Cisco CX Cloud MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific data types like contracts, assets, accounts, field notices, hardware/software EOL, inventory, network elements, security advisories, and uncovered assets. The descriptions explicitly differentiate each tool's function, eliminating any ambiguity or overlap.
Naming Consistency5/5All tool names follow a consistent 'get_' prefix with descriptive nouns (e.g., get_contracts, get_covered_assets), using snake_case uniformly throughout. This predictable pattern makes the tool set easy to navigate and understand.
Tool Count5/5With 10 tools, the server is well-scoped for its purpose of retrieving various customer-specific data from Cisco CX Cloud. Each tool serves a distinct and necessary function, covering key areas like contracts, assets, inventory, and advisories without being overly sparse or bloated.
Completeness4/5The tool set provides comprehensive read-only coverage for retrieving customer data, including contracts, assets, inventory, and advisories, with no obvious gaps for its apparent domain. However, it lacks write or update operations (e.g., create or modify contracts), which might limit full lifecycle management but is typical for a data retrieval-focused server.
Average 3.2/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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 carries the full burden of behavioral disclosure. It states the tool returns contract details including coverage periods, which is useful, but lacks critical information such as whether this is a read-only operation, potential rate limits, authentication requirements, or error handling. This leaves significant gaps for a tool that likely accesses sensitive data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of just two sentences that directly state the tool's purpose and return value. Every word earns its place with zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It covers the basic purpose and return scope but misses behavioral details like safety, permissions, or response format. For a tool that likely handles sensitive contract data, this leaves the agent under-informed about critical operational aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'customerId' fully documented in the schema. The description adds no additional parameter semantics beyond implying the customer context, so it meets the baseline for adequate but not exceptional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('contracts'), and specifies the scope ('for a specific customer'). It doesn't explicitly differentiate from sibling tools like 'get_customer_accounts' or 'get_covered_assets', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_customer_accounts' or 'get_covered_assets'. It mentions the customer context but offers no explicit when/when-not instructions or prerequisites, leaving usage decisions ambiguous.
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 implies a read-only operation ('Get', 'Shows') but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what 'end-of-life information' entails (e.g., dates, statuses). The description is too vague to fully inform 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that are front-loaded and to the point. However, the second sentence ('Shows which hardware is reaching end-of-life') is somewhat redundant with the first, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values include (e.g., hardware items, EOL dates, statuses) or provide enough context for a tool that likely involves complex data retrieval. More detail is needed to compensate for missing structured information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single parameter 'customerId'. The description adds no additional meaning beyond implying it's used to fetch data for that customer, which is redundant with the schema. Baseline 3 is appropriate as the schema handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('hardware end-of-life information'), and it specifies the scope ('for a specific customer'). However, it doesn't explicitly distinguish this tool from its sibling 'get_software_eol', which is similar but for software instead of hardware.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_hardware_inventory' or 'get_software_eol'. It mentions the target ('customer') but lacks context on prerequisites, exclusions, or comparison with 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 of behavioral disclosure. It states the tool returns 'network devices and their details,' which implies a read-only operation, but does not cover aspects like authentication requirements, rate limits, error handling, or pagination. For a tool with no annotations, this leaves significant gaps in behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of two sentences that directly state the tool's purpose and return value. There is no wasted language, and it efficiently communicates the core functionality. However, it could be slightly improved with more structured guidance, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return value but lacks details on behavioral traits, usage context, and output structure. This makes it complete enough for a basic read operation but with clear gaps that hinder full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'customerId' documented as 'The customer ID.' The description adds no additional semantic information beyond what the schema provides, such as format examples or constraints. According to the rules, when schema coverage is high (>80%), the baseline score is 3, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get network elements inventory for a specific customer.' It specifies the verb ('Get'), resource ('network elements inventory'), and scope ('for a specific customer'), which is clear and specific. However, it does not explicitly distinguish this tool from its siblings (e.g., get_hardware_inventory), which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'for a specific customer,' but does not clarify prerequisites, exclusions, or when to choose this over sibling tools like get_hardware_inventory or get_covered_assets. This lack of explicit usage context results in a minimal score.
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 mentions the return content ('security alerts and recommendations') but doesn't describe format, pagination, rate limits, authentication requirements, or error conditions. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences that directly state the tool's function and return value. There's no unnecessary information or repetition. However, it could be slightly more front-loaded by combining the two ideas more tightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a simple single-parameter input schema, the description provides basic completeness by stating what data is returned. However, it lacks details about response format, error handling, or behavioral constraints that would be helpful for an agent to use this tool effectively in context with its siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'customerId' documented as 'The customer ID'. The description adds no additional parameter information beyond what the schema provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('security advisories'), and specifies the scope ('for a specific customer'). It distinguishes from siblings by focusing on security advisories rather than contracts, assets, or other data types. However, it doesn't explicitly differentiate from hypothetical similar tools like 'get_all_security_advisories' or 'search_security_advisories'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for selecting this over other tools, or any exclusions. Given the sibling tools include various data retrieval functions, the agent must infer usage based on the resource name alone without explicit direction.
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 states this is a read operation ('Get'), but doesn't describe what the output looks like (e.g., list format, data fields), whether it requires authentication, any rate limits, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. Both sentences earn their place by clarifying the action and what information is shown. There's no wasted verbiage, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It adequately states the purpose but fails to provide necessary context such as output format, error handling, or usage guidelines relative to siblings. For a tool with no structured behavioral data, this leaves the agent under-informed about how to effectively use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add any meaning beyond what the input schema provides. The schema has 100% description coverage, with the single parameter 'customerId' documented as 'The customer ID'. The description implies the tool operates on a specific customer but doesn't elaborate on parameter usage, format, or constraints. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get software end-of-life information for a specific customer. Shows which software versions are reaching end-of-life.' This specifies the verb ('Get'), resource ('software end-of-life information'), and scope ('for a specific customer'). However, it doesn't explicitly distinguish this tool from its sibling 'get_hardware_eol' beyond the 'software' vs 'hardware' distinction in their names, which is why it doesn't reach a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when not to use it, or how it differs from sibling tools like 'get_hardware_eol' or 'get_security_advisories'. The agent must infer usage from the tool name and description alone, which is insufficient for optimal selection.
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 states the action 'Get all assets' but does not describe return format, pagination, error handling, or whether it's a read-only operation. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, or output, which are needed for full understanding. Without annotations or output schema, more descriptive context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with 'customerId' documented as 'The customer ID.' The description adds no additional meaning beyond this, such as format examples or validation rules. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'assets covered by contracts for a specific customer,' making the purpose understandable. It distinguishes from siblings like 'get_uncovered_assets' by specifying 'covered' assets, but does not explicitly differentiate from others like 'get_contracts' or 'get_hardware_inventory' in terms of scope or data type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing a valid customer ID, or specify use cases like contract management versus asset tracking. With siblings like 'get_uncovered_assets' and 'get_contracts,' explicit usage context is missing.
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 states the tool returns 'important product notifications and bulletins,' which implies a read-only operation, but does not specify permissions, rate limits, error handling, or response format. For a tool with zero annotation coverage, this is inadequate, scoring 2 for lacking essential 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: two concise sentences that directly state the tool's purpose and return value without waste. Every sentence earns its place by conveying essential information efficiently, warranting a score of 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, 100% schema coverage, no output schema), the description is minimally complete. It covers the basic purpose and return type but lacks behavioral details, usage guidelines, and output specifics. With no annotations and simple schema, it meets the bare minimum, scoring 3 as adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning beyond the input schema, which has 100% coverage for the single parameter 'customerId.' The schema already describes it as 'The customer ID,' so the baseline is 3. No additional parameter context is provided in the description, keeping it at the minimum viable score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get field notices for a specific customer' specifies the verb (get) and resource (field notices), with scope (for a specific customer). It distinguishes from siblings like get_security_advisories or get_hardware_eol by focusing on product notifications and bulletins, though not explicitly contrasting them. A 5 would require explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'for a specific customer' but does not clarify prerequisites, exclusions, or when to choose this over other tools like get_security_advisories. Without any usage context or alternatives named, it scores 2 for minimal guidance.
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 states the tool returns 'details about all hardware assets', which gives some behavioral insight, but lacks critical information such as whether this is a read-only operation, any rate limits, authentication needs, pagination, or error handling. The description is minimal and doesn't compensate for the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that directly state the tool's function and output. It is front-loaded with the core purpose and wastes no words, making it efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a simple input schema, the description is minimally adequate. It covers the basic purpose and output, but lacks details on behavior, error cases, or return format. For a tool with no structured metadata, it should provide more context to be fully helpful, but it meets the bare minimum for a simple read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'customerId' well-documented in the schema itself. The description doesn't add any additional meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('hardware inventory'), and specifies the scope ('for a specific customer'). It distinguishes from siblings like 'get_covered_assets' or 'get_uncovered_assets' by focusing on hardware assets. However, it doesn't explicitly differentiate from all siblings, such as 'get_network_elements' which might overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing hardware inventory for a customer, and the input schema hints at prerequisites by noting 'get from get_customer_accounts first'. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_covered_assets' or 'get_uncovered_assets', and doesn't specify exclusions or detailed context.
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 mentions the tool's utility ('identifying coverage gaps') but does not describe key behavioral traits such as whether it's a read-only operation, what the return format looks like, potential rate limits, or error handling. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and utility. It is front-loaded with the core functionality and avoids unnecessary details, making it easy to understand quickly without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity is low (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and usage hint but lacks details on behavioral aspects like return values or error conditions. For a tool with no annotations or output schema, more context would be beneficial to fully understand its operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'customerId' documented as 'The customer ID.' The description does not add any additional meaning or context beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get all assets NOT covered by contracts for a specific customer.' It specifies the verb ('Get'), resource ('assets'), and scope ('NOT covered by contracts'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'get_covered_assets' or 'get_contracts', though the distinction is implied by the 'NOT covered' phrasing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context with 'Useful for identifying coverage gaps,' suggesting when this tool might be applied. However, it does not offer explicit guidance on when to use this tool versus alternatives like 'get_covered_assets' or 'get_contracts', nor does it specify any exclusions or prerequisites. The guidance is present but lacks detail on sibling tool differentiation.
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 states the tool retrieves 'all accessible' accounts, which implies a read-only operation without destructive effects, but lacks details on permissions, rate limits, pagination, or response format. It adds some context about accessibility but misses key behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by usage guidance. Every word earns its place with no redundancy or fluff, making it highly efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that likely returns a list of accounts. It explains the purpose and usage but omits details on response format, error handling, or data scope (e.g., what 'accessible' means). For a read operation with zero structured metadata, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info beyond the schema, but with no params, a baseline of 4 is appropriate as there's nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('all accessible CX Cloud customer accounts and their IDs'), making the purpose specific and unambiguous. It distinguishes this tool from siblings by focusing on customer accounts rather than contracts, assets, or other entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides usage guidance: 'Use this first to get customer IDs for other operations.' This tells the agent when to use this tool (as an initial step) and implies its role in a workflow, though it doesn't name specific alternatives.
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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- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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