get_graph_version_historyGet the deployment and version history for a graph project. Shows all schema changes with commit SHAs, timestamps, version numbers, and messages. Use this to find a specific version for rollback operations.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | Project ID (UUID) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by detailing exactly what the history includes (commit SHAs, timestamps, version numbers, messages) and framing it as 'deployment and version history,' which goes beyond the minimal read-only disclosure. 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 two sentences, front-loaded with the primary action and resource, followed by a concise list of returned details and a clear use case. Every sentence adds value; there is no waste.
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 read-only tool with one parameter, the description is complete: it states the purpose, the exact return content (schema changes, commit SHAs, timestamps, version numbers, messages), and the intended use case. Since there is no output schema, the description effectively covers what the agent needs to know.
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 input schema already fully documents the single parameter (project_id with description 'Project ID (UUID)'), so schema coverage is 100%. The description adds no additional meaning about the parameter beyond what the schema provides. Baseline of 3 is appropriate since the description does not need 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 uses a specific verb ('Get') and resource ('deployment and version history for a graph project'), clearly distinguishing it from the generic sibling get_version_history. It also specifies the content (schema changes, commit SHAs, timestamps, version numbers, messages), leaving no ambiguity about what the tool does.
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 explicitly states when to use the tool: 'Use this to find a specific version for rollback operations.' This gives clear context for usage, though it does not explicitly mention alternatives or when not to use it. The context is strong enough to guide an agent to this tool over siblings like rollback_graph_project or get_graph_schema_at_version.
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.
Most tools are clearly differentiated by domain (project vs graph_project) and action (create, get, list, delete). The main ambiguity is get_project vs get_project_info, which both claim to return detailed project information. Otherwise tool boundaries are clear.
The server follows a strong verb_noun convention, with parallel naming for graph and non-graph tools (create_project/create_graph_project, deploy_staging/deploy_graph_staging). Minor deviations include bulk_create_graph_nodes and fulltext_search_graph, but patterns remain predictable.
48 tools is a heavy surface, even when accounting for the two parallel product domains (relational and graph). Many tools are near-duplicates across domains, and the count exceeds the 25-tool threshold that feels manageable. It would benefit from consolidation or sub-servers.
Both project types have full life-cycle coverage: create, schema management, deployment, rollback, and deletion, plus graph data operations including bulk, search, and traversal. Minor gaps exist, such as no update_graph_relationship and the redundant get_project/get_project_info pair, but agents can accomplish core workflows.