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DPA Article 28 Completeness Checker

check_dpa_gdpr_art28
Read-onlyIdempotent

DPA Article 28 Completeness Checker: 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. Open at: https://ainumbers.co/chaingraph/art-409-dpa-art28-completeness-checker.html FV-status (published/proven/still-trusted for this spec): /fv-status/8b5ae30d812cd234cfb6068c4ce2022f01d10f2a358979b0f0d73421e09d2543.json — a snapshot, not a subscription; this receipt verifies offline regardless of whether that file is ever fetched.

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.

TDQS

A3.9/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses deterministic execution, transient non-retention of inputs, server-versus-browser delegation behavior, and the AP2 artifact with execution_hash. This is substantial behavioral context that helps an agent anticipate side effects and privacy implications.

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 description is front-loaded with purpose and includes useful operational detail, but it repeats 'OpenChainGraph compute node' and 'deterministic' in consecutive sentences. The URL and FV-status receipt add provenance context, though they could be trimmed without losing core invocation guidance.

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?

The description covers execution modes, input privacy, output artifact, and a reference URL, which is fairly complete given the annotations and schema. However, without an output schema, it does not explain what the completeness-check result contains, and policy_parameters is left to an external manifest.

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?

Input schema coverage is 100%, so the structured schema already documents all four parameters. The description mostly restates the compute-mode semantics already present in the schema and does not clarify policy_parameters field names, deferring those to an external manifest.

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

Purpose4/5

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

The description opens with 'DPA Article 28 Completeness Checker' and identifies the tool as an OpenChainGraph compute node, so an agent can recognize it as a completeness check for DPA Article 28. It does not explicitly contrast itself with sibling checkers, but the domain-specific title and compute-node framing provide enough distinction.

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 gives concrete mode-selection guidance: 'auto' runs server-side on Cloudflare Workers, 'browser' forces a delegation URL, and gpu:true nodes always delegate. It also instructs users to input synthetic or anonymised data only. It does not name alternatives or exclusions relative to sibling tools, but the usage context is clear.

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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TDQS

C2.4/5.0
Disambiguation1/5

Nearly every tool is an 'OpenChainGraph compute node' with identical boilerplate, and dozens of assess/check/validate/verify/lint/recompute verbs overlap heavily in purpose. An agent cannot reliably tell which of many similarly scoped tools should handle a given compliance or analytics question.

Naming Consistency2/5

Most names are snake_case, so there is superficial consistency, but the verb vocabulary is enormous and unpredictable, mixing build/compute/check/validate/verify/lint/assess/classify/score/reconcile and more. Several noun-first names such as pain001_validate, recon_match, and ha_record_validate further break the pattern.

Tool Count1/5

695 tools is far beyond any practical agent-facing surface, exceeding even the extreme end of the calibration range. This is a full product catalog dumped into one MCP server rather than a curated, usable tool set.

Completeness3/5

The suite covers an extremely wide range of fintech and regulatory calculators, validators, chain tools, and discovery utilities, so coverage is broad rather than thin. However, the lack of a clear domain boundary makes completeness nearly impossible to assess, and the heavy overlap suggests the surface was generated rather than intentionally designed.

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