get_errorsGet recent runtime errors for an app (last 20). Useful for diagnosing issues before updating.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max errors to return (default 20) | |
| 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the behavioral detail of returning the 'last 20' errors and emphasizes 'recent', which provides context beyond the structured annotations without contradicting them.
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 efficiently written in two short sentences with no filler. It front-loads the action and scope, and the second sentence adds a relevant use case. Every word earns its place.
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 no output schema and two well-documented params, the description provides enough context: what it does, the scope, and a use case. Annotations cover the safety profile, so nothing critical is missing for an agent to call it correctly.
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 100% and both parameters (app_id, limit) have descriptions in the schema. The description does not add any meaning beyond what the schema already provides; it only mentions 'last 20' which mirrors the default value, so no extra value is added.
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 ('Get'), the resource ('recent runtime errors'), and the scope ('for an app', 'last 20'). It distinguishes itself from sibling tools like get_app_status or get_app_analytics by focusing specifically on errors, so an agent can easily identify what it 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 phrase 'Useful for diagnosing issues before updating' provides a clear context for when to use this tool. While it doesn't explicitly mention exclusions or alternatives, given the tool's simplicity and the absence of a directly competing error-specific sibling, this is sufficient guidance.
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.