GPT-6 Astra

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

Annotations already cover readOnly, idempotent, non-destructive and closed-world, so the bar is lower. The description still adds real behavioral context beyond them: bearer-token-free access and the fact that execution consumes prepaid run units, which is a cost/auth trait an agent needs before calling.

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 with the return payload front-loaded and the behavioral caveat (no token, consumes units) immediately after. Minor redundancy in restating that the metadata call is read-only, but nothing wasteful.

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 carries the return-value burden, and it discharges it by enumerating identity, price, endpoint, and access URL. It leaves error/edge behavior unstated, but for a zero-parameter read-only metadata call it is essentially 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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to clarify, and it correctly avoids fabricating parameter detail.

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 (Returns) and a fully enumerated resource set: agent identity, per-task price, MCP endpoint, and access URL. That is clear enough to identify the tool, but it never contrasts itself with the sibling run-management tools, so an agent must infer the distinction from the name alone.

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 by clarifying that this is a metadata call that 'does not run the model', but it gives no explicit when-to-use or when-not-to-use guidance and names no alternative. The context is useful but routing is left to inference.

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?

Annotations already declare readOnly=false, destructive=false, idempotent=false, and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: the call is authenticated, execution is asynchronous, and it 'can consume paid model capacity' — a cost warning an agent would otherwise miss. It stops short of explaining failure/retry semantics for the returned run.

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, zero filler, with the core operation stated first and the cost/polling context after. Nothing can be cut 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?

For an async, paid-capacity, non-idempotent creation tool with no output schema, the description covers the essential workflow and cost caveat. The one material omission is that it doesn't say the call returns a run identifier — the very handle the agent needs for the polling step it recommends.

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 (task, task_input, idempotency_key) are documented in the schema, including the retry-key behavior. The description adds no parameter-level detail beyond that, so the baseline 3 is appropriate.

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 concrete verb ('Queues') and resource (an authenticated asynchronous task), and the polling/result siblings are named so the agent can place it in the run lifecycle. However, the description never says it creates a *run* of a specific model (the title's 'GPT-6 Astra run' is not reflected), so the resource identity is slightly looser than ideal.

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?

Gives an explicit follow-up workflow ('Poll with agentfarm_get_run_status, then read agentfarm_get_run_result'), which routes the agent correctly among siblings. It does not state when *not* to use it or any precondition beyond 'authenticated', but for the only creation tool in the set the guidance is clear.

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.