Content Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes: listing, searching, deleting, and two upload methods (file vs. URL). However, 'listContentNames' and 'searchOrganizationContents' could be confused as both retrieve content, though 'search' implies semantic filtering while 'list' is name-based. The two upload tools are clearly differentiated by input type.
Naming Consistency2/5
Naming is inconsistent with mixed conventions: 'deleteOrganizationContent' uses camelCase, while 'listContentNames', 'searchOrganizationContents', and the upload tools use a mix of camelCase and descriptive phrases. There's no uniform verb_noun pattern; for example, 'uploadContentFileAboutOrganization' is overly verbose and deviates from simpler naming like 'uploadContentFile'.
Tool Count5/5
With 5 tools, the count is well-scoped for a content management server. It covers core operations (list, search, delete, upload via file, upload via URL) without being overwhelming or too sparse, fitting typical server purposes efficiently.
Completeness3/5
The toolset covers basic CRUD operations: create (via upload tools), read (list and search), and delete, but lacks an update tool for modifying existing content. This gap could cause agent failures if content needs editing, though agents might work around it by deleting and re-uploading.
Average 2.7/5 across 5 of 5 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
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It does not disclose permissions needed, effects on the system (e.g., overwriting), rate limits, or response format. This is inadequate for a mutation 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 with no wasted words. However, it is under-specified rather than concise, as it lacks necessary context for a mutation tool.
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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It does not cover behavioral aspects, usage context, or differences from siblings, leaving significant gaps for an AI agent to understand proper invocation.
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 documented in the schema. The description adds no meaning beyond the schema, such as explaining 'role' usage or file format constraints. 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.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Upload content file about the organization' restates the tool name with minimal elaboration, making it tautological. It specifies the verb ('upload') and resource ('content file about the organization') but lacks detail on what this means operationally or how it differs from sibling tools like 'uploadContentUrlAboutOrganization'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 prerequisites, context for file uploads, or distinctions from sibling tools such as 'uploadContentUrlAboutOrganization' (for URLs) or 'listContentNames' (for listing).
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 deletes content, implying a destructive mutation, but doesn't disclose critical traits like whether deletion is permanent or reversible, required permissions, rate limits, or error handling. This is a significant gap for a destructive 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 directly states the tool's action. It's front-loaded with the key verb 'Delete' and avoids unnecessary words. However, it could be slightly more informative without losing conciseness, such as specifying content type.
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 destructive nature, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., permanence, auth needs), usage context, and return values. For a mutation tool with this complexity, the description should provide more guidance to compensate for missing structured data.
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 has 100% description coverage, with 'contentId' clearly documented as 'The ID of the content to delete'. The description adds no additional meaning beyond this, such as format examples or sourcing guidance. With high schema coverage, the baseline is 3, as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Delete') and target ('specific content from the organization's database'), which clarifies the basic purpose. However, it doesn't specify what type of content (e.g., files, records, metadata) or distinguish it from sibling tools like 'uploadContentFileAboutOrganization' that handle content creation. The purpose is clear but lacks specificity and differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., content must exist), exclusions (e.g., cannot delete certain content types), or relationships to siblings like 'listContentNames' for identifying content to delete. Usage is implied by the action but without explicit 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?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose permissions needed, rate limits, whether it's idempotent, or what happens on success/failure. 'Upload' suggests mutation, but no safety or side-effect information is provided.
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 with no wasted words. It's front-loaded and appropriately sized for the tool's apparent complexity, 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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on what 'content' means, how the upload integrates with the organization, or what the tool returns. Given the context, more information is needed for 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 parameters 'url' and 'role' are documented in the schema. The description adds no meaning beyond the schema, as it doesn't explain parameter interactions or provide examples. Baseline 3 is appropriate since the schema handles documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Upload content url about the organization' states the action (upload) and resource (content url about organization), but it's vague about what 'content' entails and doesn't distinguish from sibling 'uploadContentFileAboutOrganization'. It provides a basic purpose but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'uploadContentFileAboutOrganization' or 'searchOrganizationContents'. The description implies uploading from a URL, but it doesn't specify contexts, prerequisites, or exclusions, leaving usage unclear.
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 it's a list operation, implying read-only behavior, but doesn't address key aspects like whether it's paginated, rate-limited, requires authentication, or what the return format is. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all content names') and includes the optional filtering detail. There's no wasted text, making it highly concise and well-structured for quick comprehension.
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 no annotations, no output schema, and a simple parameter, the description is incomplete. It doesn't explain what 'content names' entail (e.g., file names, titles), how results are returned, or any limitations. For a list tool with siblings offering similar functionality, 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?
The schema description coverage is 100%, with the single parameter 'name' documented as 'Optional name filter to search for specific content'. The description adds minimal value by restating this as 'optionally filtered by name', but doesn't provide additional context like wildcard support or case sensitivity. Baseline 3 is appropriate since the schema does the heavy lifting.
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: 'List all content names from the organization's database optionally filtered by name.' It includes a specific verb ('List'), resource ('content names'), and scope ('organization's database'), which makes the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'searchOrganizationContents', which might offer more advanced filtering or different output formats.
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 minimal guidance by mentioning optional filtering by name, but it doesn't specify when to use this tool versus alternatives like 'searchOrganizationContents'. There's no mention of prerequisites, performance considerations, or exclusions, leaving the agent with little context for tool selection among siblings.
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 full burden. It mentions 'semantic search' which adds some behavioral context beyond basic search, but doesn't disclose critical traits like whether this is read-only (likely, but not stated), what permissions are needed, rate limits, pagination behavior, or what the search covers (e.g., metadata, full text). For a search tool with zero annotation coverage, this is inadequate.
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 purpose. There's no wasted text, but it could be slightly more structured by explicitly mentioning the tool's scope or constraints.
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 no annotations, no output schema, and a simple input schema, the description is incomplete. It lacks information on behavioral traits (e.g., safety, performance), output format (what results look like), and usage context relative to siblings. For a search tool in an organization content system, this leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the single parameter 'query' is documented in the schema as 'The search query'), so the baseline is 3. The description adds no additional meaning about the parameter beyond what the schema provides—it doesn't explain query format, length limits, or how semantic search interprets the query.
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 ('search through') and resource ('organization's content database') with the method 'using semantic search'. It distinguishes from siblings like listContentNames (listing names only) and upload tools (adding content). However, it doesn't explicitly contrast with deleteOrganizationContent.
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 is provided. The description implies searching content, but doesn't specify when to prefer this over listContentNames for browsing or when semantic search is appropriate versus other search methods. No exclusions or prerequisites are mentioned.
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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