validate_entity_relationshipsValidate entity relationship metadata and *_id references against existing entity schemas.
| Name | Required | Description | Default |
|---|---|---|---|
| app_id | Yes | The app ID |
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 disclose readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds that the tool validates how *_id references and relationship metadata align with existing schemas, which is useful context beyond annotations. However, it does not disclose what the tool returns upon successful or failed validation (e.g., error list, boolean status, exceptions), which leaves behavioral expectations incomplete.
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 leads with the action verb and specifies the scope. No filler words or redundant details. It is front-loaded and efficient for an agent to parse.
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 tool with only one parameter and no output schema, the description should clarify what the tool returns or signals upon validation failure. This is missing. The agent cannot determine whether to expect structured errors, a boolean, or an exception. This gap is significant for a tool whose purpose is validation, as the caller likely needs to act on the result.
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 fully documents the only parameter, app_id (100% coverage), with a simple description 'The app ID'. The description adds no additional meaning about how app_id is used in the validation context. Since the schema carries the parameter semantics, baseline 3 is appropriate.
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 'validate' and the specific resource 'entity relationship metadata and *_id references against existing entity schemas'. This is precise and distinguishes it from other validation tools like validate_app or validate_change_set. An agent can immediately understand the tool's function without ambiguity.
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 provides no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. It only states what it does, leaving the agent to infer usage from the tool's name and schema. There is no explicit mention of when validation is necessary before other entity operations.
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 have clearly distinct purposes with detailed descriptions, but there are some overlapping pairs like read_app_file/read_app_files and create_entity_records vs seed_entity, which could cause misselection. Singular/plural variants and compatibility tools introduce minor ambiguity, but the majority are well-separated.
Tool names predominantly follow a consistent verb_noun pattern (e.g., create_app, get_entities, delete_secret). There are some variations like 'agency_create_client' and 'seed_entity' that deviate slightly, but the overall convention is predictable and readable.
With 82 tools, the server is far above the typical range and feels overwhelming. Even for a full platform API, the count is extreme and likely increases selection complexity. A more curated set would improve navigability without sacrificing capability.
The tool surface is exceptionally comprehensive, covering app lifecycle, file operations, entity CRUD, versioning, A/B testing, secrets, integrations, domains, agents, scheduling, policies, and member management. No obvious missing operations for the platform's scope; it even includes validation and workflow guidance tools.