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Ask Agent Ready in natural language

ask
Read-onlyIdempotent

Search Agent Ready's scoring methodology, check registry, specs, and content library using natural-language queries. Optionally filter by type or get extractive summaries.

Instructions

Natural-language search (NLWeb /ask) over Agent Ready's own content — scoring methodology, the check registry, the specs it validates, and the content library (explainers, comparisons, how-to guides, glossary). Public, no API key required. Returns Schema.org-typed result objects; optional itemType narrows to a corpus type and mode 'summarize' adds an extractive summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesNatural-language question about Agent Ready's scoring methodology, its check registry, the specs it validates, or its content library (explainers, comparisons, how-to guides, glossary).
modeNo'summarize' adds an extractive summary over the top results.
itemTypeNoOptional filter narrowing the search to one corpus type ('page' = explainers/guides/glossary).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
siteNo
_metaNo
errorNo
queryNo
resultsNo
summaryNo
query_idNo
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive. Description adds return type (Schema.org-typed objects) and effects of mode and itemType, going beyond annotations without contradiction.

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

Conciseness5/5

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

Three sentences, efficiently front-loaded with purpose. No redundant information; each sentence adds unique value.

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 (3 parameters, one required, has output schema), description covers inputs, outputs, security, and optional behaviors. Sufficient for an agent to select and invoke correctly.

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

Parameters4/5

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

Schema coverage is 100% so baseline 3. Description adds context: frames 'q' as natural-language question over specific content, explains 'mode' adds summary, and 'itemType' filters corpus type – meaningful value beyond schema.

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 is a natural-language search over Agent Ready's content, listing specific domains. Verb 'search' and resource are explicit, distinguishing it from sibling tools like scan_site and validate_structured_data.

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

Usage Guidelines4/5

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

Mentions it is public with no API key required, and describes optional parameters. Implicitly suggests use for questions about Agent Ready's content, but does not explicitly contrast with siblings or state when not to use.

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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