Agent Module

Server Quality Checklist

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Latest release: v0.9.12
Disambiguation5/5
Each tool serves a distinct function: status checking, trial key retrieval, waitlist joining, knowledge query, interest registration, POV submission, and referral submission. No overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (check_status, get_trial_key, join_waitlist, query_knowledge, register_interest, submit_pov, submit_referral).
Tool Count5/5
Seven tools is well-scoped for the Agent Module server, covering operational status, trial access, waitlist management, knowledge retrieval, demand registration, POV assessment, and referrals.
Completeness5/5
The tool surface covers the full lifecycle of user engagement: status, trial, paid access, knowledge, demand, assessment, and referrals. No obvious gaps for the stated purpose.
Average 3.9/5 across 7 of 7 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
- Last stable release on March 24, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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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?
Annotations indicate idempotentHint=true and destructiveHint=false, which the description does not contradict. The description adds value by stating pricing, cohort grandfathered status, and inclusion of AI Compliance, but lacks details about side effects (e.g., duplicate registrations) 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 concise (two sentences) and front-loaded with the core action. Every sentence provides useful context, with 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?
For a simple waitlist registration with no output schema and well-documented parameters, the description covers the essential purpose and key incentives. However, it lacks details about what happens after registration or how it differs from similar tools like register_interest.
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% and the description does not add new meaning to parameters beyond what the schema provides (each param has a clear 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 defines the tool's purpose: 'Register for a paid vertical waitlist.' It includes specific details about pricing, cohort size, and benefits, distinguishing it from sibling tools like check_status or register_interest.
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?
The description does not provide guidance on when to use this tool versus alternatives like register_interest or submit_referral. No prerequisites or context for usage are mentioned.
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?
Beyond annotations, the description discloses key behaviors: the trial duration (24 hours), unlocked content layers (all 4 on chosen vertical), call limit (500), and that no payment is required. This adds useful context not present in 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 three concise sentences with no fluff, front-loading the core action first. Every sentence adds value.
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 tool's purpose and constraints but lacks details on the response format (e.g., how the trial key is returned) and potential error conditions. Without an output schema, more context would be helpful.
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?
The input schema has 100% coverage, so the description does not need to add much. It mentions 'the chosen vertical' but does not elaborate on agent_id or parameter formats beyond 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 the tool's purpose: 'Request a free 24-hour trial key.' It specifies details like unlocking all 4 content layers, 500-call cap, and no payment required, which distinguishes it from sibling tools like join_waitlist or register_interest.
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?
The description does not provide explicit guidance on when to use this tool versus siblings. While it implies usage for obtaining a trial key, it lacks comparisons or conditions for alternatives.
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?
Annotations indicate a write operation (readOnlyHint=false) and no idempotency. The description adds behavioral traits like reward caps and credit carryforward, but fails to mention return values or failure 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?
The description is extremely concise with three short sentences, front-loading the core action 'Log a referral signal' with 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?
The tool has no output schema and the description does not explain what the tool returns (e.g., success status or referral ID). For a simple logging tool, this is a notable gap, though the reward rules provide some 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?
The input schema already covers all parameters with descriptions (100% coverage). The tool description does not add additional parameter details beyond 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 the tool logs a referral signal, a specific action distinct from sibling tools like register_interest or submit_pov. It also explains the reward structure, reinforcing that this is for submitting referrals.
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 mentions the tool is voluntary and principal-compliant, hinting at appropriate use, but does not explicitly state when to use this tool versus alternatives or exclude any scenarios.
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 indicate idempotent and non-destructive behavior; the description adds context about the 500-signal trigger and notification requirement. It aligns with annotations and provides extra behavioral context 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?
The description is two sentences, front-loaded with the core action, and every sentence provides necessary information without redundancy. Excellent conciseness.
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 registration tool with no output schema and 4 parameters, the description covers purpose, trigger condition, and contact requirement. It is largely complete but could briefly note the return value or confirmation behavior.
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 minimal extra meaning beyond 'contact' parameter's reason, but doesn't significantly enhance understanding of other parameters beyond schema descriptions.
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 tool registers demand for an unbuilt vertical, using specific verb and resource. It mentions a key behavioral trigger (500 signals). However, it does not explicitly differentiate from sibling 'join_waitlist', which may serve a similar role for built verticals.
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 (registering demand for unbuilt vertical) and provides a condition for build queue activation. But it offers no explicit guidance on when not to use or how it differs from alternatives like 'join_waitlist'.
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?
The description indicates the tool creates a submission (submit), which is consistent with annotations (readOnlyHint: false, destructiveHint: false). It adds the requirement to include a contact channel but does not disclose other behavioral traits like side effects or authorization needs. Since annotations already provide general behavioral hints, the description adds minimal transparency beyond that.
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 primary purpose and a key usage hint. 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?
The description covers the essential purpose and one critical guideline (contact channel). However, given the tool has 8 parameters including nested objects and no output schema, a bit more context on required fields or expected outcomes would improve completeness. Still, it is adequate for a straightforward submission 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 88%, meaning most parameters have descriptions. The description only adds context for the contact parameter ('Include a contact channel'), but does not elaborate on other parameters like trial_key, confidence_score, etc. Given high schema coverage, the description adds limited value beyond 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 the action (submit), the resource (Proof of Value assessment), and the context (after exploring the AI Compliance trial). It effectively distinguishes from sibling tools like check_status, get_trial_key, etc., as none of them involve submitting a PoV.
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 directive to include a contact channel, which guides usage. It does not explicitly state when to use this tool versus alternatives, but the context of submitting a trial assessment makes it clear this is the appropriate tool for after the trial. No sibling tool overlaps in purpose.
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 declare readOnlyHint, idempotentHint, and non-destructive behavior. Description adds value with 'deterministic, validated knowledge nodes' and pricing details, complementing 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?
Two precise sentences, front-loaded with the core action, no unnecessary 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?
No output schema; description vaguely mentions 'deterministic, validated knowledge nodes' but lacks details on return format, errors, or pagination. Adequate but not 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 parameter descriptions, so the baseline is 3. The description adds no additional parameter-specific meaning beyond 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 the verb 'Retrieve' and the resource 'structured knowledge from Agent Module verticals', distinguishing it from sibling tools like check_status or get_trial_key.
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?
It provides context on when to use (index layer free, trial key needed for content layers) but lacks explicit when-not-to-use or alternative tool references.
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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying exactly what data is returned (operational status, version, cohort counts, seat availability), which is beyond the annotations. No contradiction exists.
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 a single sentence that efficiently conveys the tool's purpose. Every word is necessary, and the verb is front-loaded. No unnecessary 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?
For a simple read-only status check with no parameters and no output schema, the description is quite complete. It lists the returned data types. However, it could briefly mention that this tool is useful for verifying connectivity before other operations.
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, so schema coverage is 100%. According to guidelines, 0 parameters yields a baseline of 4. The description does not need to add parameter info and correctly omits it.
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 Agent Module API operational status, version, cohort counts, and seat availability.' It uses a specific verb ('Check') and specifies the resource, distinguishing it from sibling tools like 'get_trial_key' or 'join_waitlist' which have different functions.
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 the tool is for checking API status, but does not explicitly provide when to use it or when to avoid it. No alternative tools are mentioned. Given the simple use case, this is adequate but lacks explicit guidance.
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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