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

With no annotations provided, the description adequately discloses a read-only behavior and the return of balance and billings. There is no mention of side effects, rate limits, or auth requirements, but the tool is simple with no parameters and an output schema.

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 long with no wasted words. It front-loads the purpose immediately and follows with practical usage guidance.

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 the tool has no parameters, an output schema, and no annotations, the description fully covers its functionality, including both the return value and practical use cases.

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, and the input schema coverage is 100% (vacuously). The description does not need to add parameter information, so a baseline of 4 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 clearly states 'Return the current Prime Intellect wallet balance and recent billings,' identifying a specific verb and resource. It distinguishes itself from sibling tools like pod_create and pod_quote by focusing on wallet balance.

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 explicit use cases: estimating pod runtime and debugging insufficient-funds errors. It lacks an explicit when-not-to-use section, but the context is clear enough for a simple getter tool.

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 adequately discloses that it returns GPUAvailability rows and lists fields. It implies a read-only operation and mentions the unfiltered response is large, but could add performance or reliability notes.

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 concise with three sentences: purpose, detail on returned data, and usage guidance. No superfluous words, well-structured.

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 the tool has three optional parameters and an output schema, the description covers purpose, return type, and usage context. It could elaborate on pagination or filtering behavior, but overall 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% and each parameter has a description. The tool's description adds value by noting that gpu_type is strongly recommended due to large unfiltered response, which goes beyond 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 tool lists currently-available GPU pods matching filters, with a specific verb and resource. It distinguishes itself from siblings by mentioning its role before pod_quote or for showing 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?

It explicitly says 'Use this to pick a target before pod_quote, or to show the user options,' providing clear context. However, it does not explicitly state when not to use it or compare to alternatives.

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 exist, so the description must cover behavioral traits. It accurately describes a safe, read-only list operation. While it doesn't discuss data freshness or rate limits, the simplicity of the tool (no parameters, no side effects) makes the implicit behavior clear. Slight deduction for not mentioning any potential delays or consistency guarantees.

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, each earning its place. The first sentence states the action and gives examples. The second provides usage guidance. No wasted words, and critical information is front-loaded.

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 the tool's simplicity (no parameters, clear output described), the description is complete. The existence of an output schema means return values are fully specified. The description directly addresses the agent's need to clarify vague user requests and chain to other tools.

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 parameters, so schema description coverage is 100%. With 0 parameters, the baseline is 4. The description adds value by providing examples of GPU types, which helps agents understand the output without needing to inspect the output 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?

Description clearly states the tool lists all GPU types offered by Prime Intellect, with specific examples like 'H100_80GB' and 'A100_80GB'. It distinguishes from siblings by specifying its role in clarifying vague user requests and directing results to list_availability or pod_quote.

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?

Explicitly states when to use the tool: 'when the user is vague about what they want.' Also provides clear next steps: 'Pass the result into list_availability or pod_quote.' This leaves no ambiguity about context and downstream usage.

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 full burden for behavioral disclosure. It states the tool returns matching pods but does not mention whether it is read-only, side effects, rate limits, or refresh behavior. For a check tool, assuming read-only is reasonable but not explicit.

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, no wasted words. The first sentence states purpose, the second provides usage guidance. Front-loaded with key 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 simple tool with no parameters and an output schema (not shown but exists), the description is fairly complete. It could note that the operation is read-only, but overall it covers what the tool does and when to use it.

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?

Tool has zero parameters, baseline is 4 per instructions. Description adds context about the filtering criteria (max_lifetime_hours and cost limit) which are not parameters but clarify the tool's logic. Schema coverage is 100% due to no parameters.

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 clearly states it returns 'locally-tracked pods that have run past max_lifetime_hours OR whose accumulated cost is approaching PRIME_MAX_TOTAL_USD'. This distinguishes it from sibling tools like 'pod_list' (list all) and 'pod_status' (status of specific pod), providing a specific verb+resource combination.

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?

Explicitly advises 'Call this at the start of long-running sessions to catch forgotten pods', giving clear when-to-use context. While it doesn't exclude other scenarios, the guidance is sufficient for typical use.

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, description discloses dry-run vs actual provisioning, server constraints, and side effects like recording in state.json for runaway detection.

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?

About 80 words, well-structured with bullet points, front-loaded with key action, no wasted sentences.

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?

Covers both modes, constraints, side effects. Output schema exists so return values not needed. Complete for provisioning 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?

100% schema coverage but description adds context: explains confirm's dual role, constraints on max_lifetime_hours, and how quote_token is used.

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 clearly states it provisions a GPU pod or previews provisioning, using specific verbs like 'provision' and 'preview'. It distinguishes from siblings like pod_quote and pod_terminate.

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?

Explains when to use confirm=False vs True and lists server-enforced constraints. No explicit 'when not to use' but implicit from 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?

With no annotations, the description solely bears the burden. It mentions the statuses included but not any side effects, ordering, or pagination. Since an output schema exists, return value details may be covered there, but additional behavioral context (e.g., no mutations, read-only) is absent.

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. Every word contributes meaning, making it maximally concise for its 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?

Given zero parameters and an existing output schema, the description is largely sufficient. However, it could be slightly more complete by clarifying that it lists all visible pods without filtering (vs. pod_status for a specific pod).

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?

No parameters exist, and schema coverage is 100% (trivially). The description adds no parameter information because none is needed. Baseline for zero parameters is 4.

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 specifies the verb 'List', the resource 'pod', and the scope: 'every pod the API key can see' with explicit statuses (active, provisioning, stopped). It is distinctive from siblings like pod_status or pod_terminate.

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 explicit guidance on when to use this tool vs. siblings such as pod_status for a specific pod. The description only states what it does, not when it is appropriate.

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, description carries full behavioral burden. It discloses no side effects, TTL of 60s, server picks cheapest matching row, and returns error with available options if no match. Comprehensive and honest.

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?

Four sentences with front-loaded purpose, then flow, behavior, and error case. No fluff, every sentence adds value. Very concise.

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 the complexity and presence of output schema, the description covers essential aspects: return value, TTL, side-effect-free nature, selection logic, and error behavior. Complete for a quoting 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 schema already documents each parameter well. Description adds overall logic (cheapest matching) but no extra per-parameter meaning beyond schema defaults and examples.

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 clearly states the tool gets a non-binding price quote and reserved provisioning payload, distinguishing it from sibling tools like pod_create. It specifies the verb 'Get' and the resource, making purpose unambiguous.

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?

Description explains that the tool has no side effects and that the returned quote_token should be passed to pod_create with confirm=True to provision. It implicitly guides usage before creation, but lacks explicit when-not-to-use or alternatives.

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 provided, so description carries full burden. It discloses polling behavior every 5s, blocking until SSH available, and return format for SSH connection. It does not cover rate limits or permissions but is sufficient for safe use.

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?

Description is brief (4 sentences), front-loaded with purpose, then explains the optional blocking behavior and SSH usage. Every sentence adds value with no redundancy.

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 tool complexity (polling, SSH) and presence of output schema, description adequately explains the blocking behavior and SSH string usage. Lacks details on full return object but output schema covers that.

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?

Input schema has 100% description coverage, so baseline is 3. Description adds marginal value by contextualizing SSH connection usage but essentially repeats parameter descriptions found in 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?

Description clearly states the tool gets pod status with specific statuses, and distinguishes from siblings like pod_create, pod_list, and pod_terminate by focusing on a single pod and offering SSH readiness detection.

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 status and waiting for SSH, but does not explicitly state when to use versus alternatives like pod_list or pod_create, nor provides when-not-to-use guidance.

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 behavioral disclosure. It mentions idempotency and preview behavior, but it does not disclose potential side effects, required permissions, or data loss risks. While the preview feature adds transparency, the description lacks warnings about irreversibility, making it only partially transparent.

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 long, with the first sentence concisely stating purpose and idempotency, and the second explaining the preview feature. No unnecessary words or repetitions; every sentence earns its place, making it highly efficient and front-loaded.

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 destructive tool with a clear output schema, the description covers purpose, idempotency, and preview behavior. However, it does not mention prerequisites (e.g., pod existence is handled by idempotency) or any contextual warnings about consequences. Slight gaps in completeness, but overall adequate given the tool's simplicity.

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% with descriptions for both parameters. The description adds value by clarifying the confirm parameter's preview behavior beyond the schema's 'Required True to actually terminate.' This extra context improves understanding without redundancy, justifying a score above the baseline of 3.

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 'Destroy (terminate) a pod' with a clear verb and resource. It also notes idempotency on already-deleted pods, adding clarity. The tool is uniquely positioned among siblings as the only destroy operation, making its purpose unambiguous.

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 explains the preview behavior with confirm=False, guiding when to preview vs execute. However, it does not provide explicit when-to-use or when-not-to-use guidance, nor does it compare to alternatives like pod_check_runaway. The usage guidelines are implied but not fully elaborated.

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