entropiav2

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

No annotations are provided, so the description carries the full disclosure burden. It says nothing about conversation state/memory, session requirements, response format, latency, or rate limits — all important for a chat tool.

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 with no filler, and the core purpose is front-loaded. Nothing is wasted, though it is arguably thin for the tool's role.

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 simple one-parameter tool with no output schema, the definition is minimally adequate. Since there is no output schema and no annotations, the description should ideally say more about what the conversation returns and how state is handled.

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% and the single 'message' parameter is documented in the schema, so the baseline of 3 applies. The description adds no syntax, length, or format guidance beyond 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 names a specific resource (the entropiav2 creative agent) and frames the action as a conversation, so an agent can tell it is an interactive dialogue tool. It adds the agent's specialty domains, but gives no explicit differentiation from siblings like get_agent_info or generate_composition.

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 indication of when to use this tool versus the alternatives. Nothing states whether it should be used for open-ended questions, brainstorming, or as a fallback when the generate_* tools don't apply.

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 full behavioral burden. It implies a non-destructive generation of text, but says nothing about determinism (same seed producing the same poem?), latency, cost, or whether the referenced token must already exist. For a tool with zero annotation coverage this is thin.

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, correctly identifying the artifact and its inputs. It is appropriately sized for a narrow generative tool, though it is terse enough that it omits any of the routing or output information it could cheaply have carried.

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 present, the description should at least indicate that the return value is a poetic text string, which it does only obliquely via 'descripcion poetica'. It never explains what the optional parameters (blend_mode, music_track, video_count) do to the result. Adequate but with visible gaps for a 5-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?

Schema description coverage is 100%, so all five parameters are documented in the schema itself. The description only alludes to 'parametros de composicion' generically and adds no syntax, format, or required/optional guidance beyond what the schema already gives. 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 states a specific verb and output artifact: it generates a poetic description for a videodance NFT from its composition parameters. That cleanly separates it from siblings like generate_composition and generate_contract, which produce different artifacts. It stops short of a 5 only because it does not explicitly contrast itself with those siblings.

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 statement of when to call this tool versus the alternatives, no prerequisites (e.g. that the composition must already exist), and no guidance on repeated invocation. The only usage cue is the implicit one that seed/token_id must be supplied.

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 one important behavioral trait — determinism ('misma semilla = mismo resultado') — which meaningfully changes how an agent should call it. However it says nothing about cost, latency, side effects, or whether the result is persisted/minted, leaving significant gaps.

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, no filler. The core action is front-loaded and the determinism caveat follows immediately. Nothing could be removed without losing 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?

No annotations and no output schema, so the description must explain what the caller receives — a video file, an asset ID, an NFT, JSON metadata? It never does. For a five-parameter generative tool with a rich output surface, this is a substantial omission.

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% and four of five parameters carry enum definitions with their own descriptions, so the schema already documents the inputs. The description adds only the framing that these are 'parametros poeticos' and that seed crystallizes intent, which is marginal value over 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?

States a specific verb and resource ('Genera una composicion unica de videodanza'), which is far more concrete than the bare name 'generate_composition' and clearly separates it from 'generate_contract'. It does not explicitly reference any sibling, but the domain (videodance art generation) is unmistakable.

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 statement of when to use this tool versus the siblings (chat, generate_contract, describe_nft), nor any preconditions or exclusions. The only usage-adjacent hint is that a seed can reproduce a result, which is a property, not guidance.

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 full behavioral burden. It notes the code is "seguro" and relies on OpenZeppelin, but says nothing about side effects (does it write files or just return text?), output format, permissions, or determinism — significant gaps for a generation 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?

Two compact sentences with the verb and resource front-loaded and zero filler. Every clause adds scope or capability 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 2-required-param tool with full schema coverage, the description is serviceable but silent on the return value — no output schema exists, so the agent cannot tell whether it receives source code text, a file path, or a deployment artifact. That missing output contract keeps this from being complete.

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 both parameters and the enum values are already documented in the schema. The description echoes the same contract-type list but adds no syntax, format, or naming constraints beyond what the schema provides, so the 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 ("Genera") plus resource ("codigo Solidity para smart contracts") and adds the concrete implementation basis (OpenZeppelin) and scope (NFTs, tokens, marketplaces, DAOs). An agent can distinguish this code-generation tool from siblings like chat or describe_nft 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?

The list of supported contract types ("NFTs, dynamic NFTs, tokens, marketplaces y DAOs") implies the scenarios the tool applies to, matching the enum. However, there is no explicit when-to-use guidance and no alternatives named among the siblings, so usage 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 full behavioral burden. It reveals the subject matter of the returned data but says nothing about whether it is a safe read, whether authentication or an agent identifier is required, or how failures are handled. For a zero-parameter getter this is low-risk, but the disclosure is thin.

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 that front-loads the verb and resource and then lists the concrete payload. No filler, no 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?

With no output schema, the description usefully enumerates what comes back (capabilities, stack, projects), which is the main thing an agent needs for a zero-param lookup. Minor gaps remain around authentication/identity context, but the tool's scope is simple enough that the description is nearly sufficient.

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 no parameters, so per the baseline a 4 applies. There is nothing for the description to clarify here.

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 (get information about the entropiav2 agent) and enumerates the content returned: capabilities, technical stack, associated projects. It is clear on its own, though it makes no effort to differentiate from siblings (which are unrelated operations, so the omission matters little).

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 indication of when to call this tool versus the siblings (chat, describe_nft, generate_composition, etc.), nor any prerequisite or exclusion. Usage is only implied by the tool name and the fact that it is a lookup.

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 full burden, and it does disclose a meaningful behavioral trait: a double opt-in flow where the subscriber receives a confirmation email before being subscribed. It does not cover idempotency, behavior on already-subscribed emails, or rate limits, so it falls short of fully discharging the no-annotation burden.

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 action and resource, then the opt-in behavior. The newsletter topic list is slightly marketing-flavored padding but it still earns its place by clarifying scope.

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 simple one-parameter subscription tool with no output schema, the description covers what it does and the confirm-by-email behavior an agent should expect. Missing only edge-case behavior (duplicate subscriptions, failure modes), which is minor for this tool's complexity.

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 a single parameter at 100% schema description coverage (including a hint that agents can use their own inbox like tu-agente@agentmail.to), the schema already documents the parameter fully. The description adds no additional semantics about the email field, 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?

States a specific verb (subscribe) and resource (an email to Petra's newsletter), and elaborates the newsletter's content (creative processes, body, data, generative videodance, on-chain agents). None of the siblings (chat, describe_nft, generate_composition, generate_contract, get_agent_info) overlap, so an agent can select it unambiguously.

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 purpose but there is no explicit when-to-use or when-not-to-use guidance, nor any mention of prerequisites or alternatives. Adequate but not instructive for an agent weighing whether this is the right action.

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