canaryusers

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

With no annotations, the description carries full behavioral burden and excels: discloses async status behavior, credit usage for deep, visual vs. static check differences, time estimates, and the required follow-up with get_report_markdown. All beyond what the schema conveys.

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 long but every sentence serves a purpose: core action, depth comparison, async handling, and post-scan instructions. It is front-loaded with the main function and logically organized.

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 and no annotations, the description fully covers purpose, parameters, async polling, and next steps. It even includes the agent's required action ('Always fetch and present the findings before stopping, then offer to fix the top issues'). Nothing important 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?

Though schema covers both parameters, the description adds substantial meaning: url must be live/deployed, depth='deep' renders visually on desktop/mobile and clicks flows, uses ~1 credit, while 'quick' is a fast static check that misses those issues. This gives the agent decision-making context for selecting depth.

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?

Clearly states verb+resource: 'Run a CanaryUsers UX scan on a DEPLOYED URL' and explains the evaluation approach. Distinguishes from sibling tools by focusing on initiating a scan, while get_report_markdown retrieves reports and list_recent_scans lists past scans.

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 when-to-use guidance for depth values ('use deep when the user mentions mobile, layout, or visual problems') and describes the full workflow, including waiting for status 'running' and then calling get_report_markdown. Also instructs to always present findings and offer fixes.

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 describes the output format (markdown) and content (ranked findings, why each matters, how to fix it), which is useful. It does not mention side effects, but this is a read-only reporting tool with no obvious destructive 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?

Two sentences, no fluff. The first sentence immediately conveys the tool's purpose and output maturity; the second sentence gives a key prerequisite. Perfectly front-loaded and efficiently 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?

For a single-parameter tool with no output schema and no annotations, the description sufficiently explains the tool's behavior, input source, and output content. It is complete enough for an agent to select and invoke 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?

The schema already fully describes scanId as 'The scan id (UUID) to fetch' (100% coverage), so baseline is 3. The description adds value by sourcing the scanId from list_recent_scans, which clarifies where to obtain this value and reinforces tool flow.

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 ('Get') and resource ('one scan's full report as AI-ready markdown'), and explicitly differentiates from siblings by mentioning the scanId comes from list_recent_scans. It distinguishes itself clearly from other 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?

It provides clear context for when to use the tool ('Get one scan's full report') and instructs to pass a scanId from list_recent_scans, which implicitly guides the user to use list_recent_scans first. No explicit exclusions or alternatives, but the usage context is clear.

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

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

No annotations are present, so the description bears the full burden. It discloses returned fields and account scoping, and 'List' implies a read-only operation. However, it does not mention ordering details (beyond 'most recent'), pagination behavior, or any permission requirements, which would add transparency.

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 only two sentences and front-loaded with the main action. The parenthetical list of returned fields efficiently conveys output, and the second sentence adds a useful usage hint. No unnecessary words.

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 tool is simple with one optional parameter and no output schema. The description covers purpose, returned fields, and usage, which is sufficient for an agent to select and invoke the tool correctly. Minor omissions like exact sort order or pagination details do not significantly impair completeness.

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% for the only parameter 'limit', which is fully documented in the schema. The description adds no extra meaning beyond implying that the limit controls how many recent scans are returned, so the baseline score of 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?

Description clearly states the action 'List' and the resource 'CanaryUsers UX scans', with the scope 'most recent' and the specific fields returned. This distinguishes it from siblings like 'canary_scan' (likely a single scan lookup) and 'get_report_markdown' (report retrieval).

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 the use case: 'Use this to find a scan to dig into.' This provides clear context for when to invoke this tool. It does not name alternatives explicitly, but the purpose and sibling names imply the distinction.

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