plugins/sdlc/skills/grade-on-ingest/SKILL.md
Trigger GRADE quality assessment automatically when new research sources or findings enter the corpus
npx skillsauth add jmagly/aiwg grade-on-ingestInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Automatically triggers GRADE quality assessment when new research sources or findings are added to the corpus.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
Ensures every research source entering the corpus receives a GRADE quality assessment at ingestion time, preventing unassessed sources from being cited without quality context. Implements the "assess at entry" pattern to maintain corpus-wide quality visibility.
This skill activates when:
.aiwg/research/sources/ or .aiwg/research/findings/REF-*.md, *.pdf added to research directories.aiwg/research/quality-assessments/ (already an assessment)INDEX.md or README.md*.yaml in schemas/)When a new research source is detected:
Extract metadata
ref_id, title, authors, year, source_typeDetermine baseline quality
peer_reviewed_journal -> HIGHpeer_reviewed_conference -> HIGHpreprint -> MODERATEtechnical_report -> MODERATEindustry_whitepaper -> LOWblog_post -> VERY LOWforum_discussion -> VERY LOWInvoke Quality Assessor
Store assessment
.aiwg/research/quality-assessments/{ref-id}-assessment.yamlgrade_level field (if --update-frontmatter)Update corpus index
Report
After assessment completes, Citation Guard uses the GRADE level to enforce hedging:
integration:
citation_guard:
action: update_grade_cache
data: new_assessment
Assessment populates fields required by research metadata rules:
integration:
research_metadata:
fields_populated:
- quality_assessment.grade_level
- quality_assessment.baseline
- quality_assessment.downgrade_factors
- quality_assessment.upgrade_factors
Assessment activity recorded in provenance chain:
integration:
provenance:
activity_type: quality_assessment
agent: quality-assessor
skill:
name: grade-on-ingest
type: passive
always_active_for:
- quality-assessor
- technical-researcher
- citation-verifier
file_triggers:
- pattern: ".aiwg/research/sources/REF-*.md"
- pattern: ".aiwg/research/findings/REF-*.md"
auto_assess: true
update_frontmatter: false # Requires --update-frontmatter flag
notify_on_low_quality: true
block_on_missing_frontmatter: false
.aiwg/research/quality-assessments/{ref-id}-assessment.yaml--update-frontmatter).aiwg/research/quality-assessments/INDEX.mddata-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.