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michelgrolet

people-memory-mcp

by michelgrolet

read_query

Run a guarded SELECT query for advanced graph analysis on your people memory data. Execute read-only queries to explore connections and relationships without modifying or altering any stored information in PostgreSQL.

Instructions

Run one guarded SELECT for advanced graph analysis. No DDL or data changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_rowsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. 'No DDL or data changes' usefully discloses non-mutating behavior, and 'guarded' suggests protective limits. However, it doesn't elaborate on what 'guarded' entails (e.g., execution timeout, forbidden clauses, automatic row limits), what happens on violations, or how results are returned. It adds some value beyond what the schema provides but lacks depth.

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?

Two sentences, no filler. The description is efficiently front-loaded with the core purpose followed by the safety disclaimer. Every word earns its place, though the brevity leaves behavioral detail unaddressed.

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

Completeness3/5

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

The tool is a free-form query executor (high complexity in terms of what the agent might write), with no annotations and 0% schema description coverage. While output_schema exists (helps with return understanding), the description leaves significant unknowns: query language, 'guarded' semantics, max_rows behavior, and error handling. Given the complexity, the description is under-specified, though the presence of an output schema earns it a mid score.

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 the two parameters (query, max_rows). The description mentions 'query' implicitly by 'advanced graph analysis' but provides no guidance on query syntax, language (SQL? Cypher?), or how max_rows is enforced. With zero schema coverage, the description fails to explain parameter meaning or usage, which is a significant gap.

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 states it runs a 'guarded SELECT' for 'advanced graph analysis', which is a specific verb+resource with a clear scope. It distinguishes from siblings like write_query (clearly the write counterpart). However, it doesn't name the specific alternative or elaborate enough to fully disambiguate from other query-related 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 read-only usage ('No DDL or data changes') and mentions 'guarded', giving some context. However, it does not explicitly state when to use this vs alternatives, nor does it specify the exact safety constraints of 'guarded' (e.g., is there a timeout? a row cap enforced automatically? a read replica?). The guidance is implied but not fully explicit.

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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