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

With no annotations, the description carries the full burden and does well: it discloses that money changes hands ($49), that the call is asynchronous (approve_url → buyer approves in PayPal → report link appears at status_url), and that consent has legal consequences under Austrian FAGG. It omits whether repeat calls create duplicate orders, idempotency, and behavior on invalid or foreign scan_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?

Front-loaded with the action and price, then the return shape, then the consent constraint, then per-argument notes — a sensible order. The Args block is largely non-redundant, though the repeated 'must be true' phrasing and the legal parenthetical add a little bulk.

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, and the description compensates by naming approve_url, status_url, and the eventual report link, plus the approve-then-poll flow. Missing only failure modes (invalid scan_id, unpaid approval timeout) for a payment tool, which is a modest gap rather than a blocker.

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 the description must compensate, and it does: scan_id's provenance is named (from scan_tls_raw), and consent_immediate_delivery's meaning, required value, and legal semantics are explained rather than restated. Both parameters gain meaning that the bare boolean/string schema cannot convey.

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 ('Buy the full post-quantum readiness report'), adds price ($49) and a precondition ('for a prior scan'), which cleanly separates it from the scan_tls / scan_tls_raw / start_monitoring siblings. An agent can tell this is the monetization step, not another scan.

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 ties the input to a sibling ('the scan_id returned by scan_tls_raw') and spells out the exact precondition for consent_immediate_delivery. It lacks a when-not clause (e.g., what to do if the buyer declines consent, or whether a purchase already exists for that scan), so it is clear but not fully routable.

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 supplied, so the description carries the full burden, and it does disclose the shape of the answer (a verdict plus risk explanation and remediation pointers) rather than dumping raw protocol data. It says nothing about the outbound network connection being made, authentication requirements, rate limits, or failure behavior for unreachable hosts, which are the traits an agent most needs for a scanning tool with zero annotation coverage.

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 core capability is front-loaded in the first sentence and the return behavior follows logically. The trailing 'Args:' block is a Python-docstring artifact that duplicates schema content, which is mild waste, though the single argument line still earns its place given 0% schema coverage.

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?

An output schema exists, so the description need not enumerate return fields, and its emphasis on the honest verdict is appropriate. But for a network-scanning tool with no annotations and an undocumented parameter schema, missing details about connectivity assumptions, timeouts, and how the paid-report and monitoring suggestions relate to the sibling tools leave real gaps.

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 one required parameter at 0% schema coverage, the description must compensate, and it does: it identifies the argument as a hostname and gives a concrete example ('example.com'), which disambiguates bare host from URL. It stops short of covering edge cases such as ports, non-default TLS ports, or IP literals.

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 plus the exact technique: checks whether a site negotiates post-quantum TLS key exchange via X25519MLKEM768. That is far more specific than the name alone. It does not, however, contrast itself with the sibling scan_tls_raw, so an agent cannot tell from the description why it would pick this over the raw variant.

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 description implies a quick, verdict-style check whose negative result points toward a 'full report' and 'monitoring options', which map loosely onto buy_full_report and start_monitoring. There is no explicit when-to-use statement, no exclusion of the raw scan variant, and no stated preconditions such as a resolvable public hostname.

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, so the description carries the whole burden. It discloses the return fields (including full_report_price and scan_id, which hints at a paid upsell path), but says nothing about whether the scan is read-only/safe, latency, failure modes, or rate limits for a network-facing operation.

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 sibling comparison comes first and the field list second. The parenthetical is long but each item is informational.

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, listing the returned fields is the right compensation and is done well. However, for a scanning tool the description never says what is scanned (TLS configuration, handshake, certificate), whether the call is costly or rate-limited, or how full_report_price relates to buy_full_report, leaving notable gaps.

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?

Only one parameter, domain, with 0% schema description coverage. The name is largely self-explanatory, but the description adds no detail on accepted formats (bare hostname vs. URL, port, IDN) or what a scan covers for that domain.

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?

Names the sibling scan_tls explicitly and states the differentiator: it returns the structured result rather than (implicitly) a raw one. The parenthetical enumerates the returned fields, so the agent knows the shape of the payoff. It stops short of a clean verb+resource statement of what the scan itself checks, but the contrast with scan_tls gives a usable purpose.

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 definition effectively says when to pick this over scan_tls — when you want the structured grade/key-exchange/certificate fields. There is no negative guidance (no exclusions, no note on when the raw variant is preferable or whether the scan is free).

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 carries the whole burden and does well: it discloses the recurring daily nature, the price and domain caps per plan, that a PayPal plan id is returned to complete an external payment flow, and that consent is legally gated. It omits idempotency, permissions, and what happens on duplicate subscription, so it falls short of a 5.

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 core purpose and pricing are front-loaded and the sentence count is low, but the Python-docstring style 'Args:' block partially restates what the schema already names, which is mild 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?

There is no output schema, and the description compensates by explaining that a PayPal plan id is returned to finish the subscription. Pricing, consent, and all params are covered; only edge cases like repeat or upgrade behavior are 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 0%, yet the description documents all three parameters, including the pricing and domain limits behind each plan value and the exact meaning of consent. This adds substantial meaning beyond the bare string/boolean types in the schema.

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 states a specific verb and resource: 'Start a daily monitoring subscription'. It also names the concrete plans and their pricing/limits, so it is clearly distinguishable from siblings like scan_tls and buy_full_report.

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 precondition for use: set consent to true only after the customer has agreed to email processing and immediate start, which is a real gate on when the tool may be invoked. It does not, however, say when to prefer this over buy_full_report or what to do when a subscription already exists.

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