vamseeachanta

Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.

Diagnose and fix a machine whose equivalence-state fingerprint publish is absent, stale, or gate-length slow (the wh#3500 pre-push RUN_ALL deadlock signature). Use when the equality matrix shows PUBLISH-GATED / PUBLISH-STALE / MISSING-EVIDENCE on the publish-health row, or the sentinel reports absent-fingerprint / publish-slow divergences.

Bootstrap a registered private client wiki from the committed generic template.

Build worldenergydata drill-down pages (field hub, well timelines, insight/norm pages) with the proven validate-first playbook, the fractal IA grammar, honesty rules, and the exact wed CI gotchas.

Diagnose and reduce git repository bloat — multi-GB .git, slow git status/fetch/clone caused by large binaries committed to history. Consolidates packs and enables the untracked-cache (always-safe wins), then plans an operator-gated history rewrite that strips only large already-deleted blobs. Use when a repo's .git is multiple GB, git ops are slow, or the user mentions "repo bloat", "shrink/slim .git", "git filter-repo", "repo health", or large binaries in git history. Safe to point at any workspace-hub repo.

Mandatory planning workflow for ALL GitHub issues — plan, review, approve, then implement.

Surface SPECIFIC FILES on the shared drives (/mnt/ace, /mnt/dde) relevant to the current task — the FILE-level complement to ecosystem-data-sources (domain-catalog level). Extracts query terms from work context, runs the drive-index CLI once, presents ranked canonical paths with freshness caveats. Use for similar-past-work, prior-project, or files/examples/precedent asks; when domain work needs past deliverables (mooring calc → xlsx/py; CAD → dwg/step; standards → PDF inventory).

Proactively surface what DATA the ecosystem already has for an engineering domain — before starting analysis, points to the consolidated data-source catalog, any latent ACE_SHARE project precedent, and the domain-database issue that curates it. Use when work touches an engineering domain (riser, mooring, pipeline, structural/FFS, naval-arch/hydro, metocean, materials, production, geotech, drilling, CAD/sim, or financial/asset), when someone asks 'do we have data for X', 'where do we get X data', 'build the X database', or before implementing a calculation that needs reference data.

Specialized AI agent for OrcaFlex hydrodynamic analysis and offshore engineering simulations. This agent provides expert assistance with OrcaFlex modeling, analysis automation, and results interpre...

Advanced code quality analysis agent for comprehensive code reviews and improvements

Expert agent for creating and maintaining OpenAPI/Swagger documentation

SPARC Architecture phase specialist for system design

Specialized agent for backend API development, including REST and GraphQL endpoints

Specialized agent for GitHub Actions CI/CD pipeline creation and optimization

Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis

Implementation specialist for writing clean, efficient code

Build field-level offshore infrastructure data bundles from local BSEE tables for engineering products. Use when users ask for field structures, platforms, pipelines, risers, jumpers, umbilicals, FMP/MCP systems, appurtenances, or product-ready field infrastructure joins.

Extract and process BSEE (Bureau of Safety and Environmental Enforcement) data including production, WAR (Well Activity Reports), and APD (Application for Permit to Drill) data. Use for querying production data, well activities, drilling permits, completions, and workovers by API number, block, lease, or field with automatic data normalization and caching.

Perform NPV analysis and economic evaluation for oil & gas assets. Use for cash flow modeling, price scenario analysis, Monte Carlo simulation, P10/P50/P90 probabilistic analysis, working interest calculations, and financial metrics (IRR, payback, NPV) for field development projects.

Forecast oil & gas well production using decline curve analysis. Use for EUR estimation, type curve generation, production modeling, and reserve calculations with Arps decline models (exponential, hyperbolic, harmonic).

Summarize worldenergydata source readiness, freshness, data locations, and scheduler blockers from repo metadata. Use when asked for worldenergydata data completeness, latest data dates, data locations, refresh status, scheduler source health, or acceptance-criteria inputs for data-source freshness.

Analyze drilling performance and metrics using API 12-digit well numbering system. Use for drilling time analysis, cost benchmarking, well comparison, sidetracks tracking, and drilling efficiency metrics across GOM fields.

Energy Data Visualizer (user)

Perform offshore field development economic analysis with NPV, MIRR, IRR, and payback calculations. Use for investment analysis, cashflow modeling, BSEE data integration, development system classification, and Excel report generation.

Runs the right deterministic extraction lane per office/email format and records each format's KNOWN losses UNDER A TEXT/CSV LANE in a coverage ledger so a faithful extract never masquerades as complete. Use when extracting docx/xlsx/msg/pdf/pptx sources whose richest content (formulas, charts, diagrams, attachments, images, speaker notes) does not survive a text/CSV dump.

Extracts a compressed archive (RAR/ZIP/7z) and then proves the extraction is byte-faithful by re-hashing every extracted file against the container's stored per-entry checksums — because an open-source decoder can report success while silently writing wrong bytes at the correct size (presence and size are NOT fidelity). Falls back across decoders (7z, bsdtar, official unrar) for entries one engine mis-decodes, and reports the exact set of files that no available decoder can reproduce. Use when extracting any archive before its contents enter an ingestion pipeline, especially RAR4 archives or when only partial decoders (p7zip, libarchive) are installed.

Scores committed extracts against an independent extraction engine (a different codebase than the pipeline lane) to produce measured per-lane precision/recall, with two-tier numeric scoring and a hard rule that every sub-1.0 number is attributed to a named cause. Use when a conversion lane needs correctness evidence beyond the fidelity verify loop — turning "we believe the extracts are faithful" into per-lane measured numbers.

Runs an independent adversarial verification loop on a produced change (extraction code, corpus batch, or page set) until a clean PASS — the producer never self-certifies, the reviewer is prompted to refute and to build runnable reproducers for code findings, and every fix is gated on re-running the reviewer's own reproducer. Use when a change must earn justified confidence before merge, especially pipeline-code changes where a plausible fix can be narrower than the defect class.

Independently reviews a batch of source-extract reference pages against the source binary so that no prose claims more than the committed extract supports — checking hash match, extract fidelity, and that every quoted figure traces to a committed extract with a cross-reference treated as not-a-quote and a derived number as not-quoted. Use when reviewing extracted/source-derived pages before merge, especially text-faithful pages whose prose may overreach.

Classifies XLS/XLSX workbooks before extraction and requires a traceable input data or logic contract, code artifact, and verified output artifact for a ten-file canary. Use when spreadsheet files may contain formulas, named ranges, charts, cached values, protection, or mixed data and calculation logic.

Triages a raw company archive into an ingest set by classifying on content (not extension), value-ranking candidates, deduping superseded versions, and hard EXCLUDING PII and third-party-confidential material before any extraction. Use when starting an ingestion campaign whose source is a messy company repo or shared drive full of code, build/venv, agent, and marketing noise.

Fetches the real bytes behind off-disk Git LFS pointer files via the LFS Batch API when git-lfs and sudo are unavailable, using a host token, and verifies the download because the content sha256 IS the pointer oid. Use when a source binary in a Git repo is a stored LFS pointer (a tiny version-oid-size stub) and you must read the actual file to extract from it, without installing git-lfs.

Deploy and verify the AceEngineer static website on Vercel, including local preview, static asset checks, and post-deploy verification.

Maintain SEO-facing content, metadata, sitemap/robots consistency, and marketing page copy for aceengineer-website.