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AIUC-1 Control Evidence Linter

lint_aiuc1_control_evidence
Read-onlyIdempotent

AIUC-1 Control Evidence Linter: OpenChainGraph compute node (compliance_mandate). Deterministic OpenChainGraph compute node. By default (compute:"auto") inputs are computed server-side on Cloudflare Workers for gpu:false nodes with a registered kernel; compute:"browser" forces client-side execution and returns a browser delegation URL instead. gpu:true nodes always delegate to the browser. Inputs are processed transiently to compute the response and are not stored, logged, or retained. Use synthetic or anonymised inputs only. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: art-304-aiuc1-evidence-pack-assembler. Open at: https://ainumbers.co/chaingraph/art-303-aiuc1-control-evidence-linter.html FV-status (published/proven/still-trusted for this spec): /fv-status/8498d0819c941fdb731f9e10f5d93ee929026919cb111a42149821b48b5ac180.json — a snapshot, not a subscription; this receipt verifies offline regardless of whether that file is ever fetched. Output schema: call describe_tool("lint_aiuc1_control_evidence").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
computeNoCompute mode (v0.4 Compute Binding). "auto" (default) = server for gpu:false nodes with registered kernels; "server" = force server-side; "browser" = always return browser delegation URL. gpu:true nodes always delegate.
parent_hashesNoexecution_hash values from upstream ChainGraph AP2 artifacts to chain from (sets chain.parent_hashes in the export).
parent_tool_idsNotool_id values matching parent_hashes, in the same order.
policy_parametersNoInput parameters for this tool's decision function. For gpu:false nodes with a registered kernel, these are computed server-side when compute is "auto" or "server". See the tool's manifest for field names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "aiuc1_version": {
-      "type": "string"
-    },
-    "attestation_only_count": {
-      "type": "integer"
-    },
-    "automatable_scope": {
-      "type": "integer"
-    },
-    "insufficient_evidence": {
-      "type": "boolean"
-    },
-    "missing_count": {
-      "type": "integer"
-    },
-    "overall_coverage": {
-      "type": "integer"
-    },
-    "per_control": {
-      "items": {
-        "properties": {
-          "control_id": {
-            "type": "string"
-          },
-          "pillar": {
-            "type": "string"
-          },
-          "status": {
-            "type": "string"
-          }
-        },
-        "type": "object"
-      },
-      "type": "array"
-    },
-    "per_pillar_coverage": {
-      "properties": {
-        "A": {
-          "type": "integer"
-        },
-        "B": {
-          "type": "integer"
-        },
-        "C": {
-          "type": "integer"
-        },
-        "D": {
-          "type": "integer"
-        },
-        "E": {
-          "type": "integer"
-        },
-        "F": {
-          "type": "integer"
-        }
-      },
-      "type": "object"
-    },
-    "procedural_controls_out_of_scope": {
-      "type": "integer"
-    },
-    "receipt_backed_count": {
-      "type": "integer"
-    },
-    "version_mismatch": {
-      "type": "boolean"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "aiuc1_version": {
+      "type": "string"
+    },
+    "attestation_only_count": {
+      "type": "integer"
+    },
+    "automatable_scope": {
+      "type": "integer"
+    },
+    "insufficient_evidence": {
+      "type": "boolean"
+    },
+    "missing_count": {
+      "type": "integer"
+    },
+    "overall_coverage": {
+      "type": "integer"
+    },
+    "per_control": {
+      "items": {
+        "properties": {
+          "control_id": {
+            "type": "string"
+          },
+          "pillar": {
+            "type": "string"
+          },
+          "status": {
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "per_pillar_coverage": {
+      "properties": {
+        "A": {
+          "type": "integer"
+        },
+        "B": {
+          "type": "integer"
+        },
+        "C": {
+          "type": "integer"
+        },
+        "D": {
+          "type": "integer"
+        },
+        "E": {
+          "type": "integer"
+        },
+        "F": {
+          "type": "integer"
+        }
+      },
+      "type": "object"
+    },
+    "procedural_controls_out_of_scope": {
+      "type": "integer"
+    },
+    "receipt_backed_count": {
+      "type": "integer"
+    },
+    "version_mismatch": {
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}
  3. Added

TDQS

B3/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false), but the description adds genuinely new behavior: compute:'auto' vs 'server' vs 'browser' execution, gpu:true nodes always delegating, transient non-stored/non-logged processing, and export of an execution_hash-bearing AP2 artifact. These are traits the annotations do not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single dense paragraph front-loads a generic identifier ('OpenChainGraph compute node') before the useful content, repeats 'deterministic ... compute node', and embeds a long URL and hash string that consume space without helping invocation. Functional but not tight.

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

Completeness3/5

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

For a no-output-schema lint tool it covers execution mode, data handling, artifact export, and downstream consumer, which is reasonable. It omits what a lint result/finding looks like and defers return-shape discovery to describe_tool, leaving a gap an agent would want filled.

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?

Schema description coverage is 100%, so the enum semantics of 'compute', parent_hashes/parent_tool_ids linking, and policy_parameters are already fully documented in the schema. The description restates the compute-mode behavior but adds no syntax or format detail beyond it, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The title and first clause identify it as an 'AIUC-1 Control Evidence Linter' and the description says it exports an AP2 artifact and feeds art-304-aiuc1-evidence-pack-assembler. However, the body is dominated by OpenChainGraph compute-node mechanics rather than stating what the lint actually validates, so the agent must infer the purpose from the name plus the sibling list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to choose this tool over the many sibling linters (lint_ab2013_training_data_disclosure, lint_mcp_tool_definition, etc.). The only usage-like guidance is 'Use synthetic or anonymised inputs only,' which is a data-handling constraint, not a selection rule.

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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