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opendatadiscovery

23 skills 0 estrelas no total GitHub ↗

Skills publicadas

Mostrando 12 de 23

next-batch

0

Autonomous batch driver for the rev-2 agentic-ontology sprint. Picks the next pending theme from state/sprint-themes.yaml, spawns 5 file-analyser subagents in parallel, then 5 reducers in parallel, merges deltas, refreshes coverage, appends the investigator-log entry, commits, pushes to remote, marks the theme done. Designed to be fired by `/loop` overnight without maintainer input.

Dados e Análise #ai por opendatadiscovery

navigate

0

Find where a feature, component, or concept lives in the ODD codebase. Uses the navigation index for O(1) lookups.

Dados e Análise #ai por opendatadiscovery

review

0

Verify a `review-ready` work item (or an entire batch) meets every acceptance criterion and every Quality Bar gate. Reject by default — each check requires cited evidence. Must run in a session distinct from the `/implement` session that produced the item.

Dados e Análise #ai por opendatadiscovery

probe

0

Run the probe-driven validation rounds for the agentic ontology — Type 4 (adversarial — capability-negation / cross-product-fabrication / synonym-swap-with-negation, ≥2 of 3 PASS) and Type 6 (implicit-ADR confirmation — maintainer writes 5 ADRs they know are followed; ≥3 of 5 must surface in implicit-adrs.md top-10). Both rounds are MAINTAINER-AUTHORED; this skill is the protocol mechanics, not th

Dados e Análise #ai por opendatadiscovery

status

0

Show current progress of the audit and implementation system — scanner completion, backlog counts, blockers.

Dados e Análise #ai por opendatadiscovery

test-coverage

0

Run the test-coverage-mapper reducer subagent over the per-node enrichment sidecars + actual test files in the target repo. Verifies sidecar-claimed test files exist; surfaces uncovered behaviours as TEST-GAP-NNN candidates ranked by node criticality (anchored on concepts.yaml's security/performance aggregates); cross-references with `doc-gaps.md` for double-jeopardy findings (undocumented AND unt

Segurança #ai #test por opendatadiscovery

log-issue

0

Draft an upstream-repo GitHub issue on disk. Creates the next ISS file under issues/{repo}/ with paste-ready frontmatter + body skeleton. The actual filing into GitHub is a deliberate human action — this skill never opens a real issue.

Dados e Análise #ai #git por opendatadiscovery

implement

0

Work a batch of backlog items end-to-end as a maintainer — hold the Implementation Quality Bar, run the Pre-authoring stance check, log follow-ups on disk, flip items to `review-ready`, and ship one PR per repo per batch.

Dados e Análise #ai por opendatadiscovery

panel

0

Run the methodology meta-review — a single methodology-reviewer agent that traces the whole current methodology (APPROACH.md, the ADRs, the agent contracts, the skills, the playbooks, the case-law, the live artefacts), diffs against the prior review, runs fresh blind spot-checks against real source, and emits real gaps + improvement proposals at lineage/{repo}/meta-reviews/{date}/review.md. `/pane

Dados e Análise #ai por opendatadiscovery

concepts

0

Run the concept-merger reducer subagent over the per-node enrichment sidecars to produce or refresh `lineage/{repo}/concepts.yaml` — the deduplicated concept catalog with cross-axis equivalences and canonicalisation candidates. Anchored on `documentation/docs/main-concepts.md` for the canonical vocabulary. Maintainer-curated entries preserved across refreshes.

Escrita e Conteúdo #ai por opendatadiscovery

probe-define

0

Generate probe-skeleton YAML files at `lineage/{repo}/probes/{P-NNN}.yaml` from `feature-flows.yaml`'s uncovered test-matrix cells. Each skeleton carries the feature_id + test_class + cross-references + a TODO-marked arrange/act/observe/assert block the maintainer fills in. Accelerates probe corpus growth — slice 4 of dynamic-verification ADR. Local-only per APPROACH.md section 5 rule 12.

Dados e Análise #ai #test por opendatadiscovery

ingest-docs

0

Ingest the live documentation manual into the ontology as ground-truth Doc nodes, then enrich them with doc→ontology DESCRIBES links. Runs the mechanical doc extractor (docs-ingest → doc-nodes.jsonl, split by heading/anchor, prose referenced from ../documentation), rebuilds the graph (embeds the doc prose), spawns the doc-analyser subagent per un-enriched page (live-URL verification + DESCRIBES to

Escrita e Conteúdo #ai por opendatadiscovery