Vibe Shipped

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds meaningful behavioral context no annotation provides: the comparison is built from 'sourced apps on Vibe Shipped' and revenue figures are 'stated' (self-reported), which tells the agent how to interpret and caveat the numbers. It still omits error handling for invalid or unknown tool ids.

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?

A single dense sentence with the comparison scope front-loaded and the output dimensions enumerated after the colon. No filler, no restatement of the tool name.

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?

With no output schema, the description usefully enumerates what the comparison returns, which is exactly what the agent needs. The remaining gap is what happens on an unrecognized tool id, but for a read-only single-parameter tool this is close to sufficient.

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 coverage is 100% and the single parameter is documented with an example (["cursor","lovable"]). The description's '2-6' bound merely restates minItems/maxItems already in the schema, adding no new meaning.

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?

States a specific verb and resource ('Side-by-side comparison of 2-6 AI build tools') plus the exact comparison dimensions returned (app counts, revenue totals/medians, top apps, pricing). An agent can tell this apart from list_tools/top_tools by the multi-tool comparison scope, though no sibling is named explicitly.

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?

Usage is only implied: the '2-6 tools' framing signals this is for comparing multiple tools rather than fetching one. There is no explicit when-to-use statement, no exclusion (e.g. 'use list_tools to discover ids first'), and no named alternative such as top_tools.

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

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

readOnlyHint=true already establishes this as a safe read, so the bar is lower; the description adds that the response includes source and a Vibe Shipped link, which is useful return-content context. It says nothing about auth needs, rate limits, or behavior for a missing/invalid slug.

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?

One sentence, front-loaded with the verb and resource, with the response contents trailing. Nothing is padded or redundant.

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 single-parameter read-only tool with no output schema, the description is adequate but thin: it covers what is returned at a high level yet omits slug provenance, error behavior, and any link to the sibling search tools that produce slugs. No output schema exists, so return-value explanation is legitimately on the description, and it is only partial.

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 single slug parameter has 0% schema description coverage, so the description carries the load and does state that lookup is keyed by slug. It adds no format hints (e.g., slug shape or case sensitivity) beyond the schema's bare 'string' type.

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?

States a specific verb (Get) and resource (one app) with the identifier key (slug), which cleanly separates it from the list-oriented siblings latest_apps and search_apps. It never names those siblings, so the differentiation is inferred from 'one app' rather than stated.

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?

No when-to-use guidance, no stated prerequisites, and no reference to search_apps as the source of the slug. The only hint is 'by slug', leaving the agent to infer the lookup-after-search workflow.

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

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

The readOnlyHint=true annotation already establishes this is a safe, non-mutating read, so the description is not carrying the safety burden. What it fails to add is anything operational: ordering guarantees, how the 'built with AI' criterion is applied, pagination behavior, or what happens when limit exceeds the result set. With annotations present the bar is lower, but the description still contributes almost no behavioral context.

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?

It is a single front-loaded sentence with zero filler, which is structurally clean. But its brevity comes from omission rather than efficiency, so it reads as under-specified for a discovery tool with an adjustable limit rather than genuinely concise.

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 list tool with one optional parameter, no output schema, and only a readOnly annotation, the description should at minimum clarify ordering, what 'built with AI' scopes, and how limit behaves. None of that is present, leaving the agent with a bare resource name.

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 single parameter 'limit' has 0% schema description coverage, and the description never mentions it, so its meaning (number of apps returned vs. page size), interaction with defaults, or maximum is left entirely to the schema's numeric constraints. Because the one parameter is undocumented in prose, the description does not compensate for the coverage gap.

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 phrase 'Most recently added apps built with AI' tells the agent what collection is returned and implies reverse-chronological ordering plus a domain qualifier, which is more than a bare restatement of the name. However, it is a noun phrase with no verb and no differentiation from siblings like search_apps or list_tools, so an agent cannot tell from the text alone why it would pick this tool over those.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the alternatives (search_apps, get_app, list_tools) that clearly overlap with this listing tool. The agent must infer that this is the default browse/discovery entry point rather than a filtered search.

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

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description goes further by enumerating what the response contains (what each tool is, best use, pricing with source, app counts, revenue totals/medians, top apps, new listings) — valuable given there is no output schema. It stops short of mentioning result size, ordering, or pagination.

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?

A single dense sentence, front-loaded with the verb and the tool roster before the field list. Nothing is wasted, but the trailing enumeration is long and comma-spliced, which makes the payload harder to scan than a short list would.

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?

With no input parameters and no output schema, the description carries the burden of telling the agent what comes back, and it does so thoroughly — pricing, counts, revenue, top apps, recent additions. Missing only operational details such as result volume and ordering, which are minor for an unfiltered catalog call.

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 tool takes zero parameters, so the baseline of 4 applies. There are no argument semantics to explain, and the description correctly spends its length on returned content instead.

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?

Specific verb (List) plus a concrete resource (AI build tools tracked by Vibe Shipped) with named examples (Cursor, Claude Code, Lovable, Bolt, Replit, v0, Windsurf, Rork). The enumerated return contents make it easy to recognize as the catalog/overview tool, though it never explicitly distinguishes itself from top_tools or latest_apps, which overlap with 'top apps' and 'new listings in the last 30 days'.

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?

Usage is only implied by the content description: an agent can infer this is the browse-everything entry point, but there is no explicit when-to-use statement and no mention of when to reach for compare_tools, top_tools, latest_apps or search_apps instead. No prerequisites or exclusions are given.

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

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds real behavioral value by disclosing the result shape (each result carries a Vibe Shipped page link suitable for citation) and the tool scope it indexes. It says nothing about pagination, ranking, or auth.

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?

Two tight sentences with no filler, and the core purpose is front-loaded before the result-format detail. The parenthetical tool list is long but it is doing real work by naming indexed sources.

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 4-param, no-required search tool with no output schema, the description covers what it searches and what comes back. It omits any guidance on category semantics, the limit cap, and how results are ordered, leaving the agent to guess at query shaping.

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 50%, so the schema documents q and tool while limit and category are bare. The description partly compensates by mapping the `tool` enum values to recognizable brand names (Cursor, Claude Code, Lovable, etc.), but adds nothing for category or the 1-50 limit.

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?

States a specific verb+resource (search apps) with a clear qualifier: apps people shipped with AI coding tools. It implicitly separates itself from browsing siblings like latest_apps and top_tools, but never names an alternative to sharpen the distinction.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no mention of siblings (latest_apps, top_tools, get_app). The only usage signal is implicit — that you supply keywords. An agent must infer routing from tool names alone.

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

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

Annotations only declare readOnlyHint=false and destructiveHint=false, so the description carries the interesting behavior: submission lands in a 'review queue' rather than being published directly, and a public proof link is mandatory. It stops short of describing auth needs, duplicate handling, or what the submitter gets back, but it meaningfully extends the annotation surface.

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?

Two sentences, purpose front-loaded, the hard requirement in the second. No filler and no restatement of the tool title.

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 6-parameter write tool with no output schema, the description covers the core action and the source-link requirement but says nothing about what happens after submission (queued, approval, rejection) or about half the input fields. It is minimally sufficient rather than 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 only 33%, so the description must compensate, and it partly does by elaborating source_url as a public post, launch, or interview and restating it as required. However, title, url, tools, one_liner and builder_name get no semantic help from either source, leaving required 'url' and 'title' thin.

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?

States a specific verb (submit) plus resource (an AI-built app) and destination (Vibe Shipped review queue), which instantly separates it from the read-only siblings get_app, latest_apps, list_tools and search_apps. An agent can tell this is the only write path in the toolset without opening a 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?

Gives clear triggering context (submitting an AI-built app) and a precondition (a public source link is required), but offers no explicit when-not guidance or named alternatives. Adequate routing information without exclusions.

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

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

readOnlyHint=true already tells the agent this is a safe, non-mutating read, so the description's burden is lower. It adds one useful data caveat by repeating 'stated' revenue (i.e., self-reported, not verified), but says nothing about result ordering stability, ties, or how many rows the caller should expect given the limit.

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?

A single front-loaded sentence with no filler; the ranking metrics are presented as a parallel list that is easy to scan. It is dense enough that the parenthetical keyword for each metric doubles as the enum value, which is efficient rather than wasteful.

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?

No output schema exists, so the description should have clarified the return shape (ranked tools with which metrics attached, and whether limit caps the returned rows). Ranking behavior and the metric definitions are covered, but the response contract is not.

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?

With 0% schema description coverage, the description carries the full load and does so for the enum, defining count, revenue, median, and trending in terms an agent can map to intent. The limit parameter is left implicit, though its purpose is largely conveyed by the schema's default of 10 and max of 20.

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?

States a specific verb (Rank) plus resource (AI build tools) and enumerates the four ranking dimensions, so the operation is unambiguous. It does not distinguish itself from siblings like list_tools or latest_apps, whose output (a listing of tools) overlaps with what this tool returns, leaving sibling differentiation to inference.

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 names the sort modes but never says when to choose this tool over list_tools, latest_apps, or search_apps, nor when it is inappropriate. In particular, 'trending' (new listings in last 30 days) clearly overlaps with latest_apps, and no guidance resolves that ambiguity.

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