Permanently delete a specific fact from a DataForge project version by providing project, version, and fact IDs.
PERMANENTLY DELETES DATA IN DATAFORGE. Delete a fact.
| Name | Required | Description | Default |
|---|---|---|---|
| fact_id | Yes | ||
| project_id | Yes | DataForge project id | |
| version_id | Yes | Project version id |
Changes observed during successful MCP inspections.
v0.3.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already include destructiveHint=true and readOnlyHint=false. The description adds a redundant emphasis on permanent deletion but does not disclose additional behavioral details such as idempotency behavior, cascading effects, or required permissions. It does not contradict the 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 extremely concise and front-loads the destructive warning. Every word earns its place, though the first sentence is broad and partially redundant with the second.
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 destructive operation with three required parameters and no output schema, the description is too sparse. It does not explain scoping, what happens on deletion, or how to ensure the correct project/version/fact context, relying heavily on the schema and tool name.
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 67% (fact_id is not described), which is below the high-coverage threshold. The description does not compensate by explaining what each parameter means or how project_id, version_id, and fact_id relate, so the agent must infer the semantics of the key parameter.
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 uses a specific verb and resource ('Delete a fact') and clearly distinguishes this tool from sibling delete tools such as df_delete_relationship, df_delete_version, and df_delete_measure. The explicit permanence warning also helps the agent understand the operation's weight.
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 given about when to use df_delete_fact versus alternative tools. It does not mention prerequisites, exclusions, or conditions that would select this tool over its many delete siblings, leaving the agent to infer usage from the name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.