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FaultKey · CausalLayer

by io.github.smq9sn5jck-cloud
OverviewDiscussionsAdmin

submit_incident

Submit an AI incident for deterministic causal liability attribution. Returns a signed CausalCertificate, per-agent liability allocation, evidence-chain completeness, regulatory mapping, and (where keys are configured) a Bitcoin-anchored proof. Cost: 50 credits. Three guardrails apply: PII scan, deterministic-only acknowledgement, and minimum evidence.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "title": "<title>",
      "agents": "<agents>",
      "events": "<events>",
      "deterministic_only": "<deterministic_only>"
    },
    "name": "submit_incident"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYes
agentsYes
eventsYes
categoryNo
currencyNo
severityNo
descriptionNo
jurisdictionNo
pii_acknowledgedNoG1: Set to true ONLY if caller has confirmed PII handling is permitted by their data agreement. False payloads with detected PII will be rejected.
deterministic_onlyYesG2: Must be true. Acknowledges CausalLayer is deterministic and not LLM-based.
financial_impact_centsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / agents / items / additionalProperties
      Removed value: -false
    • removedInput schema / properties / events / items / additionalProperties
      Removed value: -false
    • changedInput schema / properties / financial_impact_cents / anyOf
      Previous value: -[
-  {
-    "minimum": 0,
-    "type": "integer"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maximum": 9007199254740991,
+    "minimum": 0,
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
  2. Changed3 schema fields changed
    • addedInput schema / properties / events / items / properties / span_id
      Added value: +{
+  "pattern": "^[0-9a-f]{16}$",
+  "type": "string"
+}
    • addedInput schema / properties / events / items / properties / trace_id
      Added value: +{
+  "pattern": "^[0-9a-f]{32}$",
+  "type": "string"
+}
    • addedInput schema / properties / events / items / properties / trace_source
      Added value: +{
+  "enum": [
+    "opentelemetry",
+    "jaeger",
+    "zipkin",
+    "datadog",
+    "newrelic",
+    "other"
+  ],
+  "type": "string"
+}
  3. Changed4 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / agents / items / additionalProperties
      Added value: +false
    • addedInput schema / properties / events / items / additionalProperties
      Added value: +false
    • changedInput schema / properties / financial_impact_cents / anyOf
      Previous value: -[
-  {
-    "maximum": 9007199254740991,
-    "minimum": 0,
-    "type": "integer"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "minimum": 0,
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
  4. Changed4 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / agents / items / additionalProperties
      Removed value: -false
    • removedInput schema / properties / events / items / additionalProperties
      Removed value: -false
    • changedInput schema / properties / financial_impact_cents / anyOf
      Previous value: -[
-  {
-    "minimum": 0,
-    "type": "integer"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maximum": 9007199254740991,
+    "minimum": 0,
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
  5. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly lists the return values (signed CausalCertificate, liability allocation, evidence-chain completeness, regulatory mapping, Bitcoin proof) and discloses the cost and guardrails. This is a solid amount of transparency, though it does not explain failure modes or exact evidence thresholds, which would push it to a 5.

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 three sentences long and front-loaded with the main purpose. Each sentence adds critical information: purpose, return values, cost, and guardrails. There is no fluff or repetition, making it concise and well-structured.

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?

The description provides a comprehensive overview of what the tool does, what it returns, its cost, and its guardrails. For a complex submission tool with 11 parameters and no output schema, this is reasonably complete. However, it does not elaborate on the 'minimum evidence' requirement or error handling, leaving some gaps for an agent trying to use the tool confidently.

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 only 18% (2 out of 11 parameters have descriptions). The description mentions guardrails that map to `pii_acknowledged` and `deterministic_only`, but it does not explain the meaning or purpose of other parameters such as `agents`, `events`, `severity`, or `jurisdiction`. The description does not compensate for the low schema coverage, leaving many parameters underspecified.

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 starts with a specific verb and resource: 'Submit an AI incident for deterministic causal liability attribution.' This clearly identifies the tool's primary function and distinguishes it from siblings like submit_otel_trace (which submits telemetry) and evaluate_prospective_response (which evaluates responses). The purpose is unambiguous and the resource is well-defined.

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?

The description provides clear context on when to use this tool: to submit an AI incident for liability attribution. It also mentions cost (50 credits) and three guardrails (PII scan, deterministic-only acknowledgement, minimum evidence), which help the agent understand prerequisites and constraints. However, it does not explicitly mention alternatives or exclusions, so it falls short of a 5.

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

All FaultKey · CausalLayer toolsInspect
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