GPT-5.6-luna Agent

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds that it does not run the model and does not require a bearer token, providing additional behavioral transparency beyond annotations.

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 description is two sentences, efficiently conveying the returned items and key behavioral traits. No extraneous content.

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 no parameters and sufficient annotations, the description covers the essential return values and behavioral notes. No gaps identified.

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 has zero parameters, so the description does not need to elaborate on parameter semantics. Baseline score of 4 applies per instructions.

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 explicitly states the tool returns agent identity, per-task price, MCP endpoint, and access URL. It clarifies this is a metadata call that does not run the model. The verb 'returns' is clear, and it distinguishes from sibling tools that deal with runs.

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 description notes that the call does not run the model and does not require a bearer token, implying it should be used when metadata is needed without model execution. While it does not explicitly mention when not to use, the context of sibling tools for runs provides clear differentiation.

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 destructiveHint=true and idempotentHint=true, covering the safety profile. The description adds a meaningful constraint—only queued or running runs can be cancelled—but does not disclose what happens after cancellation (e.g., irreversible, async, effect on results). This adds some value but not rich behavioral context.

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 description is a single, front-loaded sentence with zero wasted words. It conveys the action, resource, and constraint efficiently.

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 one-parameter, destructive, idempotent tool, the schema and annotations cover most of what an agent needs. The main gap is that no output schema exists and the description does not mention what the tool returns after a successful cancel or how errors (e.g., run already finished) are surfaced, which would be useful but not critical.

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 input schema covers the sole parameter run_id with 100% description accuracy ('AgentFarm run identifier'). The tool description adds no additional parameter meaning beyond what the schema already provides, 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?

The description states a specific verb ('Cancels'), a resource ('AgentFarm run'), and a scope qualifier ('authenticated queued or running'). This clearly distinguishes it from sibling tools like create_run, get_run_status, and get_run_result, so an agent knows exactly what the tool does.

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 description implies this tool is only for queued or running runs, but it does not explicitly say when to use it versus alternatives or mention any exclusions. Context about siblings is present in the signal data but not referenced in the description itself.

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?

Beyond the annotations (readOnlyHint=false, idempotentHint=false), the description discloses that the task is asynchronous ('Queues'), requires authentication ('authenticated'), and has cost implications ('can consume paid model capacity'). It also reveals the lifecycle behavior by routing to polling and result tools. No contradiction with annotations — the mutation/async nature aligns with readOnlyHint=false. It doesn't cover failure modes or rate limits, but the annotation bar is satisfied.

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?

Three sentences, each earning its place: the core action, the cost warning, and the follow-up workflow. The most important information (what the tool does) is front-loaded, and there is zero filler or repetition of schema content.

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?

The tool is simple (3 fully documented params) and the workflow chain is stated, but there is no output schema and the description never says what the create call returns (e.g., a run ID to pass to agentfarm_get_run_status). An agent must infer the response shape to chain the lifecycle correctly. Cost and async caveats are covered, but the missing return-value semantics is a real gap.

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% — all three parameters (task, task_input, idempotency_key) already have meaningful descriptions in the schema, including the idempotency behavior of idempotency_key ('the same key and input return the original run'). The tool description itself adds no parameter-level detail, placing it at the baseline 3 for high-coverage schemas.

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 ('Queues') with a clear resource ('authenticated asynchronous task'), and the title anchors it as 'Create a GPT-5.6-luna Agent run.' It distinguishes itself from siblings by naming the downstream workflow (agentfarm_get_run_status, agentfarm_get_run_result), making it unambiguous that this is the creation step rather than a status or result read.

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 description gives explicit workflow guidance: 'Poll with agentfarm_get_run_status, then read agentfarm_get_run_result,' telling an agent exactly which sibling tools follow this one. The cost warning ('This can consume paid model capacity') implies agents should invoke cautiously. It lacks explicit when-not-to-use conditions or mention of the cancel/agent-info siblings, so it stops short of a 5.

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 read-only, idempotent, non-destructive behavior. The description adds the 'authenticated' prerequisite and specifies that it returns final summary and artifact URLs, which gives useful context about what the tool does beyond the annotations.

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 description is a single concise sentence with no filler or redundant information. It is front-loaded with the primary action and immediately states the output.

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 get-style tool with one parameter and strong annotations, the description adequately covers the return content. It does not explain error handling or prerequisites beyond 'authenticated', but these are not critical given the tool's simplicity and the absent output schema.

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 schema already describes run_id as 'AgentFarm run identifier' with 100% coverage. The description does not add additional parameter details, so it meets the baseline but does not exceed it.

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 ('Returns') and names the resource ('final summary and artifact download URLs') for an authenticated run. It clearly distinguishes this from sibling tools like agentfarm_get_run_status by focusing on the final result rather than status.

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 an authenticated run' provides clear context that this tool is used after a run has been executed and requires authentication. It does not explicitly name alternatives or exclusions, but the distinction from sibling tools is implicit through the 'final' wording.

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 readOnlyHint, idempotentHint, and destructiveHint, so the core safety profile is covered. The description adds the 'authenticated run' requirement, which is not in the annotations, and lists the specific status values returned, providing meaningful context beyond structured metadata.

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 description is a single concise sentence that front-loads the key information (what it returns) and specifies the exact statuses. Every word adds value, with no redundancy or irrelevant detail.

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 read-only status-checking tool with one parameter, good annotations, and no output schema, the description fully covers what the agent needs: it clarifies the run status values and the authentication requirement. Nothing critical is missing.

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 schema covers the single parameter run_id with a clear description ('AgentFarm run identifier'), achieving 100% schema description coverage. The tool description does not add additional parameter semantics, so it does not exceed the baseline set by 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 clearly states the verb ('Returns') and the resource ('status for an authenticated run'), enumerating the possible values (queued, running, succeeded, failed). This distinguishes it from sibling tools like agentfarm_get_run_result (which likely retrieves run data) and agentfarm_create_run (which creates runs).

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 description implies usage for checking run status, but it does not explicitly say when to use this tool versus alternatives like get_run_result or get_run_info. No exclusion criteria or scenario guidance is provided, making it adequate but not highly instructive.

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