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Glama

Set Data Store Record

set_store_record
Idempotent

Create or overwrite a data store record to seed data flows or correct records. Stores value as-is; wrap scalars in an object.

Instructions

Create or overwrite one record of a data store. value is stored as it is, so wrap a scalar in an object, e.g. {"value": "text"}. Useful for seeding data a flow will read, or correcting a record a flow wrote.

Input Schema

NameRequiredDescriptionDefault
keyYesRecord key; an existing key is overwritten.
valueYesThe value object to store.
store_idYesThe ID of the store.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare idempotentHint=true and destructiveHint=false, and the description is consistent with that (set semantics, overwrite by key). Beyond the annotations it clarifies that overwrite of an existing key is the intended behavior and that the value is stored verbatim, but it says nothing about required permissions, whether a prior value can be recovered, or concurrency behavior.

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 short sentences, front-loaded with the operation, then the parameter gotcha, then use cases. No filler and nothing repeated from the schema verbatim.

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

Completeness4/5

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

Covers purpose, the tricky value format, and when to reach for it; annotations cover the safety profile and there is no output schema to explain. The only gap is how to obtain a valid `store_id` (e.g. via list_stores), which the description never mentions.

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 the baseline would be 3, but the description adds genuine meaning: it explains that `value` is persisted exactly as given and must be an object, with a worked example {"value": "text"} for the scalar case. That resolves the non-obvious wrapping rule the schema's `additionalProperties: {}` leaves ambiguous.

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?

States a specific verb and resource with scope: "Create or overwrite one record of a data store." That distinguishes it implicitly from get_store_records and delete_store_record, but no sibling is named, so an agent must infer the routing rather than being told.

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?

Gives two concrete usage contexts ("seeding data a flow will read" and "correcting a record a flow wrote"), which is real guidance rather than a vague hint. It stops short of explicit exclusions or of pointing at the read/delete counterparts for other cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.