Whysaid — Verify claims, sources & AI answer share

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

No annotations are provided, so description must carry the burden. It reveals the cost ($0.05) and that it uses a live assistant (implying dynamic results), but does not mention latency, possible failure modes, or that it may produce variable responses. Adequate but not comprehensive.

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, compact and informative, with key details front-loaded. Could be slightly more structured with explicit parameter mapping, but it's efficient.

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?

Given the moderate complexity (4 params, no output schema), the description suffices for expected usage: it covers purpose, cost, and type of output. Missing small details like format of report but not critical.

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 0%, so description must compensate. It explains 'prompt' implicitly by 'Ask... a buyer question', and mentions 'brand is named' and 'which competitors appear', which maps to 'aliases' and 'competitors'. It doesn't clarify 'domains' but the field names are self-explanatory.

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 uses strong verbs and specifics: 'ask a live AI assistant', 'report whether a given brand is named, at what position, and which competitors appear'. It clearly differentiates from siblings (verification, provenance) by focusing on competitive/market research.

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 states 'Use for competitive and market research that reflects what assistants say right now', which gives clear context. It does not explicitly mention alternatives or when not to use, but the context is sufficient among siblings.

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?

Since no annotations are provided, the description carries the full burden. It discloses two detection capabilities, the operational consequence of bypassing it (re-ingesting model output), and a cost of $0.25 in USDC. This goes beyond the minimal and adds useful operational context, though it does not describe the output or error behavior.

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 two sentences, front-loaded with the primary function, and includes a clear usage instruction and cost. No wasted words; it is efficient and easy to parse.

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 tool with a single parameter, no annotations, and no output schema, the description covers the core behavior, the intended use case, and a cost consideration. It could optionally mention what the tool returns (e.g., a boolean or confidence), but given the simplicity, it is adequately 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?

The schema has only one string parameter 'content' with 0% description coverage. The description implies the input is text ('piece of text') but doesn't elaborate on format, length limits, or whether it accepts any string. It adds some meaning but does not fully compensate for the lack of schema documentation.

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 tool's function: detecting whether text is model-generated and whether the system has emitted identical content before. This is a specific action on a specific resource (text) and differs from siblings like verify_claim or verify_source, which likely focus on factual verification.

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 advises using the tool before storing text in long-term memory to prevent re-ingestion of model output. This provides a clear context of use, though it does not explicitly mention when not to use it or alternatives. The guidance is actionable and directly tied to the tool's purpose.

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?

No annotations are provided, so the description carries the full burden. It does disclose a key behavioral fact ('Free'), but it does not explain what 'how to pay' means if the service is free, nor what the tool returns (e.g., a list, a message, a link). For a simple informational tool this is adequate but minimal.

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 two short sentences with no filler. 'What each Whysaid verification costs and how to pay. Free.' is front-loaded and every word earns its place. The standalone 'Free.' is abrupt but still informative.

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 zero-parameter, no-output-schema tool, the description covers the essential information: costs and payment method. The only ambiguity is the relationship between 'how to pay' and 'Free,' but overall the description is sufficient for an agent to understand the tool's purpose and invoke it appropriately.

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 has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics because there are none. No additional parameter information is required.

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 tool provides pricing information ('what each Whysaid verification costs') and payment instructions ('how to pay'). It distinguishes itself from the sibling verification/share tools by focusing on cost rather than verification actions. It lacks an explicit verb like 'get' or 'list,' but the noun-phrase framing is still specific and unambiguous.

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 context is implied rather than explicit: the name 'pricing' and description make it obvious this is for cost/payment questions. However, there is no direct guidance on when to use this tool versus alternatives, nor any exclusion criteria. The sibling tools are clearly different in function, so the lack of explicit guidance is a minor gap.

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?

No annotations are present, so the description bears the burden of behavioral disclosure. It adds cost information ($0.35 USDC) and indicates the tool can perform HTTP fetches, file reads, and shell commands. However, it does not warn about potential side effects of shell execution or describe failure/return behavior, leaving notable gaps.

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 extremely concise: two sentences that front-load the purpose and include the practical cost detail. Every word contributes meaning, with no filler or redundancy.

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?

The tool can execute shell commands, which carries safety implications, yet there is no warning about side effects or guidance on selecting check kinds. No output schema exists, and the description does not explain return values, error cases, or how to structure check_spec. Sibling tools like verify_source are not mentioned, so differentiation is weak.

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 input schema has 0% description coverage, and the tool description only loosely maps to parameters: 'claim' is implied, 'check_kind' is referenced as HTTP/file/command, but 'check_spec' remains entirely unexplained. The description adds minimal semantic value beyond what the schema already shows with enum values, failing to compensate for the lack of parameter documentation.

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 tool's core function: independently verifying a claim against a real check (HTTP fetch, file, or command). It contrasts with taking an assertion on trust and specifies the use case of confirming another agent's reported work, making the purpose specific and distinguishable from trusting claims.

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 explicitly says 'Use to confirm work another agent reports as done,' providing a clear when-to-use context. It does not name alternative tools or provide exclusions, but the context is sufficient for an agent to understand appropriate usage.

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?

With no annotations, the description must carry the full burden. It adds a key behavioral trait: 'Costs $0.20 in USDC.' It also describes outcomes (catches dead links, changed pages, unsupported claims). However, it does not disclose return format, error behavior, or whether any side effects occur, limiting full transparency.

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 two sentences long, with the purpose front-loaded in the first sentence and usage context and cost in the second. Every sentence earns its place, with no filler or redundancy.

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 2-parameter tool, the description covers the purpose, when to use, and cost. The absence of an output schema means the return value is not described, which is a minor gap. Also, sibling differentiation is weak, but the tool's scope is clear from the description.

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 the baseline is 3. The description does not add extra meaning beyond the schema; the schema already describes both 'url' and 'contains' clearly. The intended usage of 'contains' is implied by 'actually says what it is claimed to say' but not elaborated.

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 tool confirms a URL is reachable and matches the claimed content, using specific verbs and a defined resource. It does not explicitly differentiate from sibling tool 'verify_claim', but the URL focus provides implicit 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?

Provides explicit context on when to use: 'Use before citing, quoting, or acting on a web source.' It explains what it catches (dead links, changed pages, unsupported claims). It does not name alternatives or exclusions, but the usage context is clear.

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