gobeyondclouds

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds value the annotations don't: it names the fields the records contain, which matters because there is no output schema. It does not mention result size or pagination, the one behavioural 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?

Two dense sentences with zero filler: the payload description comes first, the filtering options second. Nothing repeats the tool name or the annotations, and every clause adds new information.

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-required-parameter, flat-schema list tool with no output schema, the description supplies both the return shape and the filter vocabulary, which is what an agent needs to call it correctly. Only pagination/result-size behaviour is left implicit.

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 0% and neither parameter declares an enum, so the description carries the full burden — and it delivers by spelling out the accepted values (cluster: a2a | space | energy-data; status: live | pilot | lab | programme | data-capability | waitlist). It does not state case sensitivity or matching behaviour, but the critical closed value sets are there.

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?

Opens with a specific verb+resource ('The venture registry: every GBC venture') and enumerates exactly what each record carries (cluster, status, buyer, pricing, URL, agent access). The only friction is the undefined acronym 'GBC', which an agent outside the org cannot resolve, but the scope is otherwise unmistakable and none of the siblings (network_stats, skill_rank, solar_prefeasibility) overlap with 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?

Makes the default behaviour explicit — it returns *every* venture unless you narrow with the optional cluster or status filter — which is the key when-to-use decision for this tool. There are no exclusions or named alternatives, but the siblings are unrelated domains, so there is nothing to route against.

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 adds genuinely new behavioral context: the numbers are 'live', each carries a refreshed_at timestamp, and each carries a source URL — telling the agent how to judge freshness and provenance, which no annotation conveys.

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 sentence, front-loaded with the resource identity and then the enumerated payload plus freshness/provenance metadata. Every clause carries information an agent would otherwise have to discover by calling the tool; there is no filler.

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 return values, and it does so at a useful level: the counter categories, the refreshed_at field, and the source URL. It does not state the response shape (e.g., whether counters are an array or object), which is a minor remaining gap for a no-parameter 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 there is no parameter semantics to document and the baseline of 4 applies. The description correctly does not invent inputs, confirming this is a 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 a specific resource (GoBeyondClouds network live counters) and enumerates exactly which counters are returned: subscribers, articles, energy forecasts, skills indexed, skill calls scored. That enumeration clearly separates it from siblings like list_ventures or skill_rank. It stops short of an explicit verb ('return'/'get'), but the resource is 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?

There is no explicit when-to-use statement, no prerequisites, and no named alternatives. Usage is only implied by the content: an agent infers it should call this when it needs aggregate network metrics. For a zero-parameter read-only tool that inference is easy, but the description does no active work here.

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 a non-read-only, non-destructive, non-idempotent call, and the description adds genuinely new context: that a visit is persisted and that operator/purpose may be publicly listed on gobeyondclouds.io/agents while contact is never shown. That privacy disclosure is exactly the kind of side-effect information annotations cannot convey. It stops short of stating that repeated calls register additional visits.

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 the action stated before the parenthetical detail. The parenthetical is dense but every clause carries real information; nothing is wasted.

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 4-param registration tool with no output schema, the description covers the side effect, the privacy implication, and the return value. The only real gap is behavior on repeat calls or on an already-registered agent_name.

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 carry the load, and it does for three of four params: operator and purpose may be publicly listed, contact is never shown. Only agent_name goes unexplained, though its meaning is self-evident from the name.

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 a specific verb+resource pair ("registers a visit") and states the return value ("returns the service list"), which distinguishes it clearly from read-only siblings like list_ventures and network_stats. It does not explicitly name those siblings, keeping it below a 5.

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 implied by "Introduce your agent to the network" and by the promise of a service list, which hints this is a first-contact/discovery call. There is no explicit when-to-use vs when-not guidance or reference to alternatives.

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, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the tool returns a pointer (URL) plus index size rather than the ranking itself, and the underlying index is public — which prevents an agent from assuming this call delivers ranking results.

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 tight sentences, front-loaded with the verb and resource, followed by the return payload and the public-index note. Nothing is padded and nothing repeats the title verbatim.

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 naming the return values (URL and index size). Minor gaps remain — nothing on what happens for an unmatched skill name or whether matching is fuzzy — but for a one-parameter lookup the core is covered.

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 100% schema description coverage on a single required parameter, the schema already explains that 'query' is a skill name or category with an example. The description's phrasing ('skill or category') restates rather than extends that meaning, 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?

The description names a specific verb ('look up') and resource ('an AI agent skill or category') along with the data source (SkillAssay, outcome-based ranking). It also states what the call yields — the SkillAssay URL plus current index size — so an agent knows exactly what this tool does 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?

Usage is implied by the statement that the index is public at skillassay.com, suggesting a two-step 'get URL, then query the site' workflow. There is no explicit when-to-use or when-not guidance, but the sibling tools (list_ventures, network_stats, solar_prefeasibility, say_hello) are unrelated, so there is no genuine alternative to route to.

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 open-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: an external partner key is required, and a missing key yields an instructional response rather than an error – that is exactly the kind of context an agent cannot infer from annotations. It stops short of describing what the feasibility output contains.

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, no filler, with the quantity delivered (pre-feasibility report) first and the credential constraint second. Nothing in the text is redundant with the title or annotations.

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 and no parameter descriptions, the definition leaves the core invocation question unresolved: is location supplied as lat/lon, as a free-text address, or either? It also never says what the returned feasibility assessment reports (yield, irradiance, payback), which the agent needs to decide whether to call this at all. Adequate on auth, inadequate on inputs and returns.

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 0% across four parameters, so the description carries the full burden. It explains only api_key (requirement plus fallback); lat, lon and address are left entirely undefined, so the agent must guess whether address is an alternative to coordinates or an additional filter, and with zero required parameters it cannot tell which combination is valid.

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 and output type – a solar pre-feasibility assessment for a factory roof, sourced from PVGIS plus satellite data – so an agent knows what it produces. It does not differentiate from siblings, but the sibling set (list_ventures, network_stats, say_hello, skill_rank) has no topical overlap, so the ambiguity risk is low.

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 prerequisite ('Requires a SolarAnalytics partner API key') and the fallback ('Without a key, returns how to get one') give real call-context, including that it is safe to invoke without credentials. However there is no explicit when-to-use versus alternative framing and no statement of which location input form to pick.

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