fruits-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@fruits-mcplist all articles in the FAQ category"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
fruits-mcp
MCP server for the Product Fruits Knowledge Base API.
Requirements
uv installed
Windows:
winget install astral-sh.uvmacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | shRelated MCP server: ProductLane MCP Server
Claude Desktop setup (Windows)
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"fruits-mcp": {
"command": "uvx",
"args": ["--from", "git+https://github.com/lucassampsouza/fruits-mcp", "fruits-mcp"],
"env": {
"PRODUCT_FRUITS_API_TOKEN": "your_token_here"
}
}
}
}Restart Claude Desktop after saving.
Claude Code setup
claude mcp add fruits-mcp uvx -- --from git+https://github.com/lucassampsouza/fruits-mcp fruits-mcpThen set the token:
# Add to your shell profile or set in Claude Code settings
export PRODUCT_FRUITS_API_TOKEN=your_token_hereAvailable tools
Tool | Description |
| List articles, optionally filtered by category |
| Create/update articles (up to 50, up to 20 languages each) |
| Delete an entire article |
| Delete a specific language from an article |
| Delete a specific content version |
| List all categories |
| Get a category by correlationId |
| Create/update categories |
| Update a category |
| Delete a category |
| Upload an image (Base64) |
Available Tools
11 toolsdelete_articleB
Delete an entire article (all languages) by its correlation ID.
| Name | Required | Description | Default |
|---|---|---|---|
| correlation_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. It only says 'delete' but omits consequences like irreversibility, effect on related data, or authorization requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, directly states action and scope, no wasted words, front-loaded with important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple delete with one param, but lacks info on post-deletion behavior, error handling, or prerequisites. Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not add meaning beyond the schema's 'Correlation Id' title; does not explain what a correlation ID is or how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'Delete', resource 'entire article (all languages)', and identifier 'correlation ID'. Distinguishes from siblings like delete_article_content_version by specifying 'all languages'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies that this tool is for deleting all languages of an article, and siblings handle partial deletions, but no explicit when-to-use or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_article_content_versionC
Delete a specific content version from an article language.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | Yes | ||
| content_id | Yes | ||
| correlation_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks any behavioral details beyond the deletion itself, such as reversibility or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no excess, but it is too brief for the complexity of a 3-parameter required tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and minimal description; the agent lacks context on return values or implications of deletion, though the operation is relatively simple.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the three required parameters (correlation_id, lang, content_id), leaving the agent to infer their meaning from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Delete' and the resource 'specific content version from an article language', distinguishing it from siblings like delete_article or delete_article_language.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description is purely functional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_article_languageA
Delete all content versions for a specific language from an article.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | Yes | ||
| correlation_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It discloses that the tool deletes all content versions for a specific language, indicating destructive action, but does not detail permissions, side effects, or what happens to the article structure. Adequate 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, efficiently conveying the core action. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a deletion tool with 2 parameters, no output schema, and no annotations, the description is minimal. It lacks details on return values, confirmation, or error states, leaving gaps for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning to the parameters beyond their names; it does not explain that 'lang' likely refers to a language code or describe the purpose of 'correlation_id'. Schema coverage is 0%, and the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (delete), resource (content versions for a language from an article), and effectively distinguishes from sibling tools like delete_article and delete_article_content_version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for removing a language from an article but provides no explicit guidance on when to use it versus alternatives like delete_article_content_version. No when-not-to-use 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.
delete_categoryB
Delete a category by its correlation ID.
| Name | Required | Description | Default |
|---|---|---|---|
| correlation_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits such as side effects, reversibility, or permissions needed. It adds minimal value beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words, appropriately sized for the information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description is too minimal. It does not explain what a correlation ID is, whether the category must exist, or what happens after deletion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning by specifying 'by its correlation ID', which gives context beyond the schema. However, with 0% schema description coverage, more detail would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (delete), resource (category), and method (by correlation ID). It distinguishes from sibling tools that delete other entities like articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like update_category or list_categories. No prerequisites or conditions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_categoryC
Retrieve a specific category by its correlation ID.
| Name | Required | Description | Default |
|---|---|---|---|
| correlation_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must cover behavioral traits. It only states 'Retrieve', implying a read operation, but omits any mention of side effects, permissions, error handling (e.g., if category not found), or the type of return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but could be structured to include more details like return value or prerequisites without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no output schema, no annotations), the description lacks completeness: it does not describe the return format, error conditions, or any prerequisites, leaving the agent with incomplete knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter with 0% description coverage, and the description only says 'by its correlation ID' without elaborating on what correlation_id is, its format, or how to obtain it, adding minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'category', and specifies the identifier 'correlation ID', which distinguishes it from sibling tools like list_categories (listing all) or update_category (modifying).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With siblings like list_categories and update_category, explicit context for when to choose this tool is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
import_articlesA
Import or update knowledge base articles (max 50 per request, up to 20 languages each). Each article requires 'correlationId' and 'contents'. Each content entry requires 'lang', 'title', and 'content'. Optional fields: 'format' (markdown|html), 'publishStatus' (published|draft), 'categoryCorrelationId', 'isPrivate', 'ignoreImportErrors'.
| Name | Required | Description | Default |
|---|---|---|---|
| articles | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses upsert behavior, max limits, and required fields but lacks details on authentication, error handling, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with key limits, and logically organized. One minor point: it could be even more concise by using a bullet list for optional fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex import tool with minimal schema and no output schema, the description covers input structure, constraints, and optional fields adequately. Lacks details on return values or error scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with a single 'articles' parameter. The description fully compensates by detailing the required and optional fields for each article and content entry, including nested structures.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Import or update knowledge base articles' with specific constraints (max 50, up to 20 languages). It distinguishes from sibling tools like delete_article and list_articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the context of bulk import/update is clear from the constraints. No direct guidance on 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.
import_categoriesA
Import or update knowledge base categories. Creates if not found, updates if existing. Each category requires 'correlationId' and 'name'. Optional: 'parentCorrelationId', 'isPrivate', 'order'.
| Name | Required | Description | Default |
|---|---|---|---|
| categories | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses create/update behavior based on existence but lacks details on error handling, atomicity, or partial failures for the batch array input. With no annotations, the description should provide more behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four concise sentences: purpose, upsert behavior, required fields, optional fields. No unnecessary words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers operation, parameters, and upsert behavior. Lacks return value description (e.g., list of created/updated category IDs) and error scenarios, but adequate for a simple import tool given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% coverage for the array object properties. The description fully compensates by listing required fields (correlationId, name) and optional fields (parentCorrelationId, isPrivate, order), adding essential meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Import or update knowledge base categories' with specific verbs and resource. It distinguishes from sibling tools like 'update_category' by indicating batch upsert behavior. The operation is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for batch import/update but does not explicitly state when to prefer this over siblings like 'update_category' or 'list_categories'. No when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_articlesA
List all knowledge base articles. Optionally filter by category correlation ID.
| Name | Required | Description | Default |
|---|---|---|---|
| category_correlation_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states listing and filtering, omitting details on pagination, ordering, error handling, or behavior with invalid filters. Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the action. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description is adequate but could be more complete by mentioning response format, pagination, or ordering. It lacks enough detail for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by naming the parameter 'category correlation ID' and its filter role. However, it lacks details on its format, source, or default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists all knowledge base articles and mentions the optional filter by category correlation ID. It uses a specific verb and resource, and distinguishes from sibling tools (delete, import, update, upload).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing articles, but provides no explicit guidance on when not to use or alternatives. It lacks context about prerequisites or when to choose this over other tools, though the sibling list is limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesA
Get all categories from the knowledge base.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. For a read-only list operation, the description is adequate but lacks details on pagination, ordering, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence, no wasted words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no output schema, the description is complete and sufficient for an agent to understand the basic function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, baseline 4. The description correctly implies no additional input is needed, matching the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'all categories', which is specific and distinguishes from sibling tools like get_category (single) and delete_category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like list_articles or get_category. The description only states what it does without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_categoryC
Update an existing category by its correlation ID.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| order | No | ||
| is_private | No | ||
| correlation_id | Yes | ||
| parent_correlation_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits like idempotency, partial update behavior, error handling for invalid correlation IDs, or side effects. The description is minimal and does not add context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundancy, but it is overly brief at the expense of completeness. While front-loaded with the key action, it lacks necessary detail for effective tool selection and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no output schema, no annotations, and 0% schema description coverage, the description is severely incomplete. It omits critical information about updatable fields, default behaviors, error conditions, and return values, making it insufficient for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 4 optional parameters (name, order, is_private, parent_correlation_id) are explained in the description. The description only mentions correlation_id, which is already in the schema. No additional semantic value is provided for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and resource 'category', and identifies the key identifier 'correlation ID', which distinguishes it from siblings like delete_category, get_category, and list_categories. However, it could be more explicit about the specific fields that can be updated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when to update vs. delete or retrieve a category. There is no mention of prerequisites or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upload_imageA
Upload an image to use in knowledge base articles. Provide the image as a Base64-encoded string along with its MIME type (e.g. 'image/png') and filename (e.g. 'cover.png').
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | ||
| mime_type | Yes | ||
| image_base64 | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only specifies input format (Base64, MIME type, filename) but omits essential details: what happens after upload (e.g., returns ID/URL?), any side effects, size limits, or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. The first states purpose, the second gives parameter format instructions. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Input format is well-covered, but output is missing entirely. Users don't know what the tool returns (URL, ID, success confirmation). Given no output schema, description should explain result. Lacks completeness for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description carries full burden. It adds meaning beyond schema titles: explains image_base64 is Base64-encoded, provides MIME type example ('image/png'), and filename example ('cover.png'). Could further specify constraints like max file size.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Upload an image') and its purpose ('to use in knowledge base articles'). No sibling tool performs uploading, so it is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when needing an image for articles) but provides no explicit guidance on when not to use it or alternatives. It lacks exclusions or context for comparing with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
The tools are mostly distinct, with clear descriptions for each. However, the multiple delete tools for articles (delete_article, delete_article_content_version, delete_article_language) could cause confusion at first glance, though their descriptions clarify the scope.
All tools follow a consistent verb_noun pattern in snake_case, such as delete_article, import_categories, list_categories. The naming is predictable and uniform across the set.
With 11 tools, the set is well-scoped for a knowledge base management system covering articles, categories, and images. Each tool serves a distinct purpose and the count is appropriate.
The set covers basic operations but has notable gaps: no get_article or update_article tool (only bulk import), and image management lacks delete/update capabilities. This may force workarounds.
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