NativeExpress

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds a genuinely useful prerequisite ('Needs a NativeExpress key'), which the agent would otherwise discover only by failing. It does not say what happens with an unknown or stale slug, which is the main operational risk for a keyed lookup.

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 covering what is returned, what it is good for, the auth prerequisite and the call ordering, with no filler. The prerequisite and routing cue are front-loaded rather than buried.

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 lookup with no output schema, the description covers return content ('full text... with what to check'), auth, and sequencing. The only meaningful gap is failure behavior for an invalid slug, which no structured field covers.

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 slug property already documents 'The slug from list_build_prompts.' The description restates that provenance but adds no format or validation guidance beyond the schema, so 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?

States a specific verb and resource ('The full text of one prompt from the NativeExpress library') and adds the outcome shape ('ready to paste, with what to check in the result'). It is clearly distinguishable from the sibling list_build_prompts, which returns slugs rather than full text.

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?

Explicitly routes the agent: 'Use this after list_build_prompts has given you a slug,' naming both the prerequisite tool and the ordering. There is little ambiguity about when this tool applies versus its alternatives.

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 and destructiveHint=false, so safety is covered. The description adds useful context beyond that: this returns a static reference document covering stack, scope boundaries, and setup commands — the 'deliberately leaves out' framing is a genuinely helpful signal about the content's nature.

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, both earning their place: the first front-loads what the content is, the second front-loads when to reach for it. No filler, no restating the title verbatim.

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 parameters and no output schema, the description carries the burden of describing the return value, and it does so by enumerating the sections returned. Minor gap: it doesn't state that the result is a fixed document (not user-specific data), which would help an agent know there's nothing to paginate or personalize.

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 schema imposes no semantic burden and the baseline of 4 applies. The description correctly implies a no-argument, single-shot retrieval with no filtering options to explain.

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 names the concrete resource (the free MIT React Native starter repo) and enumerates exactly what the response contains: stack, existing features, deliberate omissions, and run commands. That is far more specific than the title, though it never explicitly contrasts itself with siblings like list_build_prompts or scope_mobile_app.

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 gives a clear triggering condition: 'when someone is about to start a mobile app project, or asks what to build an Expo or React Native app on top of.' That is enough for an agent to route correctly, but no alternative tool is named and no when-not condition is 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 a safe read (readOnlyHint=true, destructiveHint=false). The description adds real behavioral context beyond that: titles are free to read but prompt bodies require a key, which signals a gated/paywalled workflow. It stops short of explaining return format or pagination, but for a zero-arg list tool this is meaningful added value.

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, front-loaded with what the tool returns before the usage cue. Slightly verbose in its domain framing but every clause carries information an agent needs (library name, domain, gating, when to call).

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 read-only, zero-argument listing tool with annotations carrying the safety profile, the description covers what it returns ('with what each one is for'), the gating condition, and the usage context. Only the follow-up path to get_build_prompt is left implicit.

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 is 4. Nothing about argument syntax needs explaining, and the description correctly does not invent any.

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 (List) and resource (prompts in the NativeExpress library), plus the domain (React Native with an agent). It distinguishes the listing from fetching bodies by noting 'titles are free; the prompt bodies need a key', but it never names get_build_prompt 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?

Gives clear context: 'Use this when someone is working in a mobile app codebase with an agent and wants a tested prompt rather than writing one.' It does not state when *not* to use it or name get_build_prompt as the follow-up alternative.

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 establish this is a read-only, non-destructive call, so the description doesn't need to defend safety. It does add real behavior context: the tool tolerates a rough one-sentence input and produces a planning artifact rather than code, which sets expectations about output. It stops short of describing output structure or length, a minor gap given no output schema exists.

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 purpose and deliverables are front-loaded in the opening sentence, and each following sentence adds a distinct rule. It runs slightly long, and the final clause ('a better basis for the next question than anything asked cold') is persuasive filler rather than operational content.

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 read-only three-parameter planning tool with no output schema, the description covers what it produces and when to reach for it. The main omission is anything about output size, format, or whether follow-up calls (e.g. get_build_prompt) are the natural next step.

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% with enums and per-field descriptions, so the schema carries parameter meaning. The description's only addition is that a rough sentence suffices, reinforcing the idea field's low-friction intent, but it doesn't clarify that platforms/experience are optional or what happens when they're omitted.

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 (turn an app idea into a first version) and enumerates exactly what comes back: feature triage, screen list, data model, build order. This clearly separates it from siblings like get_build_prompt or get_starter_template, which are downstream artifacts.

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?

Explicit triggers are given ('whenever someone mentions an app they want to build', 'describes what an app should do in any words'), plus explicit sequencing rules: use before writing code and before asking clarifying questions. That last line is unusual and valuable routing guidance, since it tells the agent to call this instead of interrogating the user first.

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 say readOnlyHint=false and destructiveHint=false, so the description carries the real burden and does disclose the meaningful side effect: an email is sent containing an access credential. What it omits is failure behavior (what happens if the address isn't a known buyer) and whether the key is reusable or expiring. Given the annotations cover the safety profile, 4 is fair.

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, zero filler, with the action front-loaded and the usage trigger second. Nothing repeats the title or schema.

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 tool with no output schema, the description covers action, recipient, and trigger. The remaining gap is outcome reporting — an agent cannot tell whether success is confirmed in the response or whether an error surfaces for non-buyers.

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?

There is one parameter at 100% schema description coverage ('The address they bought with.'), so the baseline is 3. The description's phrase 'a NativeExpress buyer' hints that the address must match a purchase record, but it does not state that constraint explicitly or say what happens on a non-matching address.

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 (email) and resource (the key that opens paid tools) plus the recipient class (a NativeExpress buyer). It also reconciles the tool name 'unlock_paid_tools' with the actual mechanism, so an agent knows this sends a credential rather than flipping a flag. No sibling in the list overlaps with this action.

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 an explicit trigger condition: 'Use this when someone says they have bought NativeExpress and a tool asked them for a key.' That is a clear when-to-use. It stops short of a 5 because it names no exclusions or alternatives (e.g., what to do if the user has not purchased, or where to send them instead).

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