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

No annotations are provided, so the description carries the full burden. It usefully discloses the key behavioral trait that the command is executed verbatim without model reinterpretation, but it says nothing about side effects (can a command mutate the workspace?), permissions, error behavior, or whether output is returned raw or summarized.

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 that states the action first and the key caveat second; there is no filler or boilerplate. 'Interpretar ou reformular' is mildly redundant but the pairing does clarify intent.

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 3-parameter tool with no annotations and no output schema, the description covers the essential semantic (verbatim CLI execution) but leaves side-effect risk, output format, and failure modes unaddressed. It is adequate, not 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 description coverage is 100%, so the schema already documents 'command' (with slash prefix and example), 'model' (with default), and 'directory'. The description adds no further parameter meaning beyond repeating the '/usage' example, 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?

The description names a specific verb+resource ('executa literalmente um comando direto do Antigravity CLI') and gives a concrete example ('/usage'), which is clear and actionable. It also implicitly disambiguates from model-driven siblings by stating the command is not interpreted or reformulated, though it never names agy_exec or the other siblings 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?

Usage is implied rather than stated: the tool is for raw slash-style CLI commands, illustrated by '/usage'. There is no explicit when-to-use vs. when-not, no mention of how it differs from agy_exec or agy_plan, and no prerequisites or conditions that would route an agent here rather than elsewhere.

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 discloses almost nothing: it never mentions that the default mode 'accept-edits' implies filesystem mutation, nor any sandbox, permission, cost, or rate-limit characteristics. An agent could reasonably assume this is a read-only query tool, which is misleading given the schema defaults.

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 tight sentence with no padding, and the delivery mechanism is front-loaded. It earns its place structurally even though its content is thin.

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-parameter execution tool with no output schema, no annotations, and a mutation-implying default mode, the description leaves the agent without the safety and routing context it needs. The critical risk that acg_exec can modify a project directory is nowhere acknowledged.

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 every parameter is already documented in structured data and the baseline of 3 applies. The description adds nothing about the prompt, model selection, mode, or directory semantics beyond what the schema states.

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 verb (executa) and a resource (comandos/consultas) delivered via the Antigravity CLI, which rules out unrelated tools. But 'genéricos ou arbitrárias' is near-tautological and gives no basis for distinguishing this tool from sibling agy_command, which by name also sounds like command execution.

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?

No statement of when to use this tool versus agy_plan, agy_command, agy_review or agy_validate_tests, and no prerequisites. The only routing hint, if any, lives in the mode enum rather than in the description.

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 of behavioral disclosure. It only says it generates or validates plans, but does not state whether this is a read-only operation, whether it writes files, what permissions are required, how long it takes, or what the output looks like. For a tool that likely invokes an external CLI and may modify a workspace, this is a critical 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?

The single sentence is front-loaded and contains no wasted words. It efficiently states the core function and the tool used. However, it is too sparse to be concise in a helpful way; it omits necessary context rather than being tight.

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?

Given the complexity (external CLI, workspace analysis, model selection) and the lack of annotations and output schema, the description is incomplete. It does not explain what a 'plan' is, how it is returned, whether it executes code, or how it interacts with the workspace. An agent cannot safely invoke this tool without additional assumptions.

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 the parameters are already well-documented in the schema. The description adds no parameter-level details (e.g., expected format of prompt, meaning of directory, model selection guidance). Baseline 3 is appropriate when the schema does the heavy lifting and the description adds nothing.

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 verb+resource ('Gera ou valida planos de arquitetura e implementação técnica') and mentions the mechanism (agy CLI in planning mode). However, it does not distinguish from siblings like agy_exec or agy_review, which likely also produce plans or run agy commands. An agent cannot tell from the description alone why it should pick agy_plan over agy_exec for a planning task.

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 guidance. The phrase 'em modo de planejamento' implies a planning mode but does not state when planning is preferred over execution (agy_exec) or review (agy_review). No exclusions or alternative tools are mentioned.

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, and it discloses almost none. It does not say whether the operation is read-only or whether it can modify the target directory, that the prompt is sent to an external Google Gemini model, anything about latency/cost, or what the result looks like. Only the enumerable evaluation dimensions (manutenibilidade, segurança, performance, bugs) add substance.

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?

One dense sentence with the action front-loaded and no filler; the four review dimensions are packed in efficiently. It is well-sized for a single-purpose tool, though packing purpose, mechanism and scope into one sentence makes it slightly harder 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 3-parameter tool with no output schema and no annotations, the definition is adequate on purpose but thin on everything an agent needs to invoke it confidently: expected output form, whether the directory is read or written, and where the review is executed. Nothing required is present in structured fields to compensate.

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 model, prompt and directory each documented in the schema itself, so the baseline is 3. The description adds nothing about prompt formatting, directory semantics, or model selection trade-offs beyond what the schema already states.

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 (revisão técnica aprofundada) and concrete resources (código, diffs, implementações), plus the delivery mechanism (Antigravity / agy CLI) and the evaluation axes. It is clearly distinguishable from agy_plan, agy_exec, agy_command and agy_validate_tests by the object and intent, though it never names a sibling to sharpen the boundary.

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 agent can infer 'use this when you want a deep code review', but there is no explicit when-to-use vs when-not, no routing to agy_plan for planning or agy_validate_tests for test validation, and no prerequisites stated.

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 falls short. It discloses the execution vehicle (agy CLI / Antigravity), which is useful context, but says nothing about whether files are modified, whether a report is returned, auth/API-key needs, or cost/latency of an LLM call.

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 verb and resource first, followed by the concrete findings it produces. No filler or restatement of the name, though the field list makes it dense.

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 should hint at the return shape and behavioral envelope, and it does neither. It adequately covers the analysis scope for a 3-parameter tool, but an agent cannot tell whether this just returns text, writes artifacts, or alters the working directory.

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 all three parameters (model, prompt, directory) are documented in the schema itself, including the enum and default. The description adds no extra meaning about how prompt or directory should be formatted, 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 (analisa) and resource (código de teste e de produção) and names the exact analysis dimensions it will report on: asserções frágeis, casos de borda não cobertos, vazamento de estado, robustez da suíte. It is clear and concrete, but it never distinguishes itself from the sibling agy_review, which an agent could easily mistake for this task.

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, when-not-to-use, or alternative guidance. With siblings like agy_review and agy_plan, the agent must infer from the name alone that test/quality audit is this tool's lane, and nothing excludes using agy_review for the same input.

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