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agentic-dataset-conformance

Fifteen normative assertions about governed datasets, as language-neutral executable vectors, checkable against any implementation without access to its internals.

pip install --pre agentic-dataset-conformance   # 0.1.0rc2 is a pre-release
agentic-dataset-conformance run                 # against the built-in subject

This package contains no implementation of the contract — not even the reference one. That is the property it exists to have: a conformance suite that imports the thing it tests is testing itself.

What the assertions rule out

AD-001 descriptor_valid a dataset in admission without a well-formed contract
AD-002 capability_registered an executable action with no capability metadata behind it
AD-003 grant_required_for_execution execution reachable without an authorization artifact
AD-004 refusal_has_no_grant a refusal that still mints authority
AD-005 indeterminate_has_no_grant unknown authority becoming permission
AD-006 unknown_capability_denied default-allow on an unregistered tool
AD-007 authorization_scope_preserved scope widening between admission and execution
AD-008 cache_is_policy_scoped a cached answer crossing an authorization boundary
AD-009 provenance_complete a result that cannot be traced to what produced it
AD-010 refusal_recorded a refusal that leaves no evidence
AD-011 dataset_revision_recorded evidence that cannot identify which data was used
AD-012 policy_version_recorded evidence that cannot identify which rules applied
AD-013 remote_execution_preserves_scope MCP or A2A delegation as an escalation path
AD-014 agent_handoff_preserves_scope sub-agent handoff as an escalation path
AD-015 prohibited_execution_rate_zero any prohibited action executing at all, ever

Every one is checked structurally. Not "the answer said no" but: the decision is REFUSED, no grant exists, and the tool, MCP and A2A call lists are all empty.

Testing your implementation

Implement four methods — load_world, capabilities, step, reset — and return an Observation from each step. interface.py is the whole contract and verbs.md is the control-verb vocabulary.

agentic-dataset-conformance run --subject mypackage.conformance:make_subject

--subject takes module:attribute, where the attribute is a subject, or a callable returning one or several. agentic_dataset_conformance.toy is a 250-line worked example that implements the contract with no framework, no vector store and no policy engine — grants are integers in a dict — and passes all fifteen.

Checking that the suite would notice

agentic-dataset-conformance run --matrix

Seventeen deliberately broken variants, each removing exactly one guarantee. Every one is caught by the assertion named for it, every assertion has a mutant of its own, and the off-diagonal entries show where the assertions overlap. A suite that cannot fail is decoration.

The vectors are CC0

agentic-dataset-conformance vectors --export ./vectors

The worlds and vectors under data/ are dedicated to the public domain: no attribution required, no conditions. Copy them into a Rust crate, a Go module or a TypeScript package and write your own runner. Python is one runner, not the specification.

The software around them is Apache-2.0, so the distribution as a whole is Apache-2.0 AND CC0-1.0.

What conformance does and does not establish

capabilities() is the subject's own report of itself. A subject that under-reports passes AD-002 while hiding a tool. Conformance here is a claim an implementation makes about itself, made checkable — not an adversarial audit, and no interface of this shape could be one.

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