testing-provenance-ontology

Validates telic seam provenance and ontology schema changes with targeted pytest workflows.

Updated Aug 5, 2026
One-click install
npx skills add https://github.com/AmitabhainArunachala/dharma_swarmv.01 --skill testing-provenance-ontology-amitabhainarunachala
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: testing-provenance-ontology
Source: https://github.com/AmitabhainArunachala/dharma_swarmv.01/tree/main/.agents/skills/testing-provenance
Command: npx skills add https://github.com/AmitabhainArunachala/dharma_swarmv.01 --skill testing-provenance-ontology-amitabhainarunachala

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Changes to the telic seam and ontology surface can fail silently: OntologyRegistry.create_object() returns (None, [errors]) instead of raising, so a broken schema looks green unless you assert on the created object. This Skill provides a disciplined test procedure that proves provenance actually persists rather than merely verifying that code imports. ## Core Features & Use Cases - Targeted Test Workflow: Runs focused pytest suites for telic_seam.py, task_board.py, and telos_graph.py before a full-suite regression sweep diffed against a same-session baseline. - Ontology Enum Round-Trip Validation: Enforces updating both the code-level whitelist and the ontology schema enum, with an explicit assertion that create_object() does not return None. - Adversarial Test Patterns: Provides fixture construction rules and adversarial patterns (topology round-trip, orphan proposal, method existence) to catch silent fallback behavior. - Use Case: After adding a new action_type enum value to ActionProposal, use this Skill to verify the dispatch is stored with the new value rather than the silent fallback "dispatch", and produce a structured PASS/FAIL verdict block. ## Quick Start Verify my changes to telic_seam.py and ontology.py by running the targeted provenance tests and the enum round-trip check, then give me the verdict block.

Frequently Asked Questions about testing-provenance-ontology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I test ontology schema enum changes in Python?▼

Update both the code-level whitelist and the ontology schema enum in ontology.py, then call OntologyRegistry.create_object() with the new value and assert the returned object is not None. A schema mismatch returns (None, [errors]) silently instead of raising.

How do I verify a dispatch records provenance correctly?▼

Record a dispatch with the new topology value, then read the stored action_type property back off the ontology object and assert it equals the new value. Do not treat record_dispatch returning without exception as success, since it can silently fall back to "dispatch".

Why does create_object return None instead of raising an error?▼

OntologyRegistry.create_object() returns a tuple of (None, [error_list]) when schema validation fails, such as when an enum value is missing from the PropertyDef enum_values. Callers like record_dispatch swallow the None, so you must assert on the created object explicitly.

How should I construct TelicSeam in pytest fixtures?▼

Build a real OntologyRegistry via create_dharma_registry() and a LineageGraph backed by pytest's tmp_path, then pass them to TelicSeam(registry=..., lineage=...). Avoid the path-based constructor, which may not register all required ontology types, and never share a /tmp database across parallel runs.

How do I compare test failures against a baseline correctly?▼

Run the full pytest suite on your change, then diff against a same-session baseline from git stash or a clean main checkout. Never compare against remembered failure counts, since pre-existing-failure tallies rot over time.