Validate Change Set
validate_change_setValidate current app files plus staged change set files before applying.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| app_id | Yes | The app ID | |
| change_set_id | Yes | Change set ID | |
| include_runtime_errors | No |
validate_change_setValidate current app files plus staged change set files before applying.
| Name | Required | Description | Default |
|---|---|---|---|
| app_id | Yes | The app ID | |
| change_set_id | Yes | Change set ID | |
| include_runtime_errors | No |
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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which fully cover the safety profile. The description adds the scope of validation (current app files plus staged change set files), which is useful context. However, it does not disclose what the validation does in detail (e.g., checks runtime errors, returns errors) or what the result means. Given annotations cover the key behavioral aspects, a score of 3 is appropriate.
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, efficient sentence that front-loads the verb and clearly conveys the action and scope. There is no redundance or filler; every word contributes to meaning. It is appropriately concise for its purpose.
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?
The description tells what the tool does but not what it returns or what happens on success/failure. Since there is no output schema, the agent is left guessing whether validation returns a boolean, an error list, or a status. Annotations cover the read-only and idempotent aspects, but the lack of return information is a significant gap for a validation tool. Overall, it is adequate but not fully complete.
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% (2 out of 3 parameters have descriptions). The tool description does not add any additional meaning to the parameters, such as clarifying the purpose of include_runtime_errors, which has no schema description and is not mentioned in the tool description. Since the schema already covers most parameters and the description provides no extra semantic value, a score of 3 is warranted.
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 action (validate), the resource (current app files plus staged change set files), and the context (before applying). It distinguishes itself from sibling tools like apply_change_set by specifying the pre-apply validation step. The verb and resource are specific and unambiguous.
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 'before applying' gives explicit usage context, indicating this tool is meant to be used prior to applying a change set. While it doesn't explicitly mention alternatives (e.g., 'use apply_change_set after validation'), the context and sibling names make the workflow clear. There are no exclusions or when-not-to-use conditions, but the timing guidance is sufficient.
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.