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askdkc

pgroonga-mcp

by askdkc

pgroonga_search

Run PGroonga full-text searches on PostgreSQL with structured filters, modes, and snippets.

Instructions

Execute a bounded, catalog-validated PGroonga search with structured filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
limitNo
orderNoscore
queryYes
targetYes
filtersNo
snippetNo
returnColumnsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
queryYes
targetYes
rowCountYes
warningsYes
truncatedYes
executionMsYes
scoreAvailableYes
normalizedQueryYes
snippetAvailableYes
normalizationProfileYes
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds meaningful context by stating the search is 'bounded' (enforcing limit) and 'catalog-validated' (checking target schema/table/column existence), which are useful constraints. However, it omits details like read-only behavior, error conditions, or requirements for PGroonga indexes. It provides some value beyond a bare search but leaves significant gaps.

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?

The description is a single, front-loaded sentence with no wasted words. Every phrase ('bounded', 'catalog-validated', 'structured filters') adds value and the structure is easy to scan.

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

Completeness2/5

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

Given the tool has 8 parameters, 3 required, and a rich nested schema, the description is far too short to provide complete context. It does not explain the various search modes, filter operator semantics, limits, or ordering behavior. The presence of an output schema reduces the need to detail return values, but the input behavior remains under-specified. This is inadequate for a tool of this complexity.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for explaining parameters. It hints at 'structured filters' (mapping to the filters parameter) and 'bounded' (mapping to limit), but it fails to explain the essential mode parameter (keyword, query, prefix, etc.), the query format, or the semantics of returnColumns and snippet. The description adds only minimal meaning over the raw schema.

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

Purpose4/5

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

The description clearly states the tool performs a PGroonga search with structured filters and bounded results. It names the specific operation (search) and resource (PGroonga), which is sufficient to distinguish it from most siblings like server info, list indexes, and normalization tools. However, it does not differentiate from pgroonga_explain_search, which also relates to search.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives such as pgroonga_explain_search. There is no mention of suitable use cases, exclusions, or prerequisites. The description offers no context about when this search is preferred over other sibling tools.

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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