Fable 5 Agent

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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds genuinely non-structured context: no bearer token required for this call, and that execution (not this call) consumes prepaid run units — useful cost/auth information an agent can't derive from 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?

Two tight sentences with no filler. The return-value content is front-loaded and the auth/cost caveat follows immediately; every clause carries 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 zero-parameter, annotation-covered metadata call with no output schema, the description supplies the return fields (identity, price, endpoint, URL) plus the auth and cost behavior. Nothing an agent needs to invoke it correctly 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 tool takes zero parameters, so the baseline of 4 applies. The description appropriately says nothing about arguments and instead spends its text on return fields and call semantics.

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 ('Returns this agent's identity, listed per-task price, MCP endpoint, and access URL') and enumerates exactly what comes back. This is clearly distinguishable from the run-lifecycle siblings (create_run, get_run_status, get_run_result, cancel_run), which all deal with executions rather than agent metadata.

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?

It implicitly positions itself as a pre-execution metadata call by clarifying it 'does not run the model' and that execution is what consumes run units. That gives an agent a clear condition for reaching for it, though it never explicitly names a sibling alternative or a when-not-to-use case.

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?

The description adds meaningful behavioral context beyond the annotations: the task is asynchronous, requires authentication, and can consume paid model capacity. This is especially valuable for a mutation-like operation where cost and async behavior are critical for agent decision-making. No contradiction with 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 concise sentences with no filler. It front-loads the core action, then adds a critical cost warning and a clear follow-up path. Every sentence earns its place.

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 tool with no output schema, the description adequately explains the full lifecycle: creation, polling, and result retrieval. It also surfaces the cost and auth requirements in one short description. Combined with the complete parameter schema, the agent has everything needed to call this tool correctly.

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 has 100% parameter description coverage, so the baseline is 3. The description itself does not add parameter-level detail beyond what the schema already provides, but the schema already sufficiently documents 'task', 'task_input', and 'idempotency_key'.

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') and resource ('an authenticated asynchronous task'), clearly identifying the tool as the creation/queueing step. It also implicitly distinguishes from sibling tools by referencing the follow-up status and result tools, so an agent understands this is not the poll or read operation.

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 clearly states the intended workflow: queue a task, then poll with agentfarm_get_run_status, then read agentfarm_get_run_result. This gives clear context on when to use this tool relative to its siblings. It does not explicitly state when not to use it or mention alternative creation methods, but the workflow guidance is strong.

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.