NumeroClaw

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

Beyond the annotations it discloses the things an agent could not infer: nothing is charged at creation, an unpaid order expires after 24 hours, payment is taken at purchase, delivery lands within hours and always within 6, and invalid details create no order at all. The private nature of orderToken is also called out. It never contradicts the destructiveHint=true annotation; it narrows what creation actually does.

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?

Purpose is front-loaded correctly and nothing is padded with boilerplate, but the single paragraph is dense and mixes order lifecycle, product input rules, and a lengthy explanation of Y pronunciation without headings or bullets. An agent has to parse a wall of prose to extract the per-product field requirements.

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 16 parameters and no output schema, the description fills every gap that matters: the per-product field matrix, date format, expiry, delivery window, failure mode, and the exact return fields (orderId, orderToken, product, amount, currency, paymentLink, expiresAt, charged). Nothing an agent needs in order to call this correctly is missing.

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 already 100%, so the baseline is 3, but the description adds cross-parameter rules the schema cannot express: which fields each product needs, that name_analysis takes no dateOfBirth, that current-name fields apply only when the name differs from the birth name, and the reading order for yClassifications (first, middle, last; birth name before current name). That is genuine added meaning, though the Y vowel/consonant explanation is longer than the calling decision requires.

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 opens with a specific verb and resource ("Creates an unpaid order for one NumeroClaw reading") and states the outcome (a link to a payment page). It is clearly distinguishable from the siblings get_order and list_products, since this is the only tool that creates a purchase.

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 explicit preconditions (the person has confirmed product, price, email and details), an exclusion (not for a reading about a child), and a routing rule (one order per person per reading; a second order is a second purchase). It also names the escalation path (email hello@numeroclaw.com with the order id) instead of inventing a retry.

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?

Goes well beyond the readOnly/idempotent annotations by enumerating every possible status value, explaining that delivery happens only by email, and setting a timing expectation (usually a few hours, always within 6). It also clarifies that a 'failed' status implies a refund after human review, which prevents the agent from misreporting an outcome.

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?

Front-loads purpose and usage before enumerating statuses and edge cases, and every sentence carries operational value. It is somewhat long and slightly repetitive about the writing-time expectation, but nothing is padding.

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, so the description fully carries the burden of describing return values — statuses, amount, payment link, timing, and message — and it also covers the failure/refund path. Nothing an agent needs in order to call and interpret this tool is missing.

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 both parameters are already documented as being returned at order creation, so the description's 'both returned when the order is created' mostly restates the schema. The added hint that orderToken is a private credential is useful but marginal, 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 — 'Returns the status of a NumeroClaw reading order' — which is immediately distinguishable from the sibling create_order and list_products. The agent knows exactly what this tool retrieves 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?

Gives a clear trigger condition: 'Use it when the person asks whether their order is paid or their reading is ready.' It does not explicitly name create_order or list_products as alternatives or state when not to use it, but the trigger is unambiguous enough to route correctly in practice.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description still earns credit for adding the no-input contract and a detailed account of what each returned record contains, including price currency, sale state, delivery time, refund terms, sample links and orderability — information no structured field supplies. It omits nothing an agent plausibly needs for a static catalog read, though it does not address failure or empty-catalog 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?

Three sentences, front-loaded with the what, then the when, then the return shape. The final sentence is long but enumerates distinct fields rather than repeating itself. Slight density cost keeps it off a 5.

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, so the description must carry the return-value burden, and it does so thoroughly by naming the product ids, pricing, sale state, delivery, refunds, links and prerequisites. For a zero-parameter read whose annotations cover safety, nothing material is missing.

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 zero parameters, the baseline is 4, and the description reinforces it by stating "Takes no input," removing any doubt about whether a query argument is expected. There is no parameter meaning left 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 gives a specific verb and resource ("Lists the numerology readings available from NumeroClaw") and immediately enumerates the three items in the catalog (Theme, Name Analysis, Birthday Portrait). The sibling tools create_order and get_order operate on orders, so the resource boundary is unambiguous without opening any 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 states the triggering situations explicitly: someone asking which readings exist, what they cost, or what details a reading needs. That is concrete when-to-use guidance rather than an implied purpose. It stops short of naming alternatives or exclusions, though the sibling set makes that largely unnecessary.

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