factory-supervisor-mcp

by Heytish-V

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have clearly distinct purposes: inventory, machines, orders, maintenance, schedule, KPIs. However, the five high-level analytics/summary tools (analyzeFactory, predictFactoryHealth, factoryCopilot, dailySupervisorBrief, executiveSummary) could be confused due to overlapping outputs like health scores and recommendations, though their descriptions partially clarify target audiences.
Naming Consistency4/5
The naming pattern is largely consistent with verb-first camelCase (getInventory, listMachines, predictMachineFailure, etc.). Exceptions like factoryCopilot, dailySupervisorBrief, executiveSummary, and ping deviate from this pattern, but they remain readable and semantically descriptive.
Tool Count4/5
Eighteen tools is slightly above the typical 3-15 well-scoped range, but each tool maps to a distinct aspect of factory supervision (status reads, predictions, forecasts, summaries). The count feels justified for the broad domain, though it is on the heavier side.
Completeness4/5
The tool set covers all major factory modules (machines, inventory, orders, maintenance, schedule, KPIs) with both operational reads and predictive analytics. Minor gaps include per-order detail retrieval or explicit shift/employee data, but these are not critical for the supervisor role.
Average 3.6/5 across 18 of 18 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 19 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 provided, the description must carry the full burden of behavioral disclosure. It only states 'Get factory production orders' and does not mention return format, scope (e.g., all orders, current orders), pagination, or any side effects. The 'Get' verb implies read-only, but no explicit transparency is offered.
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 concise sentence with no filler words. It is appropriately sized for a tool with no parameters and a straightforward 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?
For a simple tool with no parameters, the description is minimally adequate but leaves room for improvement. It does not clarify the exact set of orders returned (e.g., all, by status, by date range) or the output structure, which would be helpful since no output schema is provided.
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 zero parameters, so the baseline is 4. The description does not need to explain parameter semantics because there are none; the schema confirms an empty parameter object.
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 action ('Get') and the resource ('factory production orders'), making the tool's purpose understandable. However, it does not differentiate from sibling tools like getProductionSchedule or getFactoryKPIs, which also deal with production-related data.
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?
There is no guidance on when to use this tool versus alternatives. The description does not mention any specific use case, prerequisites, or exclude scenarios where another tool would be more appropriate.
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 must carry the full burden of behavioral disclosure. The word 'get' implies a read operation, but the description does not specify return format, whether it includes current/future schedules, or any access requirements. This is a minimal safety disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no redundant words. It is appropriately front-loaded and efficient for a zero-parameter getter.
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, the description is minimally viable, but it lacks detail about the response contents (e.g., is it a list of scheduled items? a time range? current or upcoming?). No output schema exists, so the description should clarify what 'production schedule' entails, yet it does not.
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 accepts zero parameters, so the input schema fully covers parameter semantics. The description adds no parameter details, but none are needed. The baseline of 4 is appropriate for a parameterless tool.
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 'Get factory production schedule' clearly identifies the verb (get) and resource (production schedule), which is distinct from sibling tools like getInventory or getOrders. It lacks scope details (e.g., date range) but is specific enough to convey intent.
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 provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or alternative tools. Usage must be inferred solely from the tool name and resource, which is insufficient for clear 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?
With no annotations, the description carries the full burden. It only says 'diagnostic health check ping' without explaining what the response looks like, whether it's read-only, or any other behavioral traits. This is a significant gap for a health check 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 a single concise sentence that conveys the essential purpose. It is appropriately minimal and front-loaded, 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 zero-parameter, no-output-schema tool, the description is adequate but not complete. It doesn't describe what the health check returns (e.g., status, latency, errors) or how to interpret the result. Simple tools can get away with minimal descriptions, but a bit more behavioral detail would make it fully complete.
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 zero parameters and the schema coverage is 100%, so there is no need for the description to explain parameter semantics. The baseline for 0 parameters is 4, and the description doesn't need to compensate here.
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 this is a diagnostic health check ping tool for the server. It distinguishes from sibling factory operations by indicating it's a health check rather than a domain-specific operation. However, the phrase 'ping tool' is somewhat redundant with the tool name 'ping'.
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?
There is no guidance on when to use this tool versus alternatives. It doesn't mention that it's for verifying server availability or suggest any specific scenario. No exclusions or alternatives are 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, and the description does not disclose behavioral traits such as read-only nature, performance implications, or any side effects. It only lists inputs and outputs, leaving the operational behavior unclear.
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 sentence that is information-dense but still readable. It front-loads the primary action (consolidates) and then lists outputs. It could be slightly more structured by separating the outputs, but it remains concise and purposeful.
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?
There is no output schema, so the description must explain return values and interpretation. It lists outputs but lacks details on how to interpret health score thresholds, severity levels, or recommendation usage. For a complex analysis tool, this is insufficient.
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 zero parameters, so the description does not need to explain parameter meaning. The baseline of 4 applies here, as there is nothing to add beyond the empty input 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 consolidates data across all factory modules and lists concrete outputs (severity levels, health score, summary, etc.). It distinguishes itself from sibling tools that target individual modules or predictions by emphasizing the all-in-one analysis nature.
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 explicit guidance on when to use this tool versus alternatives. While it implies use for comprehensive factory analysis, it does not mention alternative tools like predictFactoryHealth or dailySupervisorBrief, nor does it provide use-case exclusions.
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, the description must fully disclose behavioral traits. It lists the forecast outputs but does not mention whether the tool is read-only, requires specific inputs (like recent data), handles missing partId, or has any limitations. There is no statement about side effects or data prerequisites.
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, efficient sentence that immediately conveys the tool's purpose. No redundant or filler content is present.
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 only one optional parameter and no output schema, so the description must explain what the forecast returns. It lists the key outputs but omits context such as whether a single result or a list is returned, what happens with no partId, and how to interpret the risk level. It is adequate but not complete.
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 schema already provides 100% coverage for the single optional parameter, describing it as a filter with an example. The tool description adds no extra parameter detail, but the schema is sufficient. 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 a specific verb ('Forecasts') and the exact resources/outputs (stockout date, days remaining, inventory risk level, recommended reorder quantity). This distinguishes it from siblings like getInventory or getLowStockItems, which presumably return current state rather than predictions.
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 provided on when to use this tool versus alternatives (e.g., getInventory, getLowStockItems). The description does not mention scenarios where forecasting is appropriate or when other tools should be preferred, leaving the agent to infer usage.
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 available, the description carries full responsibility for disclosing behavioral traits. It does not mention whether the tool is read-only, how the estimate is computed, what data it relies on, or any potential side effects. The word 'estimate' hints at uncertainty, but this falls short of a clear behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately states the tool's purpose and key output components. It is concise and free of redundant 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?
The tool is simple (one parameter, no output schema), and the description covers the main return aspects: completion time, confidence score, and delay risk. It does not elaborate on their format or units, but for a simple estimation tool, the description is reasonably complete.
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 fully documents the single parameter orderId with an example format, so the baseline is 3. The description adds minimal semantic value by clarifying that the order is a production order, but it does not introduce new 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's function: estimating completion time, confidence score, and delay risk for a production order. The verb 'estimates' and specific resource 'production order' make its purpose distinct from sibling tools that focus on other predictions or data retrieval.
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 explicit guidance is provided on when to use this tool versus alternatives such as getProductionSchedule or predictMachineFailure. The phrase 'for a given production order' implies a use case, but it does not offer context or exclusions to help the agent choose this tool correctly.
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 behavioral disclosure. It only states that the tool 'detects active and impending' bottlenecks but does not clarify whether it performs a read-only analysis, what data sources are accessed, or how results are returned. This is insufficient for the agent to understand side effects or safety implications.
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, front-loaded sentence with no filler. Every word contributes to conveying the tool's purpose and scope, making it appropriately concise and structurally sound.
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 a simple input schema (no parameters), but lacks an output schema and annotations. The description covers the detection scope but does not mention what the tool returns (e.g., a list, a report, a severity score) or any caveats. For a low-complexity, parameterless tool, this is a moderate gap that could confuse agents expecting return format 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?
The tool has zero parameters, so the schema provides complete coverage. The description adds no parameter-specific meaning, but per the rubric, a 0-parameter tool receives a baseline of 4 because there is nothing to explain.
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 function using the specific verb 'detects' and defines the scope as 'active and impending production bottlenecks across machines, inventory, and shifts.' This distinguishes it from sibling tools like analyzeFactory or predictMachineFailure, which have broader or different analytical purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention any exclusions or preferred contexts, leaving the agent without direction for selecting this over siblings like getMachineStatus or analyzeFactory.
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 full behavioral burden. It accurately describes the output (summary with performance, risk, recommendations) and implies a read-only operation, but it doesn't formally declare side effects, permissions, or any limitations. No contradictions.
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?
One concise sentence efficiently communicates purpose and key output components. No filler or 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?
For a zero-parameter tool without an output schema, the description is fairly complete: it lists what the summary covers. It could add a note about whether it aggregates data from other tools, but it's sufficient for basic selection.
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 zero parameters, so schema coverage is 100% by default. The baseline for zero-param tools is high, and no additional parameter explanation is needed.
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 a specific verb+resource: it provides a high-level executive summary covering factory performance, revenue exposure risk, and strategic decisions. This distinguishes it from detailed reporting tools, though some overlap remains with analyzeFactory or dailySupervisorBrief.
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 explicit guidance on when to use this tool versus alternatives. The description implies it's for strategic decision-making, but it doesn't mention exclusions or how it differs from sibling tools like dailySupervisorBrief or analyzeFactory.
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 bears the full burden. It only states that it retrieves status details, offering no insight into side effects, read-only guarantees, response structure, or potential errors. The verb 'get' implies a read operation, but this is not explicitly disclosed.
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, front-loaded with the action, and contains no unnecessary words. It is efficiently structured and immediately clear.
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 simple (one parameter, no output schema), so the description is minimally viable. However, it lacks any mention of what the status details include or how they are returned, which could be valuable given the absence of an output schema. It is adequate but has clear gaps.
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 fully describes the machineId parameter with an example (CNC-01), and the schema coverage is 100%. The description only mentions 'by machineId' without adding any new semantic meaning beyond what the schema provides, so the baseline of 3 applies.
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 a specific verb ('Get') and resource ('status details for a specific machine'), and identifies the key parameter (machineId). This distinguishes it from sibling tools like listMachines, which presumably list all machines, by focusing on a single machine.
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?
Usage is implied: you would use this tool when you need status for a specific machine. However, there is no explicit guidance on when to use it versus alternatives, such as listMachines for an overview, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 disclosing behavior. However, it only states the purpose and gives no information about whether this is a read-only operation, what the return format looks like, or any side effects or permissions required. This is a significant gap for a tool with no structured 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 a single concise sentence with no fluff or redundant information. It is appropriately sized and front-loaded with the action and resource.
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 no-parameter tool, the description is minimally adequate, but it could provide more context such as what the maintenance logs contain, whether it returns a list or summary, or how it relates to other monitoring tools. Without an output schema, the description should at least hint at the return value, which it does not.
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 zero parameters, so there are no parameter semantics to explain. The schema coverage is 100% (empty schema), and per the baseline for 0-parameter tools, a score of 4 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 'Get factory maintenance logs and history', using a specific verb ('Get') and a distinct resource ('factory maintenance logs and history') that differentiates it from sibling tools like getMachineStatus or getInventory. It is unambiguous in what it does.
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 provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, so the agent has to infer usage from the name alone.
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 exist, so the description carries the full burden of disclosing behavior. It simply says 'Get', implying a read operation, but does not mention data source, time range, side effects, or any other behavioral details.
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, concise sentence that immediately states the tool's purpose. There is no redundant information or unnecessary detail.
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 tool with no parameters and no output schema, the description is minimally sufficient. It clearly identifies the tool's purpose, though it could be slightly more specific about which KPIs are included. Overall, it is complete enough for a simple getter.
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 zero parameters, so the baseline of 4 applies. There is no need for parameter guidance, and the description adds no ambiguity.
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 factory key performance indicators. The verb 'Get' and the resource 'factory KPIs' make it distinct from sibling tools like getInventory or getMachineStatus.
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 provided on when to use this tool versus alternatives. It does not mention situations where this should be preferred, nor does it exclude any 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 carries the full burden. It discloses that the tool routes questions and generates actionable answers, but it does not state whether it is read-only, what side effects it may have (e.g., invoking other tools), or how it handles ambiguous or unsupported questions. This lack of behavioral detail is a significant ambiguity for an orchestration 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 a single sentence, concise and front-loaded with the key action ('routes user questions'). Every word earns its place, with no redundancy or unnecessary detail.
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 complex orchestration tool with no output schema and no annotations, the description gives only a high-level role. It does not specify the response format, error handling, or how routing occurs, which leaves the agent uncertain about the tool's full behavior. While adequate for a starting point, it lacks depth for a tool that likely coordinates multiple MCP calls.
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 describes the single 'question' parameter with a natural language prompt, and the schema description covers 100% of parameters. The tool description adds some domain context (factory status, capacity, machines, inventory, orders) but this is largely mirrored in the schema description. Therefore, it provides minimal additional meaning, warranting the baseline 3.
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 uses a specific verb ('routes') and clearly identifies the tool as a natural language AI assistant that directs user questions to appropriate analytics and predictive tools. It effectively distinguishes itself from sibling tools (e.g., getInventory, predictMachineFailure) by positioning itself as the supervisor/orchestration layer.
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 implies when to use the tool: when a user has a natural language question about factory operations that needs to be routed to the right analytics or predictive tool. It provides clear context but does not explicitly state when not to use it (e.g., for direct data retrieval, use specific sibling tools). This is a minor gap.
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. It specifies the operation (get total stock levels) and scope (all parts) but does not disclose whether the operation is read-only, whether it returns an aggregate count or detailed per-part data, or any other behavioral traits like permissions or response format.
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, concise sentence that immediately conveys the tool's purpose. It contains no filler, and every word contributes to the meaning. The structure is optimal for a tool with no parameters.
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 tool's simplicity (no parameters, no output schema, no annotations), the description is largely complete. It clearly states the action and scope. However, it could briefly mention that the result is an aggregate stock-level view to avoid ambiguity, since sibling tools like getLowStockItems exist.
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 zero parameters, so the baseline is 4. The description adds contextual meaning by specifying 'all parts,' which reinforces that no filters are needed. No additional parameter semantics are 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 uses a specific verb and resource: 'Get total inventory stock levels for all parts.' It clearly distinguishes from sibling tools like getLowStockItems, which focuses on filtered low-stock items, and forecastInventory, which predicts future stock. The scope ('all parts') adds clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when an agent needs a broad inventory overview, but it does not explicitly state when not to use it or mention alternatives like getLowStockItems for low-stock queries. The context is clear but lacks explicit exclusions or alternative guidance.
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 of behavioral disclosure. It lists specific outputs (failure probability, health score, time window, actions) which is helpful, but it does not explicitly state whether the operation is read-only, what data is required beyond machineId, or any limitations. Since 'predicts' implies non-mutating analysis, it is reasonably transparent but incomplete.
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 concise sentence, front-loaded with the main verb 'predicts' and listing all key outputs without any filler. Every word earns its place.
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 low-complexity tool with one well-described parameter and no output schema, the description adequately covers the return values (probability, health score, time window, actions). The 'estimated failure time window' is slightly vague but acceptable. Overall, the description is complete enough for an agent to understand tool 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?
The schema fully describes the only parameter (machineId) with an example (CNC-01), so the baseline is 3. The description adds sensor telemetry context but does not further explain how machineId maps to telemetry data or any format expectations 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 a specific verb ('predicts') and resource (machine failure probability, health score, failure time window, recommended actions). It distinguishes from sibling tools like getMachineStatus (current state) and predictFactoryHealth (factory-level) by targeting machine-level predictive analysis.
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?
Usage context is implied via 'based on sensor telemetry' and the machine-specific scope, but there is no explicit guidance on when to use this tool versus alternatives like getMachineStatus or getMaintenanceLogs. No exclusions or alternative tool names 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 uses the verb 'Generates', implying a non-destructive, output-producing behavior, and specifies the content of the briefing. However, it does not disclose any side effects, data sources, or performance characteristics, leaving some ambiguity for an 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, well-structured sentence that front-loads the core action ('Generates') and then elaborates on the specific content. Every word contributes value with no repetition or filler.
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 zero-parameter tool with no output schema, the description provides a solid overview of what the briefing includes (health, risks, actions). It could add more detail about the output format or how the briefing is delivered, but the given content is sufficient for a basic 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?
The tool has zero parameters, so the baseline is 4. The description adds no parameter details, but none are needed. The schema already covers everything via an empty object, and the description is not required to compensate.
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 generates a 'concise daily supervisor briefing' with specific content: 'overall factory health, top operational risks, and priority actions.' This distinguishes it from siblings like executiveSummary by focusing on the supervisor audience and daily cadence.
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 phrase 'daily supervisor briefing' implies when and for whom to use the tool, but no explicit guidance is given about when not to use it or which alternative tools to consider. It lacks the explicit when/when-not/alternatives of a 4 or 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions returning 'current state' but does not explicitly confirm read-only behavior, response format, or pagination. The term 'list' implies a non-mutating operation, but more detail could be added.
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, concise sentence with no unnecessary words. It is front-loaded with the action and resource.
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-parameter list tool with no output schema, the description is reasonably complete. 'Current state' is slightly vague but conveys the core purpose. Additional details like fields returned would improve completeness, but the simplicity of the tool makes this adequate.
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 zero parameters, and the schema is vacuously covered. Baseline for 0 params is 4; the description does not need to elaborate on parameter meaning.
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 'list', the resource 'factory machines', and the scope 'current state'. This distinguishes it from sibling tools like getMachineStatus, which likely targets an individual machine.
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 getting an overview of all machines and their states, but it does not explicitly state when to use this tool over alternatives like getMachineStatus. No exclusions or alternative recommendations 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?
With no annotations, the description carries full burden. It states the predictive nature and time range, which implies a safe read-only operation, but it does not explicitly disclose that no data is modified, nor does it describe the return format or underlying data requirements. Some behavioral context is present but not comprehensive.
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, front-loaded sentence with no redundant words. Every word contributes to the core purpose, making it highly concise and well-structured.
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, annotations, and parameters, the description must carry all context. It clearly conveys the tool's function and temporal scope but leaves some ambiguity about the exact output structure and what 'operational indicators' encompass. Still, it is sufficiently complete for a simple prediction tool with no invocation parameters.
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 is empty with zero parameters, so the schema trivially covers all properties. The description adds no parameter information, but none is needed for a parameterless tool, aligning with the baseline of 4 for zero-parameter tools.
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 uses a specific verb ('predicts') and a clear resource ('overall factory health score trends'), distinguishing it from sibling tools like predictMachineFailure and getFactoryKPIs. It clearly states the expected output domain and time horizon.
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 purpose implicitly suggests use when future factory health trends are needed, but it does not provide explicit guidance on when to prefer this tool over alternatives like analyzeFactory or getFactoryKPIs. No exclusions or alternative comparisons are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It accurately conveys this is a read-only query for low-stock items, but it does not disclose output format, sorting, or edge cases (e.g., zero-stock items). Basic transparency is present, but richer behavioral context is missing.
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, front-loaded sentence with no wasted words. It states exactly what the tool does without any redundant 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?
Given the tool's simplicity (zero parameters, no output schema), the description adequately covers its purpose and return subject. However, the lack of explicit output field details prevents a perfect score, though this is a minor gap for a straightforward query.
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 zero parameters, so the schema is empty. The baseline for no parameters is 4, and the description adds meaning by explaining the stock-level filter, which is the core semantic logic of the tool.
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 specifies a distinct verb ('Get') and resource ('inventory items') with a precise filter condition ('available stock is at or below reorder level'), distinguishing it from siblings like getInventory or forecastInventory.
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 implies a clear use case for retrieving reorder alerts, but it does not explicitly mention alternatives or state when not to use it. This is clear context without exclusions, so a 4 is appropriate.
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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