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infrawise

infrawise

by Sidd27
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TypeScript
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EventBridge rule details

get_eventbridge_details
Read-only

Retrieve EventBridge rule details including state, schedule or event pattern, and target Lambda. Use it to check what triggers a function or review rule coverage.

Instructions

Returns all EventBridge rules with name, ENABLED/DISABLED state, schedule expression (rate/cron rules), event pattern (event-driven rules), and target Lambda function names. Call this when checking what schedule or event triggers a Lambda, or when reviewing rule coverage across the account.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_eventbridge_details"
  }
}

Input 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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.26.1
    • changedInput schema / properties / maxAgeSeconds / description
      Previous value: -"Refuse to answer from an analysis older than this many seconds. Use 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."New value: +"Freshness 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."
  2. Changed1 schema field changedv0.25.1
    • addedInput schema / properties / maxAgeSeconds
      Added value: +{
+  "description": "Refuse to answer from an analysis older than this many seconds. Use 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.",
+  "type": "number"
+}
  3. Addedv0.21.0
  4. Removedv0.19.7
  5. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered without description support. The description adds value by disclosing the shape of the returned data (states, expressions, patterns, targets), but says nothing about auth requirements, rate limits, or freshness. With annotations carrying the safety profile, a 3 is appropriate.

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?

Two sentences, both front-loaded: the return contents first, then the usage contexts. Every clause carries concrete information (field names, rule types) and there is no filler or restatement of the tool name.

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?

With no output schema, the description correctly compensates by enumerating the returned fields, which is exactly what an agent needs to interpret results. Only one optional parameter exists and annotations cover the safety profile. The only minor omission is that the snapshot/staleness model lives solely in the schema, not the description.

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?

There is a single optional parameter (maxAgeSeconds) and schema description coverage is 100%, so the schema fully explains its semantics, including the advisory freshness behavior and dataHealth reporting. The description does not mention it, but per the baseline rule, a 3 is correct when the schema already does the heavy lifting.

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?

States a specific verb (Returns) plus resource (EventBridge rules) and enumerates the exact fields returned: name, ENABLED/DISABLED state, schedule expression, event pattern, and target Lambda names. This clearly distinguishes it from sibling overview tools like get_lambda_overview because it is scoped to EventBridge rules and their triggers.

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?

Explicitly states when to call it: 'when checking what schedule or event triggers a Lambda, or when reviewing rule coverage across the account.' This gives two concrete usage contexts. It does not name a specific alternative tool or an exclusion condition, so it stops short of a 5, but the trigger conditions are clear and actionable.

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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