Revuo

products.find_agent_ready

Read-only

Find products with the highest agent readiness scores — products that are easiest for AI agents to integrate with. Sorted by compositeScore desc; supports skip/limit pagination. All readiness scores are 0-100, higher better. Calibration: <30 = not agent-ready (default minimumScore filter), 30-49 = early/limited, 50-69 = decent, 70-89 = strong, 90+ = exceptional. Ranking basis: compositeScore desc. Tier is NOT a tiebreaker here — buyer intent is technical fit, not paid placement. Every result carries { position (1-based, within the returned page), rank (0..1; 1.0 = top of this page) } so callers can merge results across tools consistently. Response: { products: [{ position, rank, slug, name, tagline, websiteUrl, tier (free|verified|featured), unverified (true when no approved vendor claim), verifiedAt (ISO; nullable), agentReadiness: { compositeScore, apiScore, protocolScore, sdkScore, integrationScore, dxScore } (each 0-100), mcp?: { hasMcpSupport, totalToolCount, serverCount } }] }.

Input Schema

TableJSON Schema

Name	Required	Description
`skip`	No	Number of results to skip (for pagination). Default 0.
`limit`	No	Maximum number of results to return per page. Caps at 50.
`minimumScore`	No	Minimum composite agent readiness score (0-100). Higher = more agent-ready. 0 returns everything; 50 is a usable threshold.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`error`	No
`products`	No

TDQS

A4.5/5.0

Behavior5/5

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

Annotations declare readOnlyHint and openWorldHint. Description adds detailed behavioral context: pagination with skip/limit, sorting by compositeScore descending, ranking behavior (position and rank within page), and the fact that tier is not a tiebreaker. This goes beyond what annotations provide, making tool behavior transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but somewhat lengthy. It front-loads the core purpose and then systematically covers calibration, ranking details, and response structure. Every sentence adds value, but the full response schema could potentially be omitted since an output schema is provided. Still, it's well-structured and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool complexity (multiple scoring dimensions, pagination, ranking, output schema), the description is thorough. It explains the scoring calibration, ranking behavior, response structure including nested fields like agentReadiness and MCP info. No obvious gaps for an agent to use this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all three parameters with descriptions. The description adds valuable calibration context for minimumScore (scores 0-100 with thresholds like <30 not agent-ready, 50+ decent, etc.), which significantly enhances parameter understanding beyond the schema's default and range info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it finds products with highest agent readiness scores, sorted by compositeScore, with pagination. It distinguishes from siblings by specifying the agent-readiness focus and explaining that tier is not a tiebreaker, setting it apart from general search or ranking tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for finding agent-ready products and provides calibration thresholds for minimumScore, which helps in parameter selection. However, it lacks explicit guidance on when to use this tool versus alternatives like products.search or rankings.get. No 'when not' or alternative tool names are mentioned.

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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TDQS

A4.4/5.0

Disambiguation4/5

The namespace grouping separates products, tools, taxonomy, and rankings cleanly, and each tool's description points to its intended query mode. Some overlap exists between products.search and products.find_by_capability, and between tools.search and tools.find_for_task, but the descriptions are detailed enough that an agent can usually pick correctly. categories.list and directory.overview also overlap, though directory.overview is explicitly marked as the preferred entry-point.

Naming Consistency4/5

The set follows a predictable `resource.action` dotted convention, with all-lowercase names and snake_case within actions. Minor deviations such as `directory.overview`, `tools.changes`, and `mcp.score_server` mix noun actions and verb+object phrases, but the overall pattern remains readable and easy to guess.

Tool Count4/5

14 tools is appropriate for a read-only directory covering products, capabilities, rankings, MCP setup, and tool discovery. The count is slightly high because the search/find family has several close variants, but each variant has a distinct query style and use case.

Completeness5/5

The surface covers the domain thoroughly: taxonomy, product search and details, capability lookup, agent-readiness scoring, rankings, MCP setup, tool discovery, and schema-drift detection. Cross-references such as products.get_mcp_setup supplying the hash consumed by tools.changes close the main workflow loops without dead ends.

Resources

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