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Vibe Shipped

by io.github.sorindecu
OverviewDiscussionsAdmin

Search apps built with AI

search_apps
Read-onlyIdempotent

Use when the user wants real apps built with AI tools, by keyword, tool or category. Example: {"q":"fitness","tool":"lovable"}

Input Schema

NameRequiredDescriptionDefault
qNoSearch keywords for the app idea or niche, e.g. fitness, invoicing, CRM; every word must match.
toolNoTool id: cursor, claude-code, lovable, bolt, replit, v0, windsurf, rork, base44, grok-bot, other.
limitNoMax results.
categoryNoCategory id as listed by the site, e.g. consumer, saas, dev-tools, mobile-app.
industryNoOptional: the user's industry, e.g. legal, finance, healthcare. Only for anonymous usage stats; does not change results.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / q / description
      Previous value: -"Keywords; every word must match."New value: +"Search keywords for the app idea or niche, e.g. fitness, invoicing, CRM; every word must match."
  2. Changed1 schema field changed
    • addedInput schema / properties / industry
      Added value: +{
+  "description": "Optional: the user's industry, e.g. legal, finance, healthcare. Only for anonymous usage stats; does not change results.",
+  "type": "string"
+}
  3. Changed5 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / category / description
      Added value: +"Category id as listed by the site, e.g. consumer, saas, dev-tools, mobile-app."
    • addedInput schema / properties / limit / description
      Added value: +"Max results."
    • changedInput schema / properties / q / description
      Previous value: -"Keywords"New value: +"Keywords; every word must match."
    • changedInput schema / properties / tool / description
      Previous value: -"Tool id, e.g. cursor, claude-code, lovable, bolt, replit, v0"New value: +"Tool id: cursor, claude-code, lovable, bolt, replit, v0, windsurf, rork, base44, grok-bot, other."
  4. First observed

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds only that results are 'real apps built with AI tools,' which usefully scopes the corpus, but says nothing about result ordering, pagination, or empty-result behavior for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short, front-loaded sentences: trigger condition first, invocation example second. The example is somewhat redundant with the schema's own example values (q='fitness', tool='lovable'), which costs a little efficiency, but there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

All parameters are optional with a default limit of 10 and no output schema, so the description should at least hint at what a result is (a list of apps) and how many are returned by default. Those gaps are minor given full schema coverage and safety annotations, but they leave the agent guessing about response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all five parameters are already documented, including the AND-matching semantics of q and the fact that industry affects only anonymous stats. The description only mirrors those fields in prose plus a sample call, adding marginal meaning beyond the schema; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — search apps built with AI tools — and names the facets it searches on (keyword, tool, category). It implicitly separates itself from get_app (single fetch) and find_tool_for_task (tool lookup), but never names a sibling to make the distinction explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Opens with an explicit trigger: 'Use when the user wants real apps built with AI tools.' That is clear context for invocation, but there are no exclusions or routing advice — e.g., nothing says when to use compare_tools, get_app, or find_tool_for_task instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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