adaptive-sensor-testing/MANIFEST.toml at main · adaptive-interfaces/adaptive-sensor-testing · GitHub

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# ============================================================
# adaptive-sensor-testing/MANIFEST.toml
# ============================================================

schema = "adaptive-interfaces-manifest-1"
schema_url = "https://github.com/adaptive-interfaces/.github/blob/main/schemas/adaptive-interfaces-manifest-1.md"

[meta]
framework = "Adaptive Interfaces"
framework_url = "https://github.com/adaptive-interfaces"
framework_note = "Provides definitions and conventions for adaptive-interfaces manifest semantics."
description = "Declarative claim of repository intent, scope, and role."
purpose = "To make explicit the boundaries, responsibilities, and expectations of this repository relative to others."

[repo]
name = "adaptive-sensor-testing"
kind = "worked-example"
description = "Complete worked example: a simulated PTAT sensor data codebase used to demonstrate agent test generation and anomaly detection using all three priors (ACS, ATD, AO) plus domain context."

[layer]
space = "Agent Engineering"
role = "worked-example"

[depends]
required = [
  "adaptive-conformance-specification",
  "adaptive-tool-discovery",
  "adaptive-onboarding",
  "python>=3.14",
  "uv",
]
optional = [
  "pytest",
  "ruff",
  "pyright",
]

[provides]
artifacts = [
  "SKILL.md",
  "MANIFEST.toml",
  "DECISIONS.md",
  "CITATION.cff",
  "LICENSE",
  "README.md",
  "src/sensor_sim/",
  "tests/",
  "data/sample_batch.csv",
  ".agent/ao-config.toml",
  ".agent/ao-config-python.toml",
  ".agent/ao-domain.toml",
  "tools/sensor-api.toml",
  "evaluation/rubric.md",
  "evaluation/scenarios/",
]

[scope]
includes = [
  "synthetic PTAT sensor data generator with injected anomalies",
  "sensor data processing functions for agent test generation",
  "partial test suite demonstrating team test conventions",
  "ao-domain.toml capturing PTAT behavior, expected ranges, anomaly definitions",
  "ATD registry for the sensor data tool surface",
  "evaluation scenarios: basic, drift detection, multi-sensor",
  "rubric for evaluating agent test generation and anomaly reporting",
]
excludes = [
  "production sensor hardware or firmware",
  "proprietary sensor processing pipelines",
  "real sensor data",
  "claims of physical accuracy beyond illustrative simulation",
  "model training or fine-tuning",
]

[citation]
cff = "CITATION.cff"
preferred = "repo"

[traceability]
identifier_map = "none"