Entyrax
Server Details
PC hardware decision engine for Brazil (pt-BR): compatibility, GPU recommendations, build analysis.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.1/5 across 3 of 3 tools scored.
Each tool targets a distinct aspect: full build analysis, pairwise compatibility, and GPU recommendation. No overlap in purpose.
All tools follow a consistent verb_noun pattern in snake_case (analyze_build, check_compatibility, recommend_gpu_by_context), making the set predictable.
Three tools is a reasonable size for a focused PC building assistant, covering the core decision points without overcomplicating.
The set covers full build analysis and compatibility but lacks recommendations for other individual components (e.g., CPU, motherboard) and price tracking, leaving some gaps.
Available Tools
3 toolsanalyze_buildAnalisar build completoARead-onlyIdempotentInspect
Analisa um build CPU+Mobo+GPU. Retorna overall_quality, reasoning (why_this_mobo/why_this_gpu/budget_note), PSU recomendada e preços.
| Name | Required | Description | Default |
|---|---|---|---|
| cpu_slug | Yes | Slug da CPU (ex: ryzen-7-7800x3d) | |
| gpu_slug | Yes | Slug da GPU (ex: geforce-rtx-5070-ti) | |
| mobo_slug | Yes | Slug da placa-mãe (ex: gigabyte-b650-aorus-pro-ax) |
Output Schema
| Name | Required | Description |
|---|---|---|
| psu | No | PSU recomendada para o conjunto |
| reasoning | No | why_this_mobo, why_this_gpu, budget_note |
| overall_quality | No | Qualidade geral do build (ex: excellent, unbalanced) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive. The description adds value by listing return fields (overall_quality, reasoning, PSU, prices) and confirms the tool's scope, which is consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, front-loaded with the core purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of annotations and full output schema, the description sufficiently covers the tool's purpose and outputs. Missing error handling or prerequisites, but not critical for this straightforward tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description reinforces that these three slugs form a build and explains what the analysis returns, but does not add new details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes a full CPU+Mobo+GPU build and returns specific outputs (overall quality, reasoning, PSU, prices). It distinguishes well from siblings like check_compatibility and recommend_gpu_by_context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for analyzing a complete build but does not explicitly state when to use it vs. siblings or provide when-not scenarios. Sibling tools are listed but no comparison is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_compatibilityVerificar compatibilidadeARead-onlyIdempotentInspect
Verifica compatibilidade e qualidade de pairing entre dois componentes (CPU+Mobo, CPU+GPU, GPU+Monitor). Retorna compatibility_status, pairing_quality, confidence e reasoning.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_a | Yes | Slug do primeiro componente (ex: ryzen-7-7800x3d) | |
| entity_b | Yes | Slug do segundo componente (ex: gigabyte-b650-aorus-pro-ax) | |
| pair_type | No | Tipo do par. Opcional; se omitido, tenta os três. |
Output Schema
| Name | Required | Description |
|---|---|---|
| reason | No | Justificativa em pt-BR |
| pair_type | No | cpu_mobo | cpu_gpu | gpu_monitor |
| compatible | No | Se o par funciona junto |
| confidence | No | 0.0–1.0 |
| pairing_quality | No | Ex: excellent, balanced, bottleneck_risk |
| compatibility_status | No | Ex: native_supported, needs_bios_update |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds that when pair_type is omitted, the tool tries all three pair types, and explicitly lists return fields. This provides useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: first covers purpose and components, second lists return fields. Every word earns its place; no fluff. Front-loaded with the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 params, output schema, annotations covering safety), the description is complete enough: it explains what pairs are checked, return fields, and behavior when pair_type is omitted. Missing details on error handling or quality metrics are acceptable given output schema presence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description repeats that entity_a and entity_b are slugs and mentions pair types, but does not add significant new meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks compatibility and pairing quality between two components, listing specific pair types (CPU+Mobo, CPU+GPU, GPU+Monitor) and return fields. This distinguishes it from siblings (analyze_build, recommend_gpu_by_context) which focus on full builds or recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking specific component pairs, but does not explicitly contrast with sibling tools or mention when not to use it. The context is clear, but no exclusions or alternatives are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recommend_gpu_by_contextRecomendar GPU por contextoARead-onlyIdempotentInspect
Recomenda top GPUs dado contexto: resolução (1080p/1440p/4k), uso (gaming-aaa/gaming-competitive/produtividade) e orçamento em BRL.
| Name | Required | Description | Default |
|---|---|---|---|
| use_case | Yes | Uso principal da máquina | |
| budget_brl | Yes | Orçamento máximo em BRL (ex: 3500) | |
| resolution | Yes | Resolução alvo do monitor |
Output Schema
| Name | Required | Description |
|---|---|---|
| picks | No | GPUs recomendadas em ordem de adequação |
| reasoning | No | Resumo do porquê do ranking |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety and idempotency. Description adds no additional behavioral traits beyond stating it recommends GPUs. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant information, front-loaded with key action and context. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists (not shown but signaled), description adequately covers the tool's purpose with three parameters. No missing context for a recommendation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by providing examples (e.g., '1080p/1440p/4k', 'gaming-aaa/gaming-competitive/produtividade') and clarifying budget format ('em BRL'), which aids the agent in parameter selection.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb ('Recomenda'), resource ('top GPUs'), and context parameters (resolution, use case, budget). Distinguishes from sibling tools (analyze_build, check_compatibility) by focusing on GPU recommendation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage when needing GPU recommendations given context, but provides no explicit guidance on when to use versus alternatives or exclusions. Siblings exist but no differentiation stated.
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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