canaryusers
Server Details
A flock of AI users tests your deployed app and reports where real people get stuck, with fixes.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.4/5 across 3 of 3 tools scored.
Each tool has a clear, distinct purpose: initiating a scan, retrieving a report, and listing scans. No overlap or ambiguity.
All tool names follow the snake_case verb_noun pattern consistently, making them predictable and easy to understand.
Three tools are well-scoped for the UX scanning domain, covering the essential workflow without unnecessary complexity.
The tool surface covers the core lifecycle (initiate, retrieve, list) but lacks optional operations like deleting scans or managing account credits.
Available Tools
3 toolscanary_scanAInspect
Run a CanaryUsers UX scan on a DEPLOYED URL (your live or preview app — not source code). A flock of AI personas evaluates the page and reports where real users would get stuck, with concrete fixes. Returns AI-ready findings you can act on immediately. Use depth='deep' for the thorough scan that renders the page, checks it VISUALLY on desktop + mobile (catches mobile breakage and layout issues), and clicks through key flows like signup/checkout (slower, ~60-90s, uses one credit); depth='quick' (default) is a fast static check that does NOT see mobile or visual issues — use 'deep' when the user mentions mobile, layout, or visual problems. IMPORTANT: if this returns status 'running' with a scanId, the findings are not ready yet — wait ~30s, then call get_report_markdown(scanId), repeating until it returns the report. Always fetch and present the findings before stopping, then offer to fix the top issues.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The public URL to scan (e.g. your deployed app or preview URL). | |
| depth | No | 'quick' (default, fast, free) or 'deep' (clicks through flows + visual review, ~1 credit). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description bears full burden. It fully discloses behavior: deep scan renders, visual checks desktop+mobile, clicks flows, takes ~60-90s, uses credit; quick is static. Also mentions async status and polling.
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?
While thorough, the description is somewhat long. However, it is well front-loaded with core purpose and each sentence adds value. Minor room for tightening.
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 with async behavior, two depths, and sibling interaction, the description is complete. It covers all necessary details for correct invocation and follow-up.
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%, but description adds significant meaning beyond schema: explains depth options with specific use cases, timing, credit cost, and default value. This helps agent choose correctly.
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 it runs a CanaryUsers UX scan on a deployed URL, distinguishing it from siblings like get_report_markdown (retrieves report) 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 guidance on when to use 'quick' vs 'deep' depth, including scenarios like mobile/layout issues. Also instructs on handling 'running' status and calling get_report_markdown with polling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_report_markdownAInspect
Get one scan's full report as AI-ready markdown: the findings ranked by severity, why each matters, and how to fix it. Pass a scanId from list_recent_scans.
| Name | Required | Description | Default |
|---|---|---|---|
| scanId | Yes | The scan id (UUID) to fetch. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Describes output format and content but does not explicitly state read-only nature, side effects, or error handling. Adequate but could add safety cues.
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, no wasted words. Front-loaded with purpose and immediate 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?
Covers main behavior and output. Lacks mention of error cases (e.g., invalid scanId) but acceptable for a simple retrieval tool. No output schema needed.
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 covers parameter fully (100% coverage). Description adds value by explaining that scanId comes from list_recent_scans, aiding correct invocation.
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?
Clear statement of action: 'Get one scan's full report as AI-ready markdown' and specific content. Distinguishes from siblings 'canary_scan' and 'list_recent_scans' by focusing on 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 directs to use scanId from sibling 'list_recent_scans', providing usage context. Could be improved by mentioning when not to use (e.g., for raw JSON data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_recent_scansAInspect
List the most recent CanaryUsers UX scans for your account (id, URL, CanaryScore, grade, status, date). Use this to find a scan to dig into.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many to return (default 10, max 50). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It lists returned fields and indicates 'most recent', but does not specify ordering, time window, pagination, or any constraints like account scope. For a list tool, this is adequate but could be more 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 a single sentence plus a short usage tip, with no superfluous words. It is front-loaded with the core purpose and efficiently communicates the tool's role.
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 low complexity (single optional parameter, no output schema), the description adequately covers the return format by listing fields. However, it omits ordering details (e.g., descending by date) and the definition of 'recent', which would improve 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 coverage is 100% for the single parameter 'limit', with a clear schema description. The tool description adds no extra meaning beyond the schema; it merely mentions 'most recent' without linking to the limit parameter.
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 'List' and resource 'recent CanaryUsers UX scans', specifying returned fields (id, URL, CanaryScore, grade, status, date). This distinguishes it from sibling tools: canary_scan (likely single scan details) and get_report_markdown (markdown export).
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 advises using this tool 'to find a scan to dig into', implying a precursor to further analysis. While it doesn't explicitly state when not to use it or name alternatives, the context with siblings and the purpose are clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
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