creation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative but slightly long. It is structured with a workflow list at the end, which is helpful. Some sentences could be condensed, but overall it earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 6 parameters, full schema coverage, and no output schema or annotations, the description covers the key aspects: purpose, required inputs, workflow, return values. It is complete enough 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.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 6 parameters. The description adds value by recommending 2-5 options, specifying ISO 8601 with timezone, and mentioning the passphrase. This goes beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a Timergy scheduling poll like Doodle, specifying the verb 'create' and resource 'poll'. It distinguishes from sibling tools by mentioning the workflow with finalize_poll and get_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear workflow: create_poll -> share URL -> wait for votes -> get_results -> finalize_poll, and notes the passphrase is remembered for finalize_poll. However, it does not explicitly state when not to use the tool or list 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?
No annotations are provided, so the description carries full burden. It transparently states the tool returns specific fields (title, status, deadline, location, time slots with option IDs) and explicitly says votes are not returned. Could mention idempotency or lack of side effects, but description is adequate for a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with purpose. Each sentence serves a distinct role: stating function and exclusion, listing returned data, and providing usage guidance. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter, no output schema, and no annotations, the description is fairly complete. It covers what is returned and how to use the results. Could mention error conditions or prerequisites, but overall sufficient for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters, with pollId described as 'Poll UUID'. The description adds minimal extra meaning beyond stating that pollId is used to retrieve optionId values. Baseline 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves poll metadata and time slot options, explicitly excluding votes. It uses specific verbs and resources, and differentiates from sibling tools like get_results and vote_on_poll.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use this tool to obtain optionId values for vote_on_poll or finalize_poll, and directs to get_results for vote details. This provides clear when-to-use and when-not-to-use guidance with named 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?
Description discloses that a unique voter token is auto-generated per voter name and that resubmission updates previous votes. With no annotations provided, this adds valuable behavioral context about idempotency and auto-generation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Five sentences packed with essential information: purpose, prerequisite, mapping, behavior. No redundant words; well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers prerequisite, vote mapping, and update behavior. Lacks mention of return values (no output schema), but for a voting submit tool the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already covers all parameters with descriptions (100% coverage). Description adds context that optionIds come from get_poll and explains the availability enum values, enriching meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Submit votes on a Timergy poll' as the main action. Differentiates from siblings by mentioning prerequisite get_poll to retrieve optionIds, and explains the vote mapping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call get_poll first to get optionIds, and notes that resubmitting with same voter name updates votes. Does not explicitly mention when not to use this tool versus finalize_poll, but the guidance is clear enough.
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?
Discloses important side effects: locks the poll and notifies participants with email. Explains passphrase auto-save behavior and manual fallback. Since no annotations provided, description fully handles 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each serving a distinct purpose: main action, prerequisite, passphrase detail, and side effects. No wasted words; information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all necessary aspects for a tool with 3 parameters and no output schema: purpose, prerequisite, parameter details, passphrase handling, and consequences. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema already has 100% description coverage for all three parameters, so baseline is 3. Description adds meaningful context: directs to use get_results for optionId and clarifies passphrase auto-save vs manual provision.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states 'Finalize a poll by picking the winning time slot', which clearly conveys the verb and resource. Distinguishes itself from sibling tools like create_poll, get_results, and vote_on_poll by specifying the action of finalizing and referencing get_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear prerequisite by advising to call get_results first to find the best optionId. Also explains when to manually provide the passphrase (if server restarted). Lacks explicit when-not-to-use, but context is sufficient.
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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