Metadata-Version: 2.4
Name: betamatter
Version: 0.1.0
Summary: Augmented reality for LLM agents: YAML frontmatter, content fencing, and fire-once tips for MCP tool responses.
Author: blightbow
License-Expression: MIT
License-File: LICENSE
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.12
Project-URL: Homepage, https://github.com/blightbow/betamatter
Project-URL: Repository, https://github.com/blightbow/betamatter
Project-URL: Issues, https://github.com/blightbow/betamatter/issues
Description-Content-Type: text/markdown

# betamatter

*Structured beta for the agent driving the tools.*

betamatter is the YAML-frontmatter layer for MCP tool responses whose user
is the LLM. Every tool response has two channels — the body (the answer)
and the frontmatter (a trusted sidechannel *about* the answer) — and this
library owns the mechanics that keep that line honest: an entries container
(`FMEntries`) that guards multi-contributor guidance keys against silent
clobbering, the sole sanctioned `---` block builder (`build_frontmatter`),
a box-drawing datamark fence for untrusted content (`fence_content`), and a
fire-once tip ledger (`TipLedger`) for once-per-process educational
guidance. Extracted from [parkour-mcp](https://github.com/blightbow/parkour-mcp),
whose frontmatter discipline it generalizes; consuming projects declare
their own trust polarity, field vocabulary, and tip registry as deltas.

The conventions themselves — handles/shape/steering, phrasing doctrine,
trust rules, tip semantics — are specified in
[docs/standard.md](docs/standard.md).
