SpecAnchor, a tool designed to provide spec governance and an anti-decay layer for AI coding agents, has launched its v0.5.0-beta.1 release. This update redefines SpecAnchor as a "Harness Context Control plane," expanding its capabilities beyond just managing Spec Context to also include Decision and Evidence contexts.
The core motivation behind this release is to tackle the challenges associated with LLM context management, such as the degradation of long contexts and the loss of precision due to automatic compaction. Previously, SpecAnchor focused on organizing 'Spec Context' (Global, Module, Task contracts). However, human input during checkpoints often involves adding to specifications or clarifying existing ones, which was not persistently captured.
With v0.5.0-beta.1, SpecAnchor now makes these crucial signals persistent:
* **Decision Context**: Checkpoint decisions are logged into Task Spec §5.2, including their status (active, superseded, withdrawn) and a pin flag. A hot/cold view automatically prunes decisions that are no longer relevant. * **Evidence Context**: Verification proofs are recorded in Task Spec §6.2, encompassing commands run, acceptance criteria mapping, unverified risks, manual checks, and rollback handles. Acceptance criteria are auto-pinned, and failed or unverified-risk entries remain 'hot'.
This release introduces a new schema (`sdd-riper-one` v2) with six new sections in the Task Spec template, along with enhanced configuration options in `anchor.yaml` for managing context control. New scripts (`decision-filter.sh`, `evidence-filter.sh`, `specanchor-doctor.sh`, `specanchor-assemble.sh`) and a new command (`specanchor_handoff`) have been added to support these features. A pre-commit hook is also included to enforce context-control linting.
Migration guidance is provided for existing projects, recommending either appending placeholder sections to legacy task specs or adjusting enforcement levels in `anchor.yaml` to avoid blocking the doctor linting process.