zyta-mcp

by blanck1945

Overview Schema Related Servers Score Discussions

TypeScript

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Server Quality Checklist

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Latest release: v1.2.0
Disambiguation4/5
Most tools target distinct resources and actions. However, 'zyta_jurisprudencia_search' and 'zyta_minerva_buscar_fallos' both search for legal rulings, causing slight overlap. Descriptions help clarify differences, but some ambiguity remains.
Naming Consistency2/5
Naming is inconsistent: mixes English ('search', 'list', 'get') and Spanish ('buscar', 'registrar'), with varying structures (e.g., 'expediente_get' vs 'expedientes_list', and 'whoami' as an outlier). No consistent verb_noun pattern.
Tool Count5/5
With 14 tools, the count is well-scoped for a legal MCP server. It covers authentication, judicial processes, jurisprudencia, Minerva, trademarks, and user info without feeling excessive or thin.
Completeness4/5
The tool set covers core workflows: auth, judicial expedient management, jurisprudencia search, Minerva consultation, trademarks, and user info. Minor gaps exist (e.g., no update/delete for expedients, no trademark management beyond search), but they are not critical.
Average 3.8/5 across 14 of 14 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on June 20, 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.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It only mentions a GET request (implying read-only) but omits details on pagination, rate limits, response format, or any side effects. Insufficient for safe agent invocation.
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?
The description is a single line with the purpose and endpoint, which is concise and front-loaded. However, it is extremely brief and could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters (including dates, pagination, class filters) and no output schema, the description lacks context on how to use these together or what results look like. It is inadequate for a parameter-rich 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%, so parameter descriptions are present in the schema. The tool description adds no additional meaning beyond the schema. Baseline of 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 action ('búsqueda de marcas' = search trademarks) and the resource ('histórico de boletines INPI' = INPI bulletin history). It also provides the HTTP endpoint, differentiating it from sibling tools like jurisprudencia or judicial searches.
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 versus alternatives, nor any prerequisites, context, or exclusions. It simply states the function without aiding decision-making.
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, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or side effects. It does not explicitly state that this is a read-only operation, leaving assumptions to the agent.
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?
The description is very short (one sentence and endpoint), front-loading the purpose. It is efficient but could include a brief note on typical use or response structure without becoming verbose.
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 tool's simplicity (1 parameter, no output schema, no annotations), the description is minimally adequate. It explains the tool's core purpose but omits details about the response format or what 'actuaciones' entails, which could aid the agent.
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% (one parameter with description), so baseline is 3. The description adds no extra meaning beyond the schema; it only restates the parameter implicitly via the endpoint.
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 'Detalle de un expediente judicial con actuaciones' (detail of a judicial file with actions) and includes the HTTP method and endpoint. It uses a specific verb (detail/get) and resource (expediente judicial), distinguishing it from siblings like list.
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 versus alternatives like zyta_judicial_expedientes_list or zyta_judicial_cursor_registrar_actuacion. The description lacks context about prerequisites or typical scenarios.
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 provided, the description carries the full burden. It discloses latency and rate limits, which is helpful. However, it does not mention authentication needs, side effects, or response characteristics.
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?
The description is concise (one sentence plus endpoint) and front-loads key information. It could be more informative without being verbose.
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 tool's complexity (search with constraints), the description covers latency and rate limits but lacks details on response format, error handling, or optimization tips. No output schema exists to supplement.
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% for the single parameter 'query', which has a basic description. The tool description adds no further semantics, such as expected format or examples.
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 purpose: search for rulings and jurisprudence in official sources. It includes the HTTP method and endpoint. However, it does not differentiate from the sibling tool 'zyta_minerva_buscar_fallos', which appears similar.
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 performance constraints (latency up to ~30 s, rate limit of 5 req/min) but provides no guidance on when to use this tool versus alternatives, nor any prerequisites or best practices.
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?
Al no haber anotaciones, la descripción carga con la transparencia. Solo indica que no genera respuesta IA y el endpoint HTTP, pero omite detalles sobre formato de salida, paginación, límites o requisitos de autenticación.
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?
Dos oraciones sin redundancia, información clave al inicio: verbo, recurso y propósito. No incluye relleno.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No hay esquema de salida y la descripción no explica qué devuelve la herramienta (ej. lista de fallos, metadatos). Falta información esencial para que un agente entienda el resultado.
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?
La cobertura del esquema es del 100%, por lo que la línea base es 3. La descripción no añade significado significativo más allá del esquema, que ya describe 'query' y 'top_k'.
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?
La descripción especifica que busca fallos en la base jurisprudencial sin generar respuesta IA, diferenciándose claramente de herramientas similares como 'zyta_minerva_consultar' y 'zyta_jurisprudencia_search'.
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?
Indica que es útil para explorar jurisprudencia antes de una consulta completa, proporcionando contexto de uso. Sin embargo, no menciona explícitamente cuándo no usarlo o alternativas.
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 alone disclose behavioral traits. It does state 'No muestra el token', which is a key safety disclosure. However, it omits details about the response format (e.g., boolean, object), error conditions (e.g., if no configuration exists), and whether the tool has side effects. Given the absence of annotations, the description is insufficiently 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?
The description is a single sentence that efficiently conveys the purpose and a key behavioral note. It is front-loaded with the main action ('Indica si') and contains no redundant words. Every word serves a purpose.
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 is adequate for a simple read-only tool but lacks completeness because there is no output schema and the description does not hint at the return value structure or possible states. For example, it does not mention what 'indica' produces (boolean? status object?). Without annotations or output schema, the description should be more thorough.
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 the schema coverage is 100%. Per rubric, 0 parameters have a baseline score of 4. The description adds meaning beyond the empty schema by explaining what the tool checks (token status, base URL) and what it does not reveal (token itself). No further clarification 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: to indicate whether the MCP has a configured token and the base URL. The verb 'Indica' combined with the specific resource ('token configurado', 'URL base') makes the action unambiguous. This distinguishes it from sibling tools like zyta_login (which performs login) and zyta_whoami (which shows current user).
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 does not explicitly state when to use this tool versus alternatives. While the purpose implies it is a readiness check before other operations, there is no guidance on prerequisites, when-not to use, or comparison with zyta_login or zyta_whoami. The agent must 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?
With no annotations, the description carries the full burden but only states the basic function: fetching connection status. It does not disclose potential side effects, error conditions, or performance characteristics. The description is adequate for a simple query but lacks depth.
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 two sentences, front-loading the key information (status of portals) and including the HTTP endpoint. No extraneous text.
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 simplicity (no parameters, no output schema), the description provides the essential purpose. However, it omits details about the response format or possible status values, which would be helpful for an agent to handle the output correctly.
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 input schema has no parameters, so schema coverage is 100%. The description does not need to add parameter details. A baseline of 4 is appropriate since no additional information is required.
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 checks the connection status of specific judicial portals (PJN and SCBA) and that it uses the same user as the JWT token. It also includes the HTTP method and path, making the purpose unambiguous and distinct from sibling tools like zyta_auth_status.
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 is given on when to use this tool versus alternatives. It does not mention prerequisites, context, or when not to use it. The user must infer from the name and description.
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 detail behavioral traits. It discloses the HTTP method but omits common list behaviors like pagination, ordering, or data limits. It does not explicitly state read-only nature.
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: two sentences that front-load the main action, mention optional filtering, and include the API path. 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?
For a simple list tool with one optional parameter, the description covers the core functionality. However, it does not specify return fields, pagination, or any default behavior. With no output schema, a bit more detail would improve completeness.
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 a well-described optional parameter. The description redundantly mentions the portal filter but adds no new meaning 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 it lists the user's judicial cases, optionally filtered by portal. It includes the HTTP method and path, distinguishing it from sibling tools like zyta_judicial_expediente_get (which retrieves a single case).
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 listing the user's own cases with optional filtering, but does not explicitly state when to use it versus alternatives or provide exclusions. It lacks guidance on prerequisites or complementary 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?
No annotations provided, so description carries full burden. It mentions the endpoint GET and implies authentication ('del usuario autenticado'), but does not disclose side effects, rate limits, or explicit read-only nature. Adequate but could be more explicit.
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, front-loaded with the main action, and includes the endpoint. No unnecessary words; every sentence 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?
Although no output schema exists, the description specifies the returned fields and pagination. For a history retrieval tool, this covers expected output. Could mention error conditions but current content is 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% with descriptions for page and limit. The description does not add meaning beyond what the schema already provides, so baseline score of 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 it returns paginated history of Minerva queries for the authenticated user, sorted newest-first, and lists included fields (query, answer, sources, tokens). It distinguishes from sibling tools like zyta_minerva_consultar which are for active queries.
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 retrieving history but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is 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 are provided, so the description must disclose behavioral traits. It indicates a GET request (read-only) and user-specific data ('del usuario'), but omits authentication requirements, rate limits, or any side effects. This leaves gaps for an AI agent.
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 function and includes the endpoint. No wasted words; front-loaded with the core purpose.
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 covers key return values (cost, limit, balance). However, it lacks specifics on time frame (current month?), data types, or format. Slightly incomplete for full agent understanding.
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?
With 0 parameters and 100% schema coverage (empty object), the description adds value by explaining the tool returns cost, plan limit, and remaining balance. Baseline for 0-parameter tools is 4, and the description meets this criteria.
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 displays monthly Minerva usage including accumulated cost, plan limit, and remaining balance. It uses specific verb 'muestra' and resource 'uso mensual', distinguishing it from sibling tools like zyta_minerva_buscar_fallos (search) and zyta_minerva_consultar (consult).
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 checking usage and balance but provides no explicit guidance on when to use this tool versus alternatives (e.g., other Minerva tools). No exclusions or conditions are mentioned.
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 that the tool uses RAG, adds curated regulatory framework, generates AI response, and logs to user history. However, it does not mention side effects (e.g., non-idempotent POST), authentication requirements, or rate limits. The behavioral traits are partially covered but not exhaustively.
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: two sentences. The first sentence delivers the core purpose with action verbs, and the second adds critical context about history logging and the HTTP method. No redundant or irrelevant information.
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, the description lacks details on the response format or error handling. It explains the general process (RAG, regulatory framework, AI generation) but does not specify what the user receives. The logging behavior is good, but for a tool that returns content, the output structure is undefined. This leaves an information gap for the agent.
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 clear descriptions for each parameter. The tool description adds no additional meaning beyond the schema; it only mentions the query implicitly. Baseline of 3 is appropriate as the schema already documents parameters well, and the description does not enhance understanding of parameter usage.
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: a complete legal consultation that searches rulings (RAG), adds curated regulatory framework, and generates an AI response. It explicitly mentions the POST endpoint and logging to user history. This differentiates it from sibling tools like zyta_minerva_buscar_fallos, which likely only searches rulings without the full consultative response.
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 indicates this tool is for a comprehensive legal query that produces an AI-generated response and logs history. It implicitly distinguishes from zyta_minerva_buscar_fallos but does not explicitly state when to use each. The context of 'completa' and the mention of generating a response provide clear usage cues, though explicit exclusions are missing.
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 that the tool performs a write operation ('registra actuaciones') and that the backend uses AI. It does not mention permissions, reversibility, or side effects. For a mutation tool, more transparency on behavior would be beneficial.
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 the core purpose. Includes the API endpoint as added detail. Every sentence serves a purpose with no fluff.
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 is a write operation with 3 parameters, no output schema. The description explains input and resolution logic, but lacks information about the return value or confirmation feedback. While the context is reasonable, completeness would improve with output details.
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%, and the description adds context beyond the schema: message is free text task, link is optional, expedienteId is UUID for specific case. It explains the AI resolution logic when expedienteId is omitted, adding value.
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 'Registra' and resource 'actuaciones en una causa sin portal'. It specifies that it works from a free text message and uses AI to resolve the case if no expedienteId is provided. This distinguishes it from sibling tools that handle other judicial functions.
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 explains when to use the tool: for cases without portal, and gives two methods—either let AI resolve or provide expedienteId. It also mentions optional link. However, it doesn't explicitly state when not to use it or compare to alternatives (e.g., tools for cases with portal).
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 compensate. It mentions the GET method implying idempotence but does not elaborate on side effects, rate limits, or response details. Adequate but minimal.
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 succinct clauses, front-loaded with the core action. Every word adds value; no fluff.
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 zero-param tool with no output schema, the description covers the purpose and prerequisite. It could mention return format but is sufficient for basic usage.
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 (0 params, 100% schema coverage), so the description adds no parameter info. Per guidelines, baseline 4 applies when no parameters are present.
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 returns the user associated with the MCP agent token, specifying the HTTP method and endpoint. It distinguishes from siblings like 'zyta_login' or 'zyta_auth_status'.
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 'Requiere sesión activa' (requires active session), indicating the tool should only be used after authentication. It does not provide alternative tools or when-not-to-use, but 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description effectively discloses the tool's actions (deleting token in memory and file) and its boundaries (no browser session closure). This is transparent for a simple 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?
The description is exceptionally concise (two sentences), front-loaded with the main action, 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.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description fully covers the tool's behavior and limitations. It is complete for a simple disconnect operation.
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?
There are no parameters, so the description cannot add meaning beyond the schema. Baseline score of 4 is appropriate as the tool's behavior is fully described without needing parameter details.
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 (closing the MCP agent session) with specific verbs and resources, and distinguishes itself from siblings by explaining what it does not do (close browser session).
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?
While the description does not explicitly state when to use or not use this tool, the context is clear and the caveat about browser session provides helpful guidance. It could be improved by mentioning alternatives like zyta_login.
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 discloses behavior: access_token can be passed as parameter or via env variable; email+password performs POST /auth/login; device flow opens browser and requires dashboard. It is transparent about dependencies and alternatives, though it does not mention session handling post-login.
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?
Three sentences, front-loaded with the most critical information (mandatory usage). Each sentence serves a purpose: prerequisite, ordered options, fallback advice. 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 the absence of an output schema and the presence of sibling tools (zyta_auth_status), the description covers prerequisites, methods, and fallbacks comprehensively. It does not detail post-login behavior, but that is likely handled by zyta_auth_status.
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 context beyond the schema: it explains the priority and rationale for each parameter (e.g., 'access_token manual (alternativa al device flow)', 'Con password hace POST /auth/login (sin depender del dashboard)'). This helps an agent choose the right input for the situation.
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 is required before any other if no session exists, and lists three authentication methods (access_token, email+password, device flow). It distinguishes itself from sibling tools by being the prerequisite for all others.
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 states when to use ('obligatorio antes de cualquier otra herramienta si no hay sesión') and provides alternatives and fallbacks (if device flow pending, use email+password or npx zyta-mcp-login).
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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