antigravity
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Each tool has a distinct role in the task lifecycle, but antigravity_status and antigravity_result both surface task status information, which could cause minor confusion. Overall, the purposes are separable: one checks CLI availability and process-held tasks, the other reads a specific task's status and response.
Naming Consistency5/5All tools follow the consistent antigravity_<verb> pattern with clear, predictable names: status, start, result, cancel. No mixed conventions or vague verbs.
Tool Count5/5Four tools cover the essential operations for delegating and managing tasks through a CLI bridge. The scope is tight and each tool earns its place.
Completeness5/5The tool surface covers the full task lifecycle: initiate (start), monitor/retrieve output (result), terminate (cancel), and environment/process health (status). No obvious dead ends or missing operations for the stated purpose.
Average 3.9/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It goes beyond the name by noting that child processes are stopped and, importantly, that already-completed file changes are not reverted. This is valuable non-obvious context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, each earning its place. The primary action is front-loaded, followed by a single important caveat. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple one-parameter cancellation tool, but lacks context on how to retrieve task_id, behavior if the task is already stopped, and what the return value indicates. With no output schema, some additional detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the sole task_id parameter, and the description does not mention the parameter at all. It fails to compensate by explaining how to obtain a task_id or what it references, leaving the agent to infer from the parameter name alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action and resource: 'Stop a running Antigravity task and its child processes.' This clearly distinguishes it from sibling tools like antigravity_start, antigravity_status, and antigravity_result.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for stopping a running task, but it does not explicitly mention alternatives, when not to use it, or how it relates to sibling tools. No exclusions or routing guidance are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint already set, the description adds meaningful behavioral context: the response includes a reusable conversation_id, and task records are cleared when the MCP server restarts. This gives the agent important lifecycle information beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core action, then adds brief polling guidance, response metadata, and lifecycle caveat. Every sentence adds distinct value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with one parameter and no output schema, the description covers the purpose, polling behavior, reusable identifier, and ephemeral storage. It is nearly complete; the only notable omission is any explanation of what happens if the task is not yet finished, though the polling advice mitigates this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explicitly explain the task_id parameter, and schema description coverage is 0%. However, the single parameter is strongly implied by 'Read a task status', so an agent can reasonably infer that task_id identifies the task being read, but the mapping could be more explicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific operation ('Read a task status and final Antigravity JSON response') with a concrete resource and output. It is clear and action-oriented, though it does not explicitly differentiate itself from the sibling antigravity_status, which likely also reads task status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides practical usage context by advising polling running tasks about every 10 seconds and noting the conversation_id can be reused. However, it does not explicitly state when to prefer this tool over antigravity_status or antigravity_cancel, nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the asynchronous return behavior and states that the bridge never bypasses Antigravity permissions, but it does not elaborate on potential side effects of delegated tasks, failure modes, or the meaning of the accept-edits mode beyond a brief caveat.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and focused, using four short sentences to convey purpose, prerequisites, mode guidance, and return behavior. Every sentence contributes value and there is no redundant or filler wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is reasonably complete for an asynchronous start operation: it states prerequisites, return behavior, and the need to poll the result tool. However, it lacks detail about the optional parameters, how long the task may run, what could go wrong, and how the status/cancel siblings fit into the workflow, leaving some context gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds some meaning for cwd and mode, but the schema has six parameters and the description does not explain prompt, model, conversation_id, or timeout_seconds. Given the 0% schema description coverage, the description insufficiently compensates by only partially covering the required and key behavioral parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action as delegating a task to the local Antigravity CLI, distinguishes this from its sibling tools by noting that it returns a task_id immediately and directs polling antigravity_result. It also clarifies mode choices, making the purpose specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage guidance: an authenticated CLI and absolute working directory are required, plan mode is for analysis, and accept-edits mode should only be used when file edits are intended. It tells the agent to poll antigravity_result after receiving the task_id, though it does not explicitly contrast with antigravity_status or antigravity_cancel.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that authentication isn't verified until task execution, a useful behavioral trait beyond the readOnlyHint annotation. It also surfaces the environmental dependency on the local CLI being discoverable. This gives an agent accurate expectations of success/failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose, no filler. The caveat about authentication is placed as a valuable second sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter status tool with a readOnlyHint and no output schema, the description covers the main outcome (CLI presence and task list) and an important side effect (no auth verification). It could specify the return shape, but its simplicity makes that a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so the baseline is 4. The description adds no parameter-specific semantics, but none are needed with an empty schema; the behavioral description is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb phrase 'Check whether the local Antigravity CLI can be found and list tasks held by this MCP process,' clearly distinguishing it from the task-execution siblings start/result/cancel. The resource and scope are precise. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternative guidance is provided. The role of a status/health check is implied by the name and description, but the description does not say when to prefer this over antigravity_start/result/cancel. It does clarify that authentication happens only at task execution, which indirectly signals a safe pre-flight check, but no direct routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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