Cisco MCP Pods Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting pods (create, delete, get_all, get_by_number, update) and pod keywords (get_keyword, update_keyword), with clear separation between pod management and keyword operations. However, 'get_pod_by_number' and 'update_pod' could potentially overlap in retrieval/update scenarios, but their descriptions clarify distinct primary functions.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case (e.g., create_pod, delete_pod, get_all_pods). The naming is predictable and uniform across the set, making it easy for agents to understand and navigate the tool surface without confusion.
Tool Count5/5
With 7 tools, the server is well-scoped for managing pods and keywords in a collection. Each tool serves a clear purpose (CRUD operations for pods, plus keyword handling), and the count is appropriate for the domain without being overwhelming or insufficient.
Completeness5/5
The tool set provides complete CRUD coverage for pods (create, get_all, get_by_number, update, delete) and dedicated tools for keyword management (get and update). There are no obvious gaps for the stated purpose of pod and keyword management in collections, ensuring agents can handle full lifecycles without dead ends.
Average 3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states 'Create a new pod' implying a write/mutation operation, but doesn't disclose permissions needed, side effects (e.g., if it affects existing pods), rate limits, or what happens on failure. The requirement for all fields is noted, but overall transparency is lacking for a creation 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 extremely concise with two sentences that are front-loaded and waste-free. The first sentence states the core purpose, and the second adds a critical constraint. Every word earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (14 parameters, 12 required) and lack of annotations or output schema, the description is incomplete. It doesn't explain what a 'pod' is, the creation process, expected outcomes, error handling, or how it interacts with the collection. For a tool with many parameters and no structured safety hints, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 14 parameters. The description adds no additional parameter semantics beyond stating 'All required fields must be provided,' which is implied by the required array. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate with extra context like field relationships or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new pod') and resource ('in a collection'), making the purpose evident. It distinguishes from siblings like delete_pod or update_pod by focusing on creation, but doesn't explicitly differentiate from tools like get_all_pods beyond the verb. The mention of 'All required fields must be provided' adds specificity about prerequisites.
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 like update_pod or delete_pod. It mentions that required fields must be provided, which is a prerequisite but not usage context. There's no indication of scenarios, dependencies, or comparisons 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?
With no annotations provided, the description carries full burden but only states the basic action without disclosing critical behavioral traits. It doesn't warn that deletion is irreversible, mention permission requirements, indicate if confirmation is needed, or describe what happens to associated data. For a destructive tool, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core action ('Delete') and efficiently specifies the target, making it easy to parse quickly. Every word earns its place without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on side effects, error conditions, return values, or safety considerations. For a tool that permanently removes resources, more context is needed to use it appropriately and safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional meaning beyond implying 'collection' and 'number' identify the pod to delete, which is already clear from the schema. This meets the baseline for high schema coverage without enhancing parameter understanding.
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 ('Delete') and target resource ('a pod from a collection'), making the purpose immediately understandable. However, it doesn't differentiate this destructive operation from sibling tools like 'update_pod' or 'get_pod_by_number' beyond the obvious verb difference, missing explicit contrast in scope or consequences.
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 doesn't mention prerequisites (e.g., pod must exist), exclusions (e.g., cannot delete if in use), or suggest alternatives like 'update_pod' for modifications instead of deletion. The agent must infer usage from context 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns pod details including login credentials, phone numbers, and status, which adds some context about sensitive data. However, it lacks critical behavioral traits such as whether this is a read-only operation, authentication requirements, error handling, or rate limits, leaving significant gaps for a mutation-free tool.
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 appropriately sized with two sentences that are front-loaded: the first states the purpose, and the second specifies return details. There is minimal waste, though it could be slightly more structured by explicitly separating purpose from output.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and return details but lacks information on usage guidelines, behavioral traits, and error handling. With no output schema, it should ideally explain return values more thoroughly, but it provides a basic overview.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already fully documents both parameters (collection and number) with descriptions and types. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, resulting in the baseline score of 3.
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 a specific pod by its number') and resource ('from a collection'), with specific return details mentioned. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_pod_keyword' or 'get_all_pods', which would require sibling differentiation for 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 Guidelines2/5
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 like 'get_pod_keyword' (which might fetch by keyword instead of number) or 'get_all_pods' (which retrieves all pods). The description implies usage for retrieving a specific pod by number but offers no explicit context or 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Update' implies a mutation operation, the description lacks details on permissions required, whether updates are reversible, rate limits, error handling, or what happens to unspecified fields. It mentions updating 'credentials' which could imply security implications, but doesn't elaborate on authentication needs or data sensitivity.
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, efficient sentence that front-loads the core action ('Update an existing pod in a collection') and adds brief examples of updatable fields. There's no unnecessary verbiage, and it effectively communicates the tool's scope without redundancy. However, it could be slightly more structured by explicitly separating purpose from usage examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation operation with 3 parameters including a nested object), lack of annotations, and no output schema, the description is insufficient. It doesn't address behavioral aspects like side effects, error conditions, or return values, leaving significant gaps for an AI agent to understand how to invoke it correctly and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters ('collection', 'number', 'updates') and nested properties. The description adds minimal value beyond the schema by listing example fields ('status, credentials, test information') that map to the 'updates' object, but doesn't provide additional syntax, format, or constraint details. This meets the baseline for high schema coverage.
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 verb ('Update') and resource ('an existing pod in a collection'), making the purpose evident. It distinguishes from 'create_pod' by specifying 'existing' and from 'delete_pod' by focusing on updates rather than removal. However, it doesn't explicitly differentiate from 'update_pod_keyword', which might handle different aspects of pod updates.
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 like 'update_pod_keyword' or other sibling tools. It mentions updating 'status, credentials, test information, etc.', but doesn't specify prerequisites, exclusions, or contextual triggers for choosing this tool over others in the server.
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 an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether the change is reversible, potential side effects, or error conditions. For a mutation tool with zero 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.
Conciseness5/5
Is 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. Every part of the sentence contributes to understanding, achieving optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation operation, lack of annotations, and absence of an output schema, the description is incomplete. It doesn't explain what the tool returns, error handling, or behavioral nuances. For a tool that modifies data, this level of detail is inadequate, leaving the agent with insufficient context for reliable use.
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 description mentions updating 'with a new value', which aligns with the single parameter 'keyword' in the schema. Since schema description coverage is 100% (the parameter is well-documented with an example), the description adds minimal value beyond what the schema provides. The baseline score of 3 is appropriate as the schema does the heavy lifting for parameter semantics.
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 ('update') and the target resource ('pod keyword/password record'), making the purpose understandable. It specifies what gets updated ('with a new value'), which is specific. However, it doesn't explicitly differentiate from sibling tools like 'update_pod' or 'get_pod_keyword', leaving some ambiguity about when to choose this tool over others.
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 doesn't mention prerequisites (e.g., needing an existing pod), exclusions, or comparisons to siblings like 'update_pod' or 'get_pod_keyword'. Without such context, an agent must infer usage from the tool name 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 tool 'Get all pods' and works with collections, but doesn't disclose whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior, or what the return format looks like (e.g., list of pod objects). For a tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose in the first sentence. The second sentence adds useful context about collection examples without redundancy. It avoids unnecessary details, making it efficient, though it could be slightly more structured by explicitly stating the tool's scope or limitations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'pods' are, the format of the returned data, potential errors, or behavioral aspects like safety or performance. For a tool interacting with collections and pods, more context is needed to ensure proper agent usage.
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 description adds minimal value beyond the input schema, which has 100% coverage for the single parameter 'collection'. It provides examples of collection names ('ciscolivepods, coelabpods, testpods, etc.') that mirror the schema's description, but doesn't explain semantics like what a 'collection' represents, if there are constraints beyond being a string, or how it relates to pods. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get all pods from a specific collection.' It specifies the verb ('Get') and resource ('pods'), and distinguishes it from siblings like get_pod_by_number (which retrieves a single pod by number) and get_pod_keyword (which likely filters by keyword). However, it doesn't explicitly differentiate from other list-like operations if any exist beyond the named siblings.
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 by stating it works with 'any collection name like ciscolivepods, coelabpods, testpods, etc.,' which suggests it's for retrieving all pods from a known collection. It doesn't provide explicit guidance on when to use this tool versus alternatives like get_pod_by_number or get_pod_keyword, nor does it mention prerequisites or exclusions, leaving usage context somewhat inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns configuration data, which hints at read-only behavior, but doesn't clarify permissions, rate limits, error conditions, or what 'current' means in terms of freshness or caching. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and outcome. It avoids redundancy and wastes no words, though it could be slightly more structured by separating intent from result for clarity.
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 (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, and output specifics, leaving gaps that could hinder effective agent invocation without additional context.
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 0 parameters with 100% schema description coverage, so the schema fully documents the input structure. The description adds no parameter-specific information, which is acceptable given no parameters exist, aligning with the baseline expectation for such cases.
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 resource ('pod keyword/password record'), specifying it returns configuration data. It distinguishes from siblings like create_pod or delete_pod by focusing on retrieval, though it doesn't explicitly differentiate from get_all_pods or get_pod_by_number.
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 like get_pod_by_number or update_pod_keyword. It implies usage for retrieving keyword configuration but offers no context on prerequisites, exclusions, or comparative scenarios with sibling tools.
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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