Read-only: matches an error from a Lovable, Bolt, v0, Cursor or Supabase app to a free fix guide.
Scored across 1 tool
With only one tool there is no possibility of misselection; the description clearly scopes it to matching an error/symptom against vibecodefixes.com guides. Its read-only, non-invasive nature is stated explicitly, leaving no confusion about what it does or does not touch.
The name diagnose_app_problem follows a clear verb_noun pattern and reads naturally. There is no set to compare against, so consistency is trivially satisfied but not demonstrated across multiple tools.
A single tool is thin for a 'Rescue' server; it covers diagnosis but nothing else in the rescue workflow. It fits the narrow lookup purpose, but one tool feels minimal even for that scope.
The diagnosis lookup is coherent, but the surface is a dead end after the first answer: no way to browse or list available guides, refine by host/builder, or retrieve the full guide content beyond a link. For a read-only matcher this may be acceptable, but it leaves obvious follow-up needs unaddressed.
Match an error message or symptom from an app built with an AI app builder or deployed to a common host (Lovable, Bolt, v0, Cursor, Replit, Base44, Supabase, Firebase, Stripe, Vercel, Netlify, Next.js, Clerk, Prisma, OpenAI/Anthropic/Gemini APIs) to the closest plain-English fix guide on vibecodefixes.com. Returns what the error means, likely causes and first steps, quoted from that guide, with a link to the full free guide. If nothing matches confidently it says so instead of guessing. Read-only: it does not connect to, read or change the user's app, accounts or code, and it collects no personal data.
| Name | Required | Description | Default |
|---|---|---|---|
| problem | Yes | The exact error text or a plain description of what is going wrong, e.g. 'new row violates row-level security policy for table todos' or 'my Lovable custom domain is stuck on verifying'. | |
| platform | No | Optional. Where the app was built or runs, e.g. 'Lovable', 'Bolt', 'v0', 'Cursor', 'Replit', 'Supabase', 'Vercel', 'Netlify'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context beyond that: it discloses the return shape (meaning, likely causes, first steps, quoted with a link) and explicitly states it does not connect to, read, or change the user's app/accounts/code and collects no personal data.
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 core purpose and platform scope are front-loaded, and the return/privacy details follow. It is somewhat long with the platform enumeration and privacy disclaimer, but each element carries real signaling value rather than filler.
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?
There is no output schema, yet the description fully explains the return content (meaning, causes, first steps, quoted, link) and the no-match case. Combined with 100% schema coverage on inputs, an agent has everything needed 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%, so both the `problem` and optional `platform` parameters are already well documented with examples in the schema. The description adds no parameter-level detail beyond what the schema provides, which is appropriate given the schema's completeness; baseline 3 applies.
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 states a specific verb and resource: it matches an error/symptom from an AI-built app to the closest plain-English fix guide on vibecodefixes.com. The platforms and hosts are enumerated, so an agent knows exactly what domain this covers without opening the schema.
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?
It clearly frames the input context (an error message or symptom from an AI app builder or common host) and states fallback behavior when nothing matches confidently. There are no sibling tools to route against, so the lack of explicit alternatives is not a gap, but it stops short of explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
diagnose_app_problemLook up an API/SDK error; get the source-linked breaking change, deprecation or advisory and fix.
Free, read-only ship-readiness check for Replit, Lovable and Bolt apps.
Search verified fixes and guides for data tools (Snowflake, dbt, Airflow, Spark…). Paste an error.
Watches your live app, explains every problem in plain language and writes the fix prompt.
Add one secure layer between your agents and this server.