RestoSignals

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

No annotations are provided, so the description carries disclosure. It adds two meaningful behavioral facts: the call is free (0 credits) and querying a state without data yields an empty result. It does not discuss caching/staleness of the inventory or refresh behavior, leaving a small gap for a tool whose whole purpose is describing 'live' data.

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 the resource and what it returns, then the usage directive and cost. No redundant restatement of the title or name.

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 still specifies the shape of the result (per-state venue counts plus hot-lead counts with the threshold), and it covers cost and empty-result behavior. That is sufficient for a zero-parameter inventory tool.

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 of 4 applies. Nothing in the description is needed to clarify inputs, and it correctly implies no filtering argument exists.

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 (states with data), and quantifies what each entry contains (scored venue count plus hot-lead count defined as opening_score >= 80). It explicitly separates itself from the sibling new_openings by positioning itself as the inventory check that precedes it.

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 directive ("Call this FIRST"), names the sibling it should precede (new_openings), and supplies the reason (querying a state with no data returns nothing). When-to-use and the alternative routing are both covered.

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 full burden. It does disclose meaningful traits: the fusion of three signal sources, the per-lead credit cost, and the live-state whitelist. It omits any return-shape, pagination, or failure behavior, which leaves a gap for a tool with no 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?

Front-loaded with the core action and ranking metric, then supporting facts. It is dense but every clause (scoring, signals, live states, credit cost) informs a decision; only the state list is mildly redundant with the 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?

No output schema exists, so the description compensates by describing what a lead contains (signal_types, opening_score) and the coverage/cost model. It is nearly complete for an agent to call it correctly, though return shape and result-count behavior are unstated.

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 adds real interpretability: it explains what opening_score means by tying signal_types ('liquor', 'food_permit', 'business') to fused lead quality, giving context the schema alone implies only partially.

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 ('Find restaurants/bars about to open in a state'), names the ranking metric, and the data-fusion scope. It is clearly distinguishable from siblings like venue_signals and watch_area, which are not about pre-opening leads.

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 routes the agent to `coverage` for the live-state list and states the cost (1 credit per returned lead), which are useful invocation conditions. However, it never says when to prefer this tool over venue_signals or watch_area, so the alternative-selection guidance is only implied.

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 burden. It discloses the source types (liquor/permit/business filings) and the cost ('1 credit'), which is useful behavioral context, but says nothing about volume, granularity, or the shape of what's returned — significant gaps for a tool with 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?

A single front-loaded sentence plus a cost tag. Every clause earns its place: the verb, the resource, the source enumeration, the fused-into-one-venue relation, and the credit cost.

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 lookup with no annotations and no output schema, the description tells the agent what concept the tool returns (underlying signals) but not the return structure, count, or pagination. It is adequate but leaves the agent guessing about output shape.

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 parameter and 100% schema description coverage, the schema already defines venue_id (including 'A venue id from new_openings'). The baseline is 4 for a zero/one-param tool, and the description adds the semantic that the id resolves to a venue that has been fused from signals, which is marginal added meaning.

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 (Return) and resource (raw underlying signals — liquor/permit/business filings) and pinpoints that they were fused into one venue. The parenthetical enumerates exactly what 'signals' means, so an agent can distinguish this provenance/audit tool from the sibling new_openings, which is where the venue_id originates.

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 phrase 'for transparency' gives a clear context (provenance / explain-the-fusion use case) rather than a search or discovery use case. It does not name an alternative or an explicit when-not-to-use, so it stops short of a 5, but the intended scenario 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?

With no annotations, the description carries full behavioral burden. It usefully discloses trigger semantics (fires on new matching openings) and cost ('Free.'), which is real added context, but omits auth requirements, delivery/retry behavior, whether duplicate registrations are deduped, and how to manage or remove the webhook.

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 short sentences, purpose front-loaded, and the one-word 'Free.' earns its place as a cost signal. The criteria enumeration is mildly redundant with the schema but remains compact and readable.

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 two-parameter webhook-registration tool with no annotations and no output schema, the description covers purpose, trigger, criteria shape, and cost, but leaves gaps around authentication, registration response (e.g., an ID needed to unsubscribe), and duplicate/retry handling that an agent would want before calling.

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 both url and criteria are already documented. The description restates the criteria fields ({state, city, signal_type, min_opening_score}) but adds no constraints such as accepted state/city formats, signal_type values, or valid min_opening_score range. Baseline 3 is appropriate.

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 concrete verb (register) and resource (webhook) plus the exact trigger condition: a new matching venue opening in an area. It implicitly distinguishes itself from the query-style sibling new_openings by being the push/registration mechanism, but never names that sibling or contrasts with it 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?

Use case is implied by 'fires when a new matching venue opens,' suggesting ongoing notification rather than one-shot lookup. However there is no explicit when-to-use instruction, no mention of how it differs from new_openings/venue_signals, and no stated prerequisites for registering a webhook.

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