AgentsPodium Hosting

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

There are no annotations, so the description carries the full behavioral burden. It discloses that the instance id is returned, that a2aUrl/a2aToken are only returned when enableA2A is true, and that the instance is not immediately usable until health polls succeed and an LLM key is set. This meaningfully reveals post-creation behavior that an agent could not infer from the schema alone.

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 short sentences each earn their place: the first states the action and resource, the second covers return values, and the third gives the required follow-up workflow. Information is front-loaded and there is no filler or repetition of schema details.

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?

With no output schema, the description compensates by specifying exactly what the caller receives. It also accounts for the operational complexity of provisioning by naming the required next steps (instance_health polling and set_llm_key), making the tool realistically actionable for an agent despite having nine parameters.

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 all nine parameters. The description adds little beyond what the schema states, aside from echoing the conditional a2aUrl/a2aToken behavior for enableA2A, which the schema already covers. 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?

The description opens with 'Create (deploy) a new AgentsPodium instance,' a specific verb plus resource that clearly states the action. It is naturally distinct from the sibling lifecycle tools (delete_instance, pause_instance, instance_health, set_llm_key), so an agent can tell them apart without opening schemas.

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 provides clear lifecycle context by instructing the agent to poll instance_health after creation and then call set_llm_key, effectively positioning create_instance as the initial provisioning step. It does not explicitly state when not to use this tool or compare it against alternatives, but the workflow guidance is sufficiently 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?

With no annotations provided, the description carries the full behavioral burden. It explicitly discloses that deletion is permanent and irreversible, which is the most critical behavioral trait for a destructive delete operation. It does not mention permissions or side effects on related resources, but the core destructive nature is clearly conveyed.

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 with no filler. The core action and the irreversible warning are both front-loaded and necessary, making this an appropriately concise and structured description.

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 one-parameter destructive tool, the description is largely complete: it states the action, the irreversibility, and the id comes from well-defined schema context. It could mention return values or post-deletion effects, but those are not essential for an agent to safely invoke the tool.

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 input schema already fully documents the 'id' parameter. The description adds no additional parameter-level meaning, but it doesn't need to since the schema is sufficient.

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 and resource: permanently delete an instance. It clearly distinguishes itself from siblings like pause_instance, resume_instance, and rebuild_instance by signaling a terminal, irreversible action.

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 no guidance on when to use this tool versus alternatives such as pause_instance or instance_term. It does not mention prerequisites, such as whether the instance must be stopped first, or caution about using it only when an instance is no longer needed.

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?

With no annotations provided, the description must carry the behavioral disclosure burden. It signals a non-mutating read-only operation via 'Check whether' and discloses the behavioral dimensions it covers: reachability, serving state, and quota. It does not detail error behavior or response format, but it clearly states what the tool observes without contradicting any 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, front-loaded sentence that immediately states the core action ('Check whether an instance is reachable and serving') and then appends the additional checks (status and quota state). There is no filler, repetition, or extraneous detail; every word contributes to the tool's purpose.

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 low-complexity tool with one fully documented parameter, the description sufficiently covers what the tool does and what it reports on: reachability, serving status, and quota state. There is no output schema to lean on, and the description could mention return format or error behavior, but for a simple health-check tool the provided information is largely 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 input schema has 100% description coverage and already documents the single 'id' parameter as the instance/agent id returned by create_instance or list_instances. The tool description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate because the schema does all the necessary explanatory work.

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 ('Check') with a clear resource ('an instance') and enumerates the exact aspects being checked: reachability, serving status, and quota state. This distinguishes it from sibling tools like create_instance, delete_instance, and pause_instance, which are clearly lifecycle mutations rather than health checks.

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 clear context for when to use the tool: whenever you need to assess whether an instance is reachable, serving, and within quota. It does not explicitly name alternative tools or state when not to use it, but the purpose is specific enough that an agent can infer the appropriate usage context.

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?

There are no annotations, so the description carries the burden of clarifying behavior. The verb 'Get' implies a read-only operation, and the description states the kind of information returned. It does not, however, explicitly state side-effect-free behavior, error cases, or permission requirements.

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 no filler. It communicates the purpose and the key output details 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 simple one-parameter lookup with no output schema, the description provides enough context to call the tool correctly: it names the return concept and the parameter is documented in the schema. It could be more complete by describing the exact response shape, but that is not critical for a tool this simple.

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 already fully documents the single 'id' parameter, including where it comes from. The description adds no parameter-level meaning beyond the schema, 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 uses a specific verb ('Get'), a clear resource ('billing term for an instance'), and enumerates the possible values ('trial/paid/grace') plus what is included ('when it renews or expires'). This clearly distinguishes it from sibling tools like instance_health or payment_options.

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 when to use the tool: whenever the billing status or renewal/expiration details of an instance are needed. However, it offers no explicit guidance about when not to use it or how it compares to related tools such as payment_options.

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?

With no annotations provided, the description carries the full burden, and it does well by explicitly stating 'Never returns secrets.' This is a meaningful safety disclosure beyond the basic listing behavior, though it doesn't mention pagination or response ordering, which are minor for a zero-parameter list tool.

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 sentence that front-loads the action and resource, then compactly lists the returned fields and ends with an important safety note. Every word earns its place; there is no fluff.

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 zero-parameter list tool with no output schema and no annotations, the description is complete: it names the scope, the full set of returned fields, and the secrecy guarantee. Nothing essential is missing for an agent to call it 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?

There are zero parameters, so the baseline is 4. The description has no parameter definitions to add, but it compensates by detailing the output fields, which is the relevant semantics for this tool.

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 ('List') and resource ('the caller's AgentsPodium instances'), then enumerates the exact fields returned. It clearly distinguishes this read-only listing tool from mutation and management siblings like create_instance, delete_instance, and instance_health.

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 purpose is so self-evident that an agent can infer it as the go-to tool for viewing instances. It doesn't explicitly name alternatives or say when not to use it, but the scoping to 'caller's instances' and the list of fields gives clear context among the sibling tools.

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 burden. The verb 'List' strongly implies a read-only operation, and the description states what is returned (engines, plans, prices, capabilities). However, it does not explicitly disclose auth requirements, side effects, or whether the data is live/cached, which is a minor gap for a zero-parameter catalog query.

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: the verb, resource, and data payload are presented in order, with no filler.

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 read-only list tool with no output schema, the description covers what the user gets (engines, plans, prices, capabilities). It omits only minor details like pagination or exact result shape, which are less critical for a catalog list.

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 no properties, and description coverage is effectively 100% (vacuously). With zero parameters, the description need not explain parameter behaviors; the baseline of 4 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 ('List') and resource ('available AgentsPodium engines (platforms) and hosting plans (tiers)') and clarifies the included data ('prices and capabilities'). It distinguishes itself from sibling list_instances by targeting the catalog of platforms/plans rather than user instances.

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 the tool is for discovering available engines and plans, but it does not explicitly state when to prefer it over alternatives or when not to use it. No sibling is referenced, leaving the routing 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?

With no annotations, the description carries the full disclosure burden and does so well: it reveals that pausing stops the billing lease (a cost consequence) and that data is archived rather than deleted (a retention consequence). Both go beyond what the tool name alone implies. It stops short of covering idempotency or prerequisite states (e.g., behavior if already paused), but the key operational effects are disclosed.

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 sentences with zero filler: the action and resource lead, followed by the two most decision-relevant consequences (billing, data retention). Every word earns its place and the most important disambiguator ('not deleted') is positioned at the end for emphasis.

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 single-parameter tool with no output schema and no annotations, this is nearly complete: purpose, cost impact, and data fate are all covered. The only gaps are minor — no mention of reversibility via resume_instance and no statement about calling pause on an already-paused instance — but nothing an agent needs to safely invoke the tool 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?

Schema coverage is 100%, and the schema already documents the single id parameter with provenance ('as returned by create_instance or list_instances'). The description adds no parameter-level detail beyond 'an instance,' so baseline 3 applies — the schema does the heavy lifting and the description neither conflicts nor adds value here.

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 ('Pause an instance') plus the concrete effects: stopping the instance and its billing lease. The phrase 'Data is archived, not deleted' actively distinguishes it from the destructive sibling delete_instance, so an agent can tell it apart without opening other schemas.

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 the decision context — pause when you want to stop compute and billing while preserving data — especially through the contrast 'archived, not deleted.' However, it never explicitly names alternatives like resume_instance (for restarting) or delete_instance (for full removal), so the agent must infer the routing logic.

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?

With no annotations, the description carries the behavioral burden: 'Get' indicates a read-only fetch, and the description enumerates what is returned, including the beta status of crypto and Stars. It doesn't state permissions or rate limits, but the read-only nature is well conveyed.

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 front-loads the main purpose and appends a compact list of return categories plus a beta caveat. Every element earns its place, and there is no filler.

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 one-parameter getter with no output schema, the description is largely complete: it names the resource, all payment option categories, the beta caveat, and the extra term field. It could be more explicit about response shape, but that is not necessary for correct invocation.

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 covers the sole id parameter at 100% and explains that it's an instance/agent id. The description adds no parameter-specific semantics beyond connecting the id to 'an instance's plan', which is enough to hit the baseline.

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 opens with a specific verb and resource: 'Get ways to pay for an instance's plan', then lists the exact contents (card/subscription links, crypto, Telegram Stars, term). This clearly identifies the tool's function and distinguishes it from instance lifecycle/health siblings.

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 wording implies the tool should be used when the agent needs payment options or billing info for an instance, but it gives no explicit when/when-not guidance or comparison to alternatives like instance_term. The context is clear enough to avoid misuse, just not fully 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?

With no annotations provided, the description carries the full behavioral burden. The example discloses that rebuild entails a restart, which is useful, but the description never states consequences such as downtime, whether data persists across the rebuild, or any prerequisite instance state. For a disruptive mutating operation this is a noticeable 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?

A single sentence delivers both the action and the canonical use case with no wasted words. The parenthetical example earns its place by clarifying when a rebuild, rather than a simpler lifecycle operation, is warranted.

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 tool with full schema coverage, the description covers purpose and a typical trigger scenario. However, with no annotations and no output schema, it leaves the agent to infer post-invocation behavior such as downtime, data persistence, and whether the instance retains its ID.

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% — the id property is fully documented, including its provenance from create_instance or list_instances. The description adds no parameter-specific detail, but none is needed; this matches the baseline of 3 for full schema coverage.

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 action on a specific resource — 'Rebuild an instance's pod' — with a concrete example scenario, 'after a config change that needs a restart.' The rebuild/restart framing implicitly separates it from siblings like pause_instance and resume_instance, but no alternative is named explicitly, so it falls short of a 5.

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 parenthetical example gives a clear trigger condition: use this tool when an instance's configuration has changed and needs a restart. This is concrete context for when to invoke it, though the description does not state when not to use it or name alternative tools.

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 must carry full behavioral burden. It does disclose that resuming involves rebuilding from an archive, which is useful, but it omits side effects, prerequisites beyond 'previously paused,' and any consequences for existing state. For a state-changing operation, this is a meaningful 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?

A single sentence that leads with the verb and resource, includes only essential qualifiers, and no filler. It 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?

With one well-documented parameter and no output schema, the core mechanics are present. However, for a mutation operation with no annotations, the lack of information about expected outcomes, errors, or disambiguation from rebuild_instance leaves the description only minimally 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 coverage is 100%: the 'id' parameter is already documented as the instance id with provenance. The description doesn't add parameter-specific detail, so the baseline score 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?

Description uses a specific verb ('Resume') with a clear resource ('previously paused instance') and adds the mechanism 'rebuilding it from its archive,' which distinguishes it from create_instance and rebuild_instance. The meaning is immediately clear.

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 'previously paused instance' establishes when to use this tool: after pause_instance. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to select it over create, delete, or rebuild.

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?

With no annotations provided, the description carries the burden of behavioral disclosure. It adds the key nuance that passing null clears the key, and that setting the key is a prerequisite for an instance to respond. However, it does not mention side effects like replacing an existing key or any error conditions, so it is not fully comprehensive.

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 concise sentences front-load the core action and then provide the crucial usage context. There is no redundancy or filler.

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 setter tool with no output schema, the description covers the key purpose, the null-clearing behavior, and the prerequisite context. Minor gaps remain: model semantics are not defined, and the source for valid provider ids is not explicitly routed to list_platforms, but these are optional or inferable.

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 coverage is 50%: provider and key are documented in the schema, while id and model are not. The description adds semantics for key via the 'clear, with key=null' clause, but does not explain what id or model mean, leaving the undocumented parameters without sufficient guidance.

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 ('Set') and resource ('LLM provider API key'), and clarifies the clear behavior with key=null. This distinguishes it from siblings like set_peers, since it explicitly targets the LLM key rather than any other setting.

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 clear context: 'Required before a freshly created instance can actually respond', which tells the agent when this tool should be called relative to create_instance. It does not explicitly name alternatives or when-not-to-use, but the applicability is strongly implied.

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?

With no annotations, the description carries the full burden of behavioral disclosure. It indicates that the tool manages allowed outbound calls, but it does not state whether the list is fully replaced, whether peers are validated, or how tokens are handled. The update semantics and side effects are unclear.

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 no redundancy. Every word contributes to the core meaning, making it easy to parse quickly.

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 mutation tool with two required parameters, no annotations, and no output schema, the description lacks essential context: how to specify the target instance, whether the peer list is replaced or merged, and what the expected response or error conditions might be. The description is too sparse to fully support correct invocation.

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 has 0% description coverage, so the description needed to explain the parameters. It only hints that peers are callable A2A agents by name; it never clarifies what 'id' refers to, what a peer 'url' represents, or what 'token' is for. This leaves an agent uncertain about how to construct a valid request.

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 action ('Set'), the object ('the list of other A2A agents'), and the scope ('this instance is allowed to call by name'). This distinguishes it from sibling tools, which focus on instance lifecycle rather than peer configuration.

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 usage guidance is provided. The description does not mention prerequisites (e.g., the instance must already exist), when this should be used relative to other configuration tools, or any conditions or exclusions. The intended use must be inferred from the tool name and sibling context.

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