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get_cognito_overview

Retrieve Cognito user pool and app client configs including MFA, auth flows, OAuth scopes, callbacks, token validity, and client secret flag to ensure correct auth implementation. Secrets and user data are never exposed.

Instructions

Returns all Cognito user pools with MFA configuration and every app client config: allowed auth flows, OAuth flows/scopes, callback URLs, token validity, and whether the client has a secret (SDK auth calls must send SECRET_HASH when true). Client secret values are never returned. Call this before writing any Cognito sign-in, sign-up, or token-refresh code to use the correct auth flow and client settings. Do NOT call to look up users or tokens — infrawise never reads user data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxAgeSecondsNoFreshness tolerance in seconds. Advisory: the answer is returned either way, with dataHealth.withinRequestedAge reporting whether it met the tolerance. Nothing re-reads AWS on a tool call — run `infrawise analyze` to refresh. Pass a small value for point-in-time questions ("does this queue have a DLQ right now"); omit it for architecture questions where a day-old snapshot is fine.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that 'Client secret values are never returned,' that SDK auth calls must send SECRET_HASH when the client has a secret, and that infrawise never reads user data. These are meaningful behavioral disclosures beyond the basic read operation, though it does not cover every edge case (e.g., pagination).

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 four sentences, each earning its place. It front-loads the primary output, then exclusions, then usage directives. No wordy or redundant statements; it packs significant detail efficiently.

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?

Despite having no output schema, the description covers the tool's return content, security constraints (secrets never returned), usage context, and data-freshness behavior (via schema). It is sufficiently complete for the tool's purpose, though return structure is not specified.

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

Parameters3/5

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

The single parameter maxAgeSeconds is fully described in the input schema with detailed guidance on freshness tolerance and when to omit it. The tool description itself adds no additional parameter semantics. With 100% schema coverage, the baseline of 3 applies.

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 states a specific verb and resource: 'Returns all Cognito user pools with MFA configuration and every app client config' and lists concrete fields (auth flows, OAuth flows/scopes, callback URLs, token validity, client secret presence). This clearly distinguishes it from sibling overview tools like get_lambda_overview or get_s3_overview.

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?

Provides explicit when-to-use: 'Call this before writing any Cognito sign-in, sign-up, or token-refresh code' and when-not-to-use: 'Do NOT call to look up users or tokens — infrawise never reads user data.' This gives clear directives without naming alternatives but effectively scopes usage.

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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