Save AI prompt results as vault entries with names, tags, model, category, and project details for later retrieval and organization.
Save an AI prompt result as a vault entry
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Result name (required) | |
| tags | No | ||
| type | No | Entry type override | |
| model | No | Model identifier | |
| content | No | Result content (required) | |
| category | No | Summary/category | |
| project_id | No | Project ID or name | |
| source_prompt_id | No | Source prompt entry ID |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden, but it only discloses that this is a write operation creating a vault entry. It says nothing about permissions, overwrite or duplicate-name behavior, validation failures, or whether saving is idempotent.
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 single sentence is front-loaded and contains no filler. It is arguably too terse for an eight-parameter mutation tool, but it does not waste words.
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 an eight-parameter write tool with no annotations and no output schema, one sentence is not enough. Key context such as required fields, side effects, and return behavior is left entirely to the schema and inference.
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 88% across eight parameters, so the schema already documents nearly every field. The description adds only the framing that the saved content is an AI prompt result, without elaborating on any parameter semantics beyond what the schema provides.
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?
States a specific verb and resource ('Save an AI prompt result as a vault entry'), which clearly conveys the action and output. It does not differentiate from close siblings like save_entry, save_artifact, or vault_mem_save, so an agent cannot tell from the description alone which save tool to pick.
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?
There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as save_entry or save_artifact. The only implied usage comes from the phrase 'AI prompt result,' leaving the agent to infer the selection conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.