infrastructure-autoresearch

Solid

Skill for deterministic AutoResearch readiness planning. Use when adding, validating, or documenting opt-in autoresearch.yaml controls, stage-gate readiness, evidence-grounded claims, artifact readiness reports, or AutoResearchClaw-inspired workflow checks in template projects.

DevOps & Infrastructure 18 stars 1 forks Updated today Apache-2.0

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# AutoResearch Readiness Use this module for deterministic planning and readiness validation. It adapts reviewed AutoResearchClaw design ideas as file-backed template controls, not as an autonomous research agent. AutoResearch CLI-style measurement ideas are treated the same way: adopt exact metric extraction, review-status vocabulary, baseline/noise/confidence disclosure, and append-only evidence discipline; do not add lifecycle hooks, git commit/revert ownership, or no-human autonomous loops by default. ## Commands ```bash uv run python -m infrastructure.autoresearch.cli validate --project templates/template_code_project --fail-on-issues ``` ## Public API ```python from infrastructure.autoresearch import ( AutoResearchConfig, AutoResearchIssue, AutoResearchPlan, AutoResearchReport, mad_confidence, metric_unit_from_name, build_autoresearch_plan, load_autoresearch_config, parse_metric_lines, parse_string_sequence, validate_autoresearch_plan, write_autoresearch_report, ) ``` `validate_autoresearch_plan(..., phase="intrinsic"|"extrinsic"|"all")` splits pre-write structure checks from post-write artifact checks. ## Configuration Project-local `autoresearch.yaml` supports: - `enabled` - `strict` - `topic` - `quality_checks` - `stage_gates` - `required_artifacts` - `security_profile` (mapping: `enabled`, `mode`, `integrity_algorithm`, `network_policy`, `external_signing`, `threat_model_frameworks`) - `source_manifests` (l...

Details

Author
docxology
Repository
docxology/template
Created
11 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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