jingtao-lbl

First-run interactive setup for the offline agent — the official "getting started" flow the FIRST time someone uses A2MC in a repo/site. Interview the user (is a2mc_config.sh set up, where is the E3SM/ELM-FATES checkout, FATES on/off, carbon-only vs nutrient-enabled PARTEH, ECA vs RD, site name/location, PFTs, calibration targets), verify the checkout + RAG milestone, then create and populate the use case (site config + validation targets + parameter list) and hand off to phase0-design. Use when the user says "set up A2MC", "first time using A2MC", "help me get started / onboard me to A2MC", "initialize a new site / use case", "configure A2MC for my site", "I want to calibrate a new site". DISTINCT from onboard-session (which resumes an ALREADY-configured setup).

Scaffold + register (or retire + de-register) an A2MC skill so the registry steps are never half-done. Use when the user or agent wants to create a new capability — "add a skill", "create/scaffold a skill", "make this reusable as a skill", "distill X into a skill" — OR to remove one — "remove/retire/delete the X skill". Writes (or deletes) the SKILL.md, and registers (or de-registers) it across all THREE human-facing registries (the README 'Current skills' table, docs/a2mc_reference/skills_catalog.md, AND the AGENTS.md 'At a glance' table), runs the mechanical drift check, and stops for human review before commit. Human-gated.

Set up real-time monitoring of an active A2MC HPC ensemble or experiment on Perlmutter at session start (CLAUDE.md Rule

Log interactive calibration work for a site under use_cases/{site}/memory/logs/. Two log types — a PHASE log (a diagnosis, screening, experiment design/result, refinement — recorded the same way the autonomous agent does, via PhaseLogger, so both modes' logs synthesize together) or a free-form SESSION log (exploratory work that does not map to a specific phase). Use when the user wants to record calibration or exploration work — "log this", "log this phase / diagnosis / experiment", "log this calibration session", "write a session log", "record what I explored".

Compare A2MC calibration rounds (R1, R2, …) against each other and the validation targets — top-N best-achievable biomass per round, per-target Morris μ* sensitivity, P-pool / cross-regime overlays. Use when the user asks to "compare rounds", "update the multi-round figure", "refresh the R1-RN comparison", "which round is best", "top sensitive parameters per round", or to regenerate any `multiround_*` / cross-round figure after new cases complete. Codifies the multiround bundle pipeline + the footguns (screening contamination, case-name patterns, μ* ranking, param-set mismatch, partial-ensemble caveats).

Inject a human-originated domain fact (a discovery, a parameter insight, a mechanism/relationship) into A2MC's curated knowledge so the calibration agent surfaces it — placing it correctly across the up-to-three channels (site discoveries.json, generic parameters.json, curated_relationships.yaml), validating, and rebuilding the graph. Use when the user says "add this finding/parameter knowledge to A2MC's AI", "inject the X discovery into the KB", "make the agent aware of X", "author a curated relationship for X", or wants a manuscript/literature insight to reach the reasoning pipeline. This is the HUMAN-originated counterpart to curate-knowledge (which promotes run-originated proposals); both are Tier-3 curated writes and you (the human-in-the-loop) own the truth call. Distilled from graphrag_curated_yaml_roadmap.md + dev log 20260519d (the clumping_index injection).

Convert a Markdown document (an ana_log, report, or note) to a shareable PDF or Word (.docx) via pandoc. Use when the user asks to "convert/render markdown to PDF/Word/docx", "render this ana_log/report to PDF", "export markdown to a document", "make a PDF of this", "turn this .md into a docx". Prose documents, not slide decks (slides go through Marp). Requires pandoc + a LaTeX engine for PDF, and python-docx for round-trip-safe .docx edits. Self-contained repo copy — depends only on tools the environment provides, not on any user-level skill or ~/.claude workflow.

Design + launch + analyze an A2MC offline HPC experiment (parameter sweep on top of a Morris base case). Use when the user wants to test a hypothesis with N variant runs (e.g., clumping_index sweep, vmax_p sensitivity, hydraulic-vulnerability probe). Codifies the conventions distributed across phases/phase5_testing/, tools/create_case.sh --case-suffix, and prior per-experiment plans in memory/dev_logs/.

Scaffold and register a new E2SA skill so the steps are never half-done. Use when the human or agent wants to create a new capability — "add a skill", "create a new skill", "scaffold a skill", "make this reusable as a skill", "distill X into a skill". Creates the SKILL.md with correct frontmatter, registers it in the AGENTS.md capability catalog (the manual registry), seeds a Changelog, and stops for human review before commit. Human-gated.

Improve an existing E2SA skill from accumulated evidence, human-gated. Use when a skill missed a step or needs updating, when a lesson/feedback in a skill's domain has piled up, or during a periodic skill review — "refine the X skill", "improve this skill", "the X skill should have caught Y", "review the skills". Gathers the signal (lessons, run-journal outcomes, feedback), proposes a concrete SKILL.md diff, and STOPS for human approval; it never self-applies. After approval it edits, appends a Changelog line, and commits.

Implement a new E2SA data-source adapter (the code that fetches a source and parses it into Observation records). Use when writing the adapter for a source that has already been onboarded/inspected — "build the adapter for X", "write the X adapter", "implement the fetch/parse for X", or the coding step after e2sa-add-data-source. Walks the BaseAdapter contract (list_available / fetch / parse_to_schema), the FetchResult single-file-vs-whole-package shape, the Observation + Provenance schema, canonical units + depth + serves, ADAPTER_REGISTRY registration, the fixture + test, and the parse gotchas already learned (sentinels, CRS tiers, obs_id uniqueness, schema drift, idempotency).

Implement a new E2SA data-center connector (the per-data-center access layer that owns auth + search + whole-package fetch under Option C). Use when wrapping a data center not yet connected — "add a connector for X", "wrap the PANGAEA/Earthdata/Zenodo API", or when migrating an existing self-fetching adapter onto a connector. Walks the BaseConnector contract, the probe-the-API-first step, the two search patterns (server-side filter vs enrich + bbox coverage-ratio), the two fetch shapes (BagIt-zip vs file-by-file), the reusable conventions (urllib + User-Agent, raw layout, token-free reads, on-disk fast-path, manual fallback), CONNECTOR_REGISTRY registration, and the mocked-urlopen + E2E_LIVE test split. Distilled from the arctic_data_center and ess_dive connectors.

Add a new data source (data center, archive, or dataset) into an E2SA project. Use when the human or agent has found a dataset to bring in, is inspecting a new archive, or says "add a data source", "add this dataset", "I found data at X", or after downloading data from a center not yet documented. Walks the full procedure: inventory check, download whole package, inspect (format/metadata-standard/CRS/license/citation), write the project-named source card, update the sources index and data-center registry, capture a finding, and credential setup. Always uses the latest dataset version and records a full citation.

Audit an E2SA adapter's data output against the REAL source and propose source-grounded corrections (applied only on human approval). Use after building or changing an adapter, after a parse, when staged data looks off, or for a periodic adapter review — "audit/validate the X adapter", "check the data X produces", "is above_stdm correct", "review the adapters for data-quality". Runs the e2sa/qc checks (serves-subset, value-range, subsurface-depth, citation-not-synthesized, self-describing) on a real parse, surfaces the value distributions, cross-checks variables/units/citation against the source, and PROPOSES a source-grounded fix for each finding (never invents) that is applied only on human approval (propose-first, like e2sa-refine-skill). NOT for run-level shippability (run skeleton / notebooks / secrets / a run_id) — that is `e2sa-validate`. Distilled from the 2026-06-23 above_stdm fabrications (reflection 20260623s).

File a data-preparation task into projects/<project>/tasks/ when the current work needs site data that isn't already prepared. Use whenever the agent (not just the human) recognizes a need for forcing data, surface dataset assembly, observations, or QC/analysis that warrants its own request with provenance. Always sets status=requested and surfaces to the human; never auto-executes the filed task in the same fire.

Produce a publication-quality study-site / watershed / regional map figure for an E2SA project, from public-data download through layered matplotlib rendering. Use when the user wants to "make a site/study-area/watershed map", "plot a DEM map with sites overlaid and labeled", "download a DEM and plot it", "stage HUC-8 boundaries", "build the overview/region figure", or "add/rescope a study site". The config-driven reference scripts live in projects/spade/tools/site_figure/. The report agent's mapping step (E2SA S9) is a downstream consumer. NOT for conceptual/architecture diagrams (use proposal-figure), data/time-series plots, or slides.