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CONTEXT/1.2 Workspace

Deterministic capsule format for Flagship agents: a shared language between the Reasoning Core, Memory Brain, and Tooling Mesh.

CI - Golden Suite Spec - CTX/1.2

Goal. Guarantee that every .context capsule conforms to the specification and passes the golden suite before entering Modular Intellegence Systems production pipelines.

Repository Map

Path Purpose
docs/context_spec_1_2.md Authoritative CONTEXT/1.2 specification with CTX-CANON/3 annexes.
docs/testing.md Guide for running and extending the golden suites.
.agents/tools/ctx_lint.py Reference parser/linter used across all validations.
tests/context/ Positive and negative .context scenarios.
tests/outcomes/ Expected outputs for the golden suite.
.github/workflows/goldens.yml CI workflow that executes the full golden suite on every push/PR.

Quickstart

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt  # ensure python>=3.11 if the file is absent
python tests/run_goldens.py

The command must exit with status 0. Any divergence between actual and expected output marks a regression and blocks merge.

Golden Suite and CI

  • goldens.yml runs on every push and pull request.
  • Always run python tests/run_goldens.py locally before publishing commits.
  • Specification changes must ship with updated golden cases and documentation.

Adding New Scenarios

  1. Create a .context capsule in tests/context/ with a descriptive name.
  2. Execute python tests/run_goldens.py to produce the digest or error metadata.
  3. Store the expected output under tests/outcomes/<name>.json.
  4. Update docs/context_spec_1_2.md and docs/testing.md if behavior changed.
  5. Open a pull request with the execution trace, references to ADRs when relevant, and proof of a green CI run.

Status and Next Steps

  • Covered: resolver metadata, chunk payloads, TTL, confidence models, signature rotation and quorum, safe hints, TAB errors, attachment hash mismatch, external relation validation, JSON round-trip placeholder.
  • In progress: pack/unpack flow, tag validation, external descriptors, public registry.
  • Quarterly target: broaden negative scenarios and formalize the converter audit protocol.

Contributing

  • Follow AGENTS.md and the Flagship bar: zero mocks, coverage >=85 percent, cyclomatic complexity <=10.
  • Each pull request includes a design brief plus evidence (test logs, ADR links).
  • Use organization GitHub Discussions for questions and design clarifications.

Support

  • Issues are the preferred channel for requests or improvements.
  • Contact: magraytlinov@gmail.com - core team replies within one business day.
  • Context is pinned on the Modular Intellegence Systems overview as the entry point into the modular ecosystem.