New Shopify Stores Radar

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

With destructiveHint and idempotentHint annotations already declaring the destructive and idempotent nature, the description adds specific behavioral details: it aborts only starting/running runs, returns updated run details, and explains the graceful option with a 30-second timeout. This goes beyond the annotations without contradicting them, though it could mention edge cases like double-abort behavior.

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 well-structured: the main purpose is stated first, followed by behavioral details, then usage guidelines and examples. It is concise but includes an unnecessary repetition of 'Abort' in the USAGE line. The examples are helpful and the overall length is appropriate for the tool's complexity.

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 (2 params, one required), the description is complete: it explains the core action, the conditions under which it has no effect, the return of updated run details, the graceful option, and provides concrete examples. The presence of an output schema means the description need not detail return fields. No critical information 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?

Both parameters (runId and gracefully) are fully described in the schema (100% coverage), and the description repeats the graceful behavior without adding new information beyond the schema. Since the schema already explains the parameters thoroughly, the description provides no extra value here, warranting the baseline score 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 clearly states the tool aborts an Actor run that is starting or running, and specifies that it has no effect on finished runs (SUCCEEDED, FAILED, ABORTING, ABORTED, TIMED-OUT). This precisely distinguishes it from sibling tools like get-actor-run (read-only) and call-actor (starts a run), leaving no ambiguity about the action and resource.

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 USAGE section explicitly says to use it when a run is 'taking too long or misconfigured,' and the no-effect statement implicitly warns against using it on already-finished runs. However, it does not explicitly name alternative tools (e.g., get-actor-run for checking status), so it falls short of the 'explicit alternatives' criterion for 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?

Beyond the readOnly/idempotent annotations, the description discloses key behaviors: waitSecs blocks up to a cap, summary describes past execution, and nextStep prescribes a follow-up action with interpolated identifiers. It also clarifies that storages are returned as an alias map, giving the agent a realistic picture of the response.

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 well organized with a front-loaded purpose, a structured return summary, a dedicated USAGE section, and compact examples. Every sentence contributes either behavioral detail or invocation guidance, with no filler or 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 the simple two-parameter schema and the presence of an output schema, this description is complete: it explains what the tool returns, how waitSecs affects behavior, how summary and nextStep should be interpreted, and when to invoke it. An agent has everything needed 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?

Schema description coverage is 100%, so the runId and waitSecs parameters are already fully documented. The description adds a small amount of practical framing — "Pass waitSecs > 0 to block until terminal" — and concrete examples, but it mostly restates information already present in the input 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 states a specific verb and resource — "Get detailed information about a specific Actor run" — and then lists the exact result fields. It clearly distinguishes this from siblings like get-dataset-items or fetch-actor-details by centering on run status and run-level 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?

The USAGE section explicitly says to use this tool to check the status of a run started by an Actor-running tool and explains when to use waitSecs. It does not explicitly name sibling alternatives or state when not to use this tool, so it falls short of full exclusion-based 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?

With annotations already declaring readOnlyHint=true and idempotentHint=true, the description adds valuable behavioral context: returns rows themselves, default limit of 20, and clean=true behavior. It also clarifies the nature of the return value beyond the 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?

Well-structured with clear USAGE and USAGE EXAMPLES sections. Some redundancy ('Get items (rows)...' and 'Returns the rows themselves...') but overall efficient and front-loaded with 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 the tool has 8 parameters, an output schema, and rich annotations, the description adequately covers key behaviors, usage triggers, and examples. It doesn't explain every parameter but relies on the schema for that, which is appropriate.

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%, so baseline is 3. The description adds extra meaning by explaining default limit (20) and the clean=true shortcut, which supplements the schema. It also provides examples for fields usage, though most parameter semantics are in 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?

Description clearly states the tool gets items (rows) from a dataset and explicitly distinguishes it from metadata, counts, or schema. It names the exact resource (dataset items) and the action (get), and provides direct trigger phrases for when to use it.

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?

Provides explicit use cases ('when the user provides a datasetId and asks to retrieve results...'), and clarifies what it is not for (metadata, counts, schema). However, it does not name alternative tools explicitly, only implies them.

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 establish readOnlyHint, idempotentHint, and destructiveHint as false. The description adds valuable behavioral context beyond this: the exact key name requirement and the preservation of Content-Encoding with automatic client decompression. No contradictions 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 well-structured with a concise opening definition, a short behavioral note, and clear usage examples. Every section earns its place without unnecessary 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 two-parameter read-only tool with full schema coverage, an output schema, and strong annotations, the description covers the essential context: how to target a record, what to expect (Content-Encoding), and when it applies. The sibling context also helps differentiate it from listing operations.

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 coverage is 100%, so the schema already documents both parameters. The description adds usage examples and the 'exact key name' requirement, but these are minimally additive beyond the schema's own property descriptions.

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 and resource: 'Get the value stored under a specific key in a key-value store.' It also distinguishes itself by explicitly stating this is 'a single record, not a listing of all keys,' which separates it from sibling tools like get-dataset-items.

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 a clear usage context: 'Use when you need to retrieve a specific record (JSON, text, or binary) from a store.' It does not name alternative tools explicitly, but the 'not a listing of all keys' phrase gives implicit exclusion guidance for listing-style operations.

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 signal readOnlyHint=false and destructiveHint=true, and the description adds useful context: results come from public Certificate Transparency logs, are flat JSON, and contain no personal data. However, it does not explicitly disclose that this starts a billed Actor run or may return before completion when waitSecs is reached, though those details exist in the input 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?

Two tight sentences: the first states the operational wrapper and the second gives a useful actor summary. The only minor redundancy is restating the full Actor identifier immediately after the title already contains it.

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 schema root description fully covers the feed/enrich modes, per-result billing, and maxItems cap, and an output schema exists, so the short description is adequate at a high level. It does not mention mode selection or the wait/poll flow, but those are already specified in the input schema and waitSecs parameter.

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 all 8 parameters, including mode-specific behavior, are already documented in the schema. The description only indirectly echoes the domains parameter through "Also checks any domain for Shopify" and adds no parameter-level detail, so the baseline 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 names the exact Actor and uses a concrete verb: "calls the Actor ... and retrieves its output results." The actor blurb further specifies the resource — newly detected Shopify stores plus domain checks — making it unmistakable what this tool does and clearly distinct from sibling run-management tools.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no comparison to siblings like get-actor-run or get-dataset-items for polling or retrieving datasets. The actor blurb implies use cases such as new-store discovery and Shopify domain checks, but the selection rule 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.