Silex Gambling Help

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 adds value beyond that by disclosing what the tool actually returns — a step-by-step plan organized by layer (DNS filtering, locked app installs, bank blocks, self-exclusion) plus what doesn't work — which matters since there is no output schema.

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 delivers and followed by the usage trigger. The parenthetical list of layers is dense but earns its place by previewing the plan's content; nothing is 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-enum, read-only advisory tool with no output schema, the description supplies everything an agent needs: scope, the three targets, the nature of the returned plan, and the trigger condition. There is no meaningful gap left for a caller to guess at.

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 enum is documented in the schema itself. The description mirrors the three values as 'an iPhone, an Android phone, or at the bank,' adding only light framing (bank = bank-level blocks) rather than new syntax or selection guidance, so the baseline of 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?

The description pairs a specific verb ('block gambling') with the resource and names the surfaces covered (iPhone, Android, bank). It implicitly separates itself from siblings like check_gambling_site and find_self_exclusion by being the 'how to block' plan rather than a lookup, but it never names a sibling 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?

It gives an explicit trigger: 'Use when someone wants to block gambling sites, apps or payments.' That is a clear usage context. It stops short of stating when not to use it or pointing to the sibling tools for site checks, help finding, or self-exclusion.

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, so the safety profile is covered. The description adds behavior annotations do not: the data source is the Silex blocklist shared with its iPhone app and browser extension, and sub-domains match their parent — a matching rule that materially affects result interpretation. It omits any note on coverage limits (false negatives for unlisted sites) or response shape.

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 tight sentences, front-loaded with what the tool does and followed by the matching rule and the usage trigger. No filler, no repetition of the title, and the most decision-relevant facts come first.

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 carries the burden of explaining what comes back, and it never says whether the result is a per-site boolean, a list of matches, or a hit count — an agent must call it blind. It is otherwise complete on scope and matching semantics for a simple single-parameter lookup.

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% with an example and min/max items, so the single parameter is fully documented in structured form. The description only implies it accepts web addresses/URLs in batch via phrasing; it adds no new syntax or normalization guidance (e.g. whether scheme or www. is stripped). 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 (checks) and resource (web addresses against a gambling blocklist) with exact scale (~294,000 domains) and source. It reads clearly as a lookup/verification tool, which an agent can immediately distinguish from the sibling block_gambling, a mutation tool.

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 final sentence gives explicit triggering contexts: someone asks whether a site is a gambling/betting site, or whether a blocker would stop it. It lacks an explicit negative boundary or a named alternative (e.g. "to add a site to the blocklist use block_gambling instead"), so routing is clear but not fully closed.

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is in disclosure of content: verified country lines, free online options that work anywhere, and US/UK debt-advice services. It also flags that verification is manual and coverage may be partial ('where verified'). It stops short of saying what happens with an unrecognised country code, which is the remaining gap.

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, each doing distinct work: provenance, when to use, what comes back. The trigger conditions are front-loaded and no sentence is redundant or restates the 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?

With no output schema, the description carries the burden of describing returns, and it does so reasonably well (lines, online options, debt advice). Minor gaps remain around behaviour for unknown or unsupported countries and whether results can be empty, but the definition is sufficient to invoke correctly.

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 country parameter is fully documented in the schema, so the baseline is 3. The description adds meaning by explaining that non-country-specific online options are returned regardless, which tells the agent that omitting the parameter still yields useful results — a behavioral fact the schema does not 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?

The description names a specific resource (free, confidential gambling helplines and crisis lines) and a specific scope (per-country, hand-verified), which is immediately distinguishable from siblings like block_gambling or gambling_self_check that operate on the user's own gambling. An agent can tell what this returns 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?

It gives concrete triggering conditions: someone wants to talk to a person, is struggling after losses, or seems in distress. That maps a real conversational situation to this tool rather than to the self-check or blocking siblings, so selection is unambiguous.

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 cover safety (readOnly, non-destructive, idempotent, closed-world), so the description focuses on domain behavior: the result is the official scheme plus its terms and sign-up link, self-exclusion is free, and it cannot be undone during a craving. That is meaningful context beyond the annotations. What it does not say is what happens for a country with no national scheme.

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 core intent and return contents, and the second sentence adds a usage trigger. The parenthetical list of national schemes is long but serves retrieval and disambiguation, so it mostly earns its space; the two-sentence structure is easy to scan.

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 lookup with no output schema, the description explains the returned payload (coverage, terms, sign-up link) and the safety-relevant nature of the result, which is what an agent needs. The only gap is unspecified behavior when no national scheme exists for the queried country.

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 and schema coverage is 100% — the schema already documents that country accepts an ISO 3166-1 alpha-2 code or English name. The description adds country-level examples of schemes but no extra parameter guidance such as fallback behavior for unsupported countries. 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 resource (the official national self-exclusion scheme for a country) and enumerates exactly what comes back: coverage, terms, and the official sign-up link, with named examples (GAMSTOP, OASIS, RGIAJ, ANJ, Brazil's federal platform). This clearly separates it from siblings like block_gambling (software blocking) and find_gambling_help (support resources).

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 when-to-use triggers are given: someone wants to stop themselves gambling, close betting accounts, or block licensed operators. There is no explicit when-not or named sibling alternative, but the triggers are concrete enough to route correctly against the other four 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed world, so the safety profile is covered. The description adds behavior beyond that: the two-phase call pattern and the fact that the empty call is a question-fetch rather than an error, plus the non-diagnostic caveat. It stops short of describing the bands or the maximum score, which is a minor gap.

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 identity of the instrument, then the call sequence, then the input encoding, then the caveat. No sentence is redundant and nothing is 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?

There is no output schema, and the description compensates by stating what comes back in each mode (questions and scale, then score and band). For a single-optional-parameter, read-only tool, an agent has everything needed to invoke it correctly in both phases.

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%, so the baseline is 3, but the description exceeds it by supplying the meaning of each value on the 0–3 scale (never, sometimes, most of the time, almost always), which the schema does not label. It also makes clear that the parameter is optional by describing the no-argument call.

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 specific instrument (PGSI, a validated 9-question screener) and states exactly what the tool produces in each mode: the questions when called empty, a score and band when called with nine answers. An agent can distinguish this from siblings like block_gambling or find_gambling_help purely from the 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?

It gives an explicit operational protocol — call without answers, ask the user each question, then call again with the nine responses — which is stronger guidance than most tools provide. It also sets the boundary 'screening tool, not a diagnosis', though it never explicitly contrasts itself with the sibling help or blocking tools.

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