list_store_makers
[Requires Pro+ plan] List all makers (citizen developers / AAD users) from the Power Clarity cache.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
[Requires Pro+ plan] List all makers (citizen developers / AAD users) from the Power Clarity cache.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and non-destructive behavior, so the description adds value by disclosing the Pro+ plan requirement and the cache-based source, which implies the data may reflect cached state. It does not repeat the annotation flags, avoiding redundancy.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the plan requirement, then gives the resource, action, and context. Every word adds meaning; there is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only list operation, the description gives sufficient context: the resource, scope, source, and access requirement. No output schema is provided, but the phrase 'List all makers' inherently conveys the return value as a collection of makers.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters and schema coverage is complete, so there is no missing parameter documentation. The description still adds slight semantic value by clarifying what entity a 'maker' is (citizen developers / AAD users), but no parameter-specific meaning is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('List'), a clear resource ('makers'), and scope ('all'), while clarifying that makers are citizen developers/AAD users. It also identifies the data source (Power Clarity cache), making the tool easily distinguishable from siblings like get_store_maker.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys the invocation context via 'Requires Pro+ plan' and the collection-scoped word 'all', but it does not explicitly contrast this with get_store_maker for single-maker retrieval or any other sibling. Usage is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The consistent live/store prefixes and clear resource nouns make most tools distinguishable, and deprecated tools explicitly flag replacements. However, the duplicated live-vs-cache surfaces and multiple run/error-history tools can still require careful reading to choose correctly.
All tools follow a consistent snake_case verb_noun pattern with stable qualifiers like live, store, flow, and run. Even meta-tools like list_skills and tool_search fit the same convention, and the few longer names such as add_live_flow_to_solution remain predictable.
34 tools is well above the 25+ threshold for 'too many,' and the set is inflated by live/store duplication plus four deprecated tools scheduled for removal. Several tools could be consolidated or dropped without losing capability.
The server covers the main flow lifecycle well: list/get/create/update, state changes, running, resubmission, run diagnostics, environments, connections, and solution migration. Notable gaps include no delete flow, no remove-from-solution operation, and read-only connection management, which agents can partially work around.