GenTech Agent Kit
Server Quality Checklist
Latest release: v0.3.2
- Disambiguation2/5
The tool set spans three unrelated domains (crypto, output enforcement, Pika creative), but within the Pika subdomain, pika_generate subsumes the functionality of pika_app_sizzle, pika_build_brand, and pika_explainer, causing ambiguity. Additionally, output_enforcer tools are distinct but weakly connected to the rest.
Naming Consistency2/5Naming conventions are inconsistent: some tools use verb_noun (get_trending), others use noun_verb (output_enforcer_clear), and the Pika tools mix brand prefix with various patterns (nouns, verbs, phrases). No unified pattern emerges.
Tool Count3/58 tools is a reasonable number, but the set feels fragmented across unrelated domains. The Pika subdomain occupies 5 tools, which is too many given the redundancy, while the other domains have minimal coverage. The count is borderline appropriate.
Completeness2/5Each domain is incomplete: crypto only offers trending data with no CRUD; output enforcement lacks configuration or detailed reporting; Pika tools are redundant with pika_generate covering most use cases. Missing essential operations like update, delete, or search across domains.
Average 3.4/5 across 8 of 8 tools scored. Lowest: 2.5/5.
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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description fails to disclose any behavioral traits such as creation of persistent resources, idempotency, authentication needs, or rate limits. The listing of skills does not explain what each skill does or how the tool behaves.
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 short and front-loaded with purpose. The list of skills is lengthy but necessary for this tool. The instruction to pass params as JSON string is clear. However, the list could be partially moved to the schema as an enum.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 20 skills and lack of parameter documentation, the description is incomplete. It does not provide enough context for an agent to correctly invoke the tool, such as what each skill does or how to format params. The presence of an output schema reduces the need for return details, but the description still lacks essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate but only states that the 'skill' parameter is a listed skill and 'params' is a JSON string. It does not explain the structure or allowed keys for the params JSON, leaving the agent without sufficient guidance on parameter values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates content using a Pika creative skill and lists 20 specific skills. However, it does not differentiate this tool from its sibling tools like pika_app_sizzle or pika_build_brand, which may serve similar purposes for individual skills.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternative Pika-specific siblings. It merely lists skills without context on appropriate usage or prerequisites.
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 present. The description indicates creation of multiple brand assets but does not disclose whether the tool is stateful, requires authentication, or has any side effects. For a generative tool, this is vague.
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 a single, efficient sentence that front-loads the action ('Generate a complete brand identity') and lists key outputs. Every word serves a purpose without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and presence of an output schema, the description covers the basic intent. However, it omits usage context, parameter clarification, and behavioral notes, making it merely adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'brief' has no schema description (0% coverage). The description mentions 'product brief' but does not explain required format, content, or length, leaving ambiguity for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it generates a complete brand identity from a product brief, listing components like strategy and tone of voice. However, it does not differentiate from sibling generative tools like pika_generate, which could perform similar tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description implies usage from a product brief but offers no exclusions or comparisons to siblings.
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 full responsibility for behavioral disclosure. It only describes the transformation input-output without detailing side effects, prerequisites, limits, or constraints. This minimal transparency leaves the agent uninformed about how the tool operates.
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 a single sentence of 13 words, extremely concise and to the point. Every word serves a purpose, making it easily parsable with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers basic input-output. However, it lacks context on video style, length, or quality guarantees. Given the presence of many sibling tools, more differentiation detail would improve completeness.
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 has 0% description coverage for its single 'url' parameter. The description adds meaning by suggesting the URL can be a website, GitHub repo, or written brief, which is helpful but vague. It partially compensates for schema lack but does not specify format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: turning a URL, GitHub repo, or written brief into an explainer video. It specifies the input types and output format, effectively distinguishing it from potential sibling tools. However, it doesn't fully align with the schema (only 'url' parameter) and could be more precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like pika_app_sizzle or pika_generate. Without explicit when-to-use or when-not-to-use instructions, the agent lacks context for selection among sibling tools.
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 fully disclose behavioral traits. It does not specify if the operation is read-only, whether authentication is needed, rate limits, pagination, or what constitutes a violation. The description is insufficient for a tool with zero annotation coverage.
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 concise, using a clear structure with a one-line summary followed by an Args section listing each parameter. Every sentence adds value, and there is no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 optional params, output schema exists). The description covers the basic purpose and parameters but lacks details on output format, limits, or behavior when no violations are found. It is adequate but not fully complete given the availability of an output schema.
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?
The schema has 0% description coverage, so the description compensates by explaining both parameters: tool_name (optional, empty returns all) and hours (default 24). This adds meaningful semantics beyond the raw schema, clarifying defaults and filtering behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves recent validation violations with optional filtering by tool name and time window. This distinguishes it from sibling tools like 'output_enforcer_breakers' (likely different violation types) and 'output_enforcer_status' (status). However, it does not explicitly state that it returns a list, which would enhance clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context (validation violations) and mentions filtering options, but lacks explicit guidance on when to use this tool versus alternatives like 'output_enforcer_clear' or 'output_enforcer_breakers'. No exclusions or prerequisites are provided.
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 full burden. It discloses the cost ($0.001 USDC/query) and implies the kind parameter values. However, it does not detail side effects, rate limits, idempotency, or behavior on invalid input.
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?
Two sentences front-load the action and options, with no wasted words. Efficient and scannable.
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?
The tool is simple with one optional parameter and an output schema. The description covers the core purpose and valid options. However, it does not hint at the structure of the returned data (e.g., token names, prices), which could be useful given siblings like get_quote offer more detail.
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?
The input schema has 0% description coverage, but the description compensates by listing valid options for the 'kind' parameter (gainers, losers, most_visited, latest). This adds meaning beyond the schema default of 'latest', though the description could clarify what each option returns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves trending crypto data and lists specific options (gainers, losers, most_visited, latest). It distinguishes the tool's focus on 'trending' data from siblings like get_listings, though it does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as get_dex_pairs or search_token. It mentions cost but does not clarify context or exclude cases.
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 carries the full burden of disclosure. It specifies the output duration (15 seconds) and accepted source types, but omits behavioral traits such as authentication requirements, processing time, error handling, or any side effects. This is insufficient for a tool with no other behavioral hints.
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 a single, well-structured sentence of 14 words. It is front-loaded with the core action and resource, with no redundant or superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter, an output schema (not shown but exists), and simple behavior, the description covers the key input types and output duration. However, it lacks usage guidelines and behavioral transparency, leaving gaps for an agent to make fully informed decisions.
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?
The input schema provides only a 'url' parameter with no description (0% coverage). The description compensates by clarifying that the URL can be an app store link, product screens, or GitHub repo URL, adding meaningful context beyond the raw 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?
The description clearly states the verb 'Create', the resource '15-second launch video', and the source types 'app store link, product screens, or GitHub repo URL'. This distinguishes it from sibling tools like pika_explainer or pika_build_brand, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus its siblings (e.g., pika_explainer, pika_build_brand). No explicit 'when-not-to-use' or alternative recommendations are given, leaving the agent to infer usage context.
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 provided; description only states listing of skills. It is straightforward but lacks behavioral details such as auth requirements or data freshness. Adequate given tool simplicity.
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?
Single sentence efficiently conveys purpose and examples with no extraneous text.
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?
Tool has zero parameters and an output schema; the description fully captures its listing functionality with examples.
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?
No parameters; schema coverage is 100% (empty). Baseline 4 as no extra info needed beyond empty 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?
The description uses 'List available Pika creative skills' with specific verb+resource and lists concrete examples, clearly distinguishing it from generation or other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like pika_generate or other pika tools; it only describes what it lists.
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?
With no annotations, the description carries the full burden. It discloses destructive behavior (clear) and mentions it affects both memory and disk, but lacks details on required permissions, reversibility, or side effects. The return count is positive.
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 extremely concise (12 words, two sentences) and front-loaded with the action and scope. Every word earns its place.
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?
For a simple tool with no parameters and an output schema, the description is complete: it states what the tool does, what it affects, and what it returns. No additional context is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description cannot add meaning beyond the schema. Schema coverage is 100% by default (empty schema). The baseline for 0 parameters is 4, and the description suffices.
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 action ('Clear'), the resource ('all violation records'), the scope ('memory + disk'), and the return value ('Returns count cleared'). It distinguishes itself from sibling tools like 'output_enforcer_breakers' and 'output_enforcer_status' by specifying a clear operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for resetting violation records but does not explicitly state when to use this tool versus alternatives, nor does it provide when-not scenarios. No guidance on prerequisites or context.
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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