Delete one owned private document and its live FTS entry.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | ||
| collection_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true. The description adds valuable context by noting that the tool also removes 'its live FTS entry' and restricts to 'owned private' documents, which are behavioral specifics not present in the schema or annotations. No contradiction with annotations.
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, front-loaded sentence with no unnecessary words. It efficiently conveys the primary action and side effect without redundancy.
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 two-parameter delete operation with an output schema and annotations covering destructive/idempotent behavior, the description provides the essential action and side effect (FTS entry deletion). No additional context is required for an agent to call it 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%, yet the description does not explain collection_id or document_id beyond their titles. It fails to compensate for the lack of schema descriptions, leaving the agent to infer meanings solely from parameter names and titles, which is a significant gap for this low-coverage scenario.
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 'Delete one owned private document and its live FTS entry' states a specific verb (Delete) and resource (owned private document), and distinguishes it from sibling tools like delete_personal_rag_collection by focusing on documents. It clearly conveys the action and scope.
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 phrase 'owned private' implies it applies only to the user's own private documents, offering implicit usage guidance. However, it does not explicitly state when to use this tool versus alternatives (e.g., delete_personal_rag_collection) or mention any exclusions beyond ownership/visibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action: problem lifecycle, knowledge reading/search/context, candidate submission/review, and experience verification. Even similar tools like get_knowledge, search_knowledge, and retrieve_context are clearly differentiated by their descriptions.
All tool names follow a consistent snake_case verb_noun pattern with no mixed conventions or vague verbs. Names accurately reflect their actions and objects, making the set predictable and easy to navigate.
At 16 tools, the count is slightly above the typical 3-15 range but still reasonable given the multi-faceted domain (problems, knowledge, candidates, experiences). Each tool appears to have a specific purpose, though a few could potentially be consolidated.
Core workflows are covered: create/claim/manage problems, submit/review candidates, publish/retrieve knowledge, and verify experiences. Minor gaps exist such as no explicit close/cancel operation for problems, but agents can work around these with existing tools.