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Search or aggregate through an adapter

liquid_query
Read-onlyIdempotent

Run server-side search or aggregation on any connected API and receive only the answer, not the full payload. Reduces token usage by returning filtered results or summaries.

Instructions

Run a server-side search or aggregation through an adapter and get just the answer instead of the full payload — deterministic, no LLM call, read-only. Two modes: set group_by/agg to aggregate (counts, sums, …), or where/fields/limit to filter and project. Side effects: a read-only outbound HTTP(S) request to the connected API, rate-limited like liquid_fetch. Returns search results {records, data, _meta} or an aggregation {result, _meta}. Prefer this over liquid_fetch whenever you only need a filtered slice, a count, or a summary — it returns far fewer tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adapter_idYesAn adapter id returned by liquid_connect (or listed by liquid_list_adapters).
endpointNoOptional endpoint path to act on (e.g. "/users"); defaults to the adapter's primary endpoint. Use a path shown by liquid_connect / liquid_list_adapters.
whereNoSearch-mode filter as field -> value (or field -> {op: value}), e.g. {"status": "active", "price": {"gt": 100}}. Keys are target_model fields.
fieldsNoSearch-mode projection: target_model field names to return, e.g. ["name", "price"]. Omit for all fields.
limitNoSearch-mode max records to return (default 100).
group_byNoAggregate-mode: target_model field to group by, e.g. "category".
aggNoAggregate-mode: aggregations per group as field -> op, e.g. {"price": "sum", "id": "count"}. Provide together with group_by.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
recordsNoSearch mode: number of records.
dataNoSearch mode: matching records (capped at 100).
resultNoAggregate mode: the grouped/aggregated result.
_metaNoCall metadata: adapter_id, service, endpoint, latency_ms (and records when applicable).
errorNo
Behavior5/5

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

Beyond annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true), the description adds details: 'read-only outbound HTTP(S) request to the connected API, rate-limited like liquid_fetch', and emphasizes deterministic behavior. This fully discloses side effects and constraints.

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 relatively concise and front-loads the main purpose. However, it could be slightly more structured by separating search and aggregate modes more explicitly. Nonetheless, every sentence adds value and there is no redundancy.

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 complexity (7 parameters, nested objects, output schema present), the description covers modes, side effects, and comparison with siblings. The output schema exists, so return values are not needed. The description is complete and sufficient for an agent to use the tool 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%, baseline is 3. The description adds value by explaining parameter roles in modes: 'set group_by/agg to aggregate (counts, sums, …), or where/fields/limit to filter and project.' This clarifies semantics beyond the schema, but does not dive into every parameter's format.

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?

The description explicitly states the tool's function: 'Run a server-side search or aggregation through an adapter and get just the answer instead of the full payload.' It distinguishes itself from sibling tools like `liquid_fetch` and clearly defines two modes (search and aggregate).

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

Usage Guidelines5/5

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

The description provides explicit guidance: 'Prefer this over liquid_fetch whenever you only need a filtered slice, a count, or a summary — it returns far fewer tokens.' It also mentions read-only, deterministic nature, and no LLM call, helping the agent decide when 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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