feat(skills): author the ac_* CTI calibration skill set (Phase 2)

.claude/skills/ac_correct_cti.md

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+../../skills/ac_correct_cti.md

.claude/skills/ac_fit_cti_model.md

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+../../skills/ac_fit_cti_model.md

.claude/skills/ac_load_results.md

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+../../skills/ac_load_results.md

.claude/skills/ac_mask_and_extract.md

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+../../skills/ac_mask_and_extract.md

.claude/skills/ac_plot.md

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+../../skills/ac_plot.md

.claude/skills/ac_setup_environment.md

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+../../skills/ac_setup_environment.md

.claude/skills/ac_simulate_dataset_1d.md

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+../../skills/ac_simulate_dataset_1d.md

.claude/skills/ac_simulate_imaging_ci.md

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+../../skills/ac_simulate_imaging_ci.md

.claude/skills/ac_workspace_navigation.md

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+../../skills/ac_workspace_navigation.md

PENDING.md

@@ -21,7 +21,6 @@ wiki page or dataset, in the reference's shape.
 - [ ] `.claude/skills/ac_hierarchicac_inference.md` — regenerate for this domain (reference: `.claude/skills/al_hierarchical_inference.md`)
 - [ ] `.claude/skills/ac_inspect_results_mcp.md` — regenerate for this domain (reference: `.claude/skills/al_inspect_results_mcp.md`)
 - [ ] `.claude/skills/ac_inspect_source_reconstruction.md` — regenerate for this domain (reference: `.claude/skills/al_inspect_source_reconstruction.md`)
-- [ ] `.claude/skills/ac_load_results.md` — regenerate for this domain (reference: `.claude/skills/al_load_results.md`)
 - [ ] `.claude/skills/ac_mge_decomposition.md` — regenerate for this domain (reference: `.claude/skills/al_mge_decomposition.md`)
 - [ ] `.claude/skills/ac_multi_dataset.md` — regenerate for this domain (reference: `.claude/skills/al_multi_dataset.md`)
 - [ ] `.claude/skills/ac_plot_fit_residuals.md` — regenerate for this domain (reference: `.claude/skills/al_plot_fit_residuals.md`)
@@ -32,7 +31,6 @@ wiki page or dataset, in the reference's shape.
 - [ ] `.claude/skills/ac_run_search.md` — regenerate for this domain (reference: `.claude/skills/al_run_search.md`)
 - [ ] `.claude/skills/ac_run_slam_pipeline.md` — regenerate for this domain (reference: `.claude/skills/al_run_slam_pipeline.md`)
 - [ ] `.claude/skills/ac_sensitivity_mapping.md` — regenerate for this domain (reference: `.claude/skills/al_sensitivity_mapping.md`)
-- [ ] `.claude/skills/ac_setup_environment.md` — regenerate for this domain (reference: `.claude/skills/al_setup_environment.md`)
 - [ ] `.claude/skills/ac_simulate_dataset.md` — regenerate for this domain (reference: `.claude/skills/al_simulate_dataset.md`)
 - [ ] `.claude/skills/ac_subhalo_detect.md` — regenerate for this domain (reference: `.claude/skills/al_subhalo_detect.md`)
 - [ ] `.claude/skills/ac_time_delay_cosmography.md` — regenerate for this domain (reference: `.claude/skills/al_time_delay_cosmography.md`)
@@ -113,7 +111,6 @@ wiki page or dataset, in the reference's shape.
 - [ ] `skills/ac_ingest_paper.md` — regenerate for this domain (reference: `skills/al_ingest_paper.md`)
 - [ ] `skills/ac_inspect_results_mcp.md` — regenerate for this domain (reference: `skills/al_inspect_results_mcp.md`)
 - [ ] `skills/ac_inspect_source_reconstruction.md` — regenerate for this domain (reference: `skills/al_inspect_source_reconstruction.md`)
-- [ ] `skills/ac_load_results.md` — regenerate for this domain (reference: `skills/al_load_results.md`)
 - [ ] `skills/ac_mge_decomposition.md` — regenerate for this domain (reference: `skills/al_mge_decomposition.md`)
 - [ ] `skills/ac_multi_dataset.md` — regenerate for this domain (reference: `skills/al_multi_dataset.md`)
 - [ ] `skills/ac_plot_fit_residuals.md` — regenerate for this domain (reference: `skills/al_plot_fit_residuals.md`)
@@ -124,7 +121,6 @@ wiki page or dataset, in the reference's shape.
 - [ ] `skills/ac_run_search.md` — regenerate for this domain (reference: `skills/al_run_search.md`)
 - [ ] `skills/ac_run_slam_pipeline.md` — regenerate for this domain (reference: `skills/al_run_slam_pipeline.md`)
 - [ ] `skills/ac_sensitivity_mapping.md` — regenerate for this domain (reference: `skills/al_sensitivity_mapping.md`)
-- [ ] `skills/ac_setup_environment.md` — regenerate for this domain (reference: `skills/al_setup_environment.md`)
 - [ ] `skills/ac_simulate_dataset.md` — regenerate for this domain (reference: `skills/al_simulate_dataset.md`)
 - [ ] `skills/ac_subhalo_detect.md` — regenerate for this domain (reference: `skills/al_subhalo_detect.md`)
 - [ ] `skills/ac_time_delay_cosmography.md` — regenerate for this domain (reference: `skills/al_time_delay_cosmography.md`)

skills/README.md

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 # skills/
 
-Procedural how-to-do-X skills for the PyAuto\* lensing stack. Each skill is a single
-Markdown file with YAML frontmatter; the body teaches an agent (and through them, the
-user) how to write Python that accomplishes one lensing task.
+Procedural how-to-do-X skills for the PyAutoCTI stack. Each skill is a single
+Markdown file with YAML frontmatter; the body teaches an agent (and through them,
+the user) how to write Python that accomplishes one CTI calibration task.
 
-Skills are also exposed at `.claude/skills/` (Claude Code) and `~/.codex/skills/` (when
-configured) via symlinks; the canonical files live here.
+Skills are also exposed at `.claude/skills/` (Claude Code) and `~/.codex/skills/`
+(when configured) via symlinks; the canonical files live here.
 
 ## Conventions
 
-- File names use the `ac_<task>` convention for lensing-API skills, e.g. `ac_run_search.md`.
-- Project-workflow skills (repo-level operations, template manipulation) use a plain
-  kebab-case name, e.g. `init-slam.md`, `start-new-project.md`.
-- Domain-mode skills that pair an external pipeline repo to the assistant use that
-  domain as prefix — `euclid_<task>.md` for the Euclid pipeline (euclid mode).
+- File names use the `ac_<task>` convention for CTI-API skills, e.g.
+  `ac_fit_cti_model.md`.
+- Project-workflow skills (repo-level operations, template manipulation) use a
+  plain kebab-case name, e.g. `start-new-project.md`.
 - Meta-skills (writing guide, bootstrap protocol) start with `_`.
-- Every lensing-API skill is **python-first**: the deliverable is a runnable `.py` script
-  + the understanding to evolve it. Project-workflow skills may instead drive `rsync`,
-  `cp`, or other repo-level operations.
-- Source citations use the project-name + repo-relative-path form,
-  e.g. `PyAutoFit:autofit/non_linear/search/nest/nautilus/`, resolved via
-  [`../sources.yaml`](../sources.yaml).
-- Wiki references use workspace-relative paths,
-  e.g. `wiki/core/concepts/non_linear_search.md`.
+- Every CTI-API skill is **python-first**: the deliverable is a runnable `.py`
+  script + the understanding to evolve it, grounded in a validated
+  `autocti_workspace` example — never API memory.
+- Source citations use the project-name + repo-relative-path form, e.g.
+  `PyAutoCTI:autocti/clocker/`, resolved via [`../sources.yaml`](../sources.yaml).
+- Wiki references use workspace-relative paths, e.g.
+  `wiki/core/concepts/charge_transfer_inefficiency.md`.
 
 ## Index
 
-Every skill below is a **complete recipe** unless marked `(stub)` — the stubs are gathered
-under "Pending — stubbed" at the end, with a queue of catalogued-but-unstubbed topics after
-them.
+The recipes below are the assistant's current CTI capability. The full growth
+queue — skills, wiki pages and datasets still to be authored — is
+[`../PENDING.md`](../PENDING.md); this cell was born as a lightweight seed and is
+grown in use.
 
 ### Meta
 
-- [`_style.md`](./_style.md) — writing guide every skill is authored against. Read first
-  before adding or editing any skill.
-- [`_bootstrap_skill.md`](./_bootstrap_skill.md) — protocol for authoring a new skill on
-  demand when a user requests a capability not yet covered.
-
-### Setup & maintenance
-
-- [`ac_setup_environment.md`](./ac_setup_environment.md) — detect absent or broken PyAuto\*
-  environments, install via pip or editable clones when needed, configure caches, verify imports.
-- [`ac_update_wiki.md`](./ac_update_wiki.md) — refresh `wiki/core/` pages whose pinned
-  source commits have moved; surface new public APIs for review.
-- [`ac_audit_skill_apis.md`](./ac_audit_skill_apis.md) — verify every PyAuto\* symbol
-  cited in `skills/` and `wiki/core/api+stack/` resolves in the installed stack;
-  report stale references with suggested replacements.
-- [`ac_refresh_api_docs.md`](./ac_refresh_api_docs.md) — orchestrate a full maintenance
-  sweep across skill recipes, wiki API pages, and pinned-source drift after a PyAuto\*
-  upgrade or source refresh.
-- [`ac_ingest_paper.md`](./ac_ingest_paper.md) — add a strong-lensing paper (local PDF
-  or arxiv URL): project-local `wiki/project/bibliography.md` by default inside a science
-  project; shared `wiki/literature/` in the assistant clone or on explicit promotion.
+- [`_style.md`](./_style.md) — writing guide every skill is authored against.
+  Read first before adding or editing any skill.
+- [`_bootstrap_skill.md`](./_bootstrap_skill.md) — protocol for authoring a new
+  skill on demand when a user requests a capability not yet covered.
+
+### Setup
+
+- [`ac_setup_environment.md`](./ac_setup_environment.md) — install and verify the
+  PyAutoCTI stack, **including arcticpy** (the C++ arctic clocking code `import
+  autocti` needs but pip won't install). The #1 setup failure; covers the
+  libgsl-dev + numpy/cython + arcticpy recipe and the numpy-downgrade trap.
+
+### The CTI calibration pipeline
+
+Grounded per-skill in the matching `autocti_workspace` stage; navigate the whole
+catalogue with `ac_workspace_navigation`.
+
+- [`ac_workspace_navigation.md`](./ac_workspace_navigation.md) — the map: the two
+  geometries (`dataset_1d`, `imaging_ci`), their shared stage pipeline, and which
+  `start_here.py` to read for any task.
+- [`ac_simulate_dataset_1d.md`](./ac_simulate_dataset_1d.md) — simulate a 1D CTI
+  dataset (charge lines + a known trap model) to generate ground truth.
+- [`ac_simulate_imaging_ci.md`](./ac_simulate_imaging_ci.md) — simulate a 2D
+  charge-injection image (the Euclid VIS / HST ACS geometry; parallel/serial CTI,
+  `Clocker2D`).
+- [`ac_mask_and_extract.md`](./ac_mask_and_extract.md) — mask the FPR/EPER before
+  fitting, and extract FPR/EPER regions as arrays (`layout.extract.fpr/eper`).
+- [`ac_fit_cti_model.md`](./ac_fit_cti_model.md) — compose a CTI model and fit it
+  with a non-linear search, including the **factor graph** that fits several
+  charge lines jointly. The core capability.
+- [`ac_correct_cti.md`](./ac_correct_cti.md) — remove CTI from data with
+  `clocker.remove_cti`, to correct science data or diagnose a calibration.
+- [`ac_load_results.md`](./ac_load_results.md) — inspect a fit's `result`, and
+  aggregate across many fits (`Aggregator`, `ac.agg.CTIAgg` and its generators).
+
+### Plotting
+
+- [`ac_plot.md`](./ac_plot.md) — the `autocti.plot` **function API**
+  (the `subplot_*` / `figure_*` families, `aplt.plot_yx`, `aplt.plot_array`, `aplt.plot_cti_1d`, the
+  `*_list` combined subplots). No MatPlot/Output/Visuals object.
 
 ### Project workflow
 
-- [`start-new-project.md`](./start-new-project.md) — the single bridge to a standalone
-  **science project** and its full lifecycle (Create → Work → Collaborate → Publish):
-  scaffold a lean repo that copies the reproducible science and refers back to the assistant
-  for skills/wiki, run modelling with reproducibility manifests + the `wiki/project/` journal,
-  build collaborator summaries, and harden for an open-science release (CITATION/license/Zenodo).
-  Optional HPC folder.
-- [`contribute-upstream.md`](./contribute-upstream.md) — prepare a scoped change,
-  push it either to your collaborator branch on `PyAutoLabs/autocti_assistant`
-  or to your fork, and open a draft PR into `PyAutoLabs/autocti_assistant`.
-- [`init-slam.md`](./init-slam.md) — populate an empty `scripts/` folder with SLaM
-  pipeline script(s) copied from `autocti_workspace` and tailored to the chosen data
-  type.
-
-### Euclid mode (pipeline-paired)
-
-Skills pairing the collaboration's
-[`euclid_strong_lens_modeling_pipeline`](https://github.com/PyAutoLabs/euclid_strong_lens_modeling_pipeline)
-to the assistant; the paired literature context is the dedicated
-[`wiki/euclid/`](../wiki/euclid/index.md) sub-wiki.
-
-- [`euclid_setup_pipeline.md`](./euclid_setup_pipeline.md) — clone/install the pipeline,
-  the `dataset/<sample>/<dataset>/` layout, and the black-box `start_here.py` run.
-- [`euclid_prepare_data.md`](./euclid_prepare_data.md) — segmentation validation, binary
-  mask tuning, extra-galaxy masks/centres via the GUI tools, hand-assembling a dataset
-  folder.
-- [`euclid_model_lens.md`](./euclid_model_lens.md) — choose and run the staged
-  pipelines: initial MGE+SIE, Sersic photometry, lens-only subtraction, multi-waveband,
-  full SLaM.
-- [`euclid_workflow_products.md`](./euclid_workflow_products.md) — aggregate many fits
-  into .csv catalogues, .fits stacks, and one-line .png summaries via `workflow/`.
-- [`euclid_hpc_runs.md`](./euclid_hpc_runs.md) — `hpc/sync` configuration and the
-  SLURM batch-array templates for sample-scale runs.
-
-### Data preparation
-
-- [`ac_prepare_imaging_data.md`](./ac_prepare_imaging_data.md) — load and preprocess
-  FITS imaging, decide masking for real data, measure noise, prepare PSF.
-- [`ac_simulate_dataset.md`](./ac_simulate_dataset.md) — synthesise a lens dataset
-  (imaging or interferometer) from a ground-truth model.
-
-### Model building
-
-- [`ac_build_imaging_model.md`](./ac_build_imaging_model.md) — compose a `Tracer` from
-  light + mass profiles and wrap it in an `AnalysisImaging`.
-- [`ac_build_interferometer_model.md`](./ac_build_interferometer_model.md) — same, but
-  for visibility-plane data.
-- [`ac_custom_profile.md`](./ac_custom_profile.md) — write a new light or mass profile
-  subclass and register it for use in models.
-
-### Fitting
-
-- [`ac_configure_search.md`](./ac_configure_search.md) — pick and tune a non-linear
-  search (Nautilus, Dynesty, Emcee, Zeus, …) for your problem.
-- [`ac_run_search.md`](./ac_run_search.md) — execute `search.fit(model=..., analysis=...)`
-  and monitor convergence.
-- [`ac_chain_searches.md`](./ac_chain_searches.md) — sequence searches so a later phase
-  inherits priors from an earlier one.
-- [`ac_run_slam_pipeline.md`](./ac_run_slam_pipeline.md) — run a Source-Light-Mass
-  pipeline (the canonical automated lensing workflow).
-- [`ac_debug_fit_failure.md`](./ac_debug_fit_failure.md) — diagnose a fit that didn't
-  converge or produced unphysical results.
-
-### Results & visualisation
-
-- [`ac_load_results.md`](./ac_load_results.md) — load a completed fit's `Tracer`,
-  `Samples`, dataset and FITS products from its output folder.
-- [`ac_inspect_results_mcp.md`](./ac_inspect_results_mcp.md) — the read-only
-  results-inspector MCP server: browse fits, summaries, result images and bulk
-  subplot/FITS extraction from chat harnesses without code execution (Claude
-  Desktop first).
-- [`ac_plot_tracer.md`](./ac_plot_tracer.md) — plot ray tracing, critical curves,
-  caustics, magnification maps.
-- [`ac_plot_fit_residuals.md`](./ac_plot_fit_residuals.md) — plot model image,
-  residuals, normalised residuals, chi-squared map.
-- [`ac_inspect_source_reconstruction.md`](./ac_inspect_source_reconstruction.md) —
-  inspect a pixelised inversion: regularisation, source-plane image, reconstruction
-  diagnostics.
-- [`ac_to_notebook.md`](./ac_to_notebook.md) — convert a generated narrative-docstring
-  script to a Jupyter notebook (docstrings → markdown cells, code → code cells) via the
-  stdlib-only `autoassistant/to_notebook.py`.
-
-### Pending — stubbed (need full recipes)
-
-Drafted as scaffolds during the 2026-05-22 coverage audit against
-`autocti_workspace/scripts/`. Each has frontmatter + Orient/Ask/Branch/Combine
-structure + `Further reading`; the `Branch` recipes are TODO markers. Fill in
-one at a time, paired with their companion wiki/core stub.
-
-**Data types and regimes**
-
-- [`ac_point_source.md`](./ac_point_source.md) (stub) — quasar / multi-image
-  position fits, flux ratios, point-source deblending.
-- [`ac_time_delay_cosmography.md`](./ac_time_delay_cosmography.md) (stub) — H0
-  from time-delay strong lenses.
-- [`ac_group_lensing.md`](./ac_group_lensing.md) (stub) — extra galaxies,
-  scaling-relation members.
-- [`ac_cluster_csv_api.md`](./ac_cluster_csv_api.md) (stub) — cluster-scale
-  CSV-driven model composition.
-- [`ac_multi_dataset.md`](./ac_multi_dataset.md) (stub) — joint imaging +
-  interferometer, multi-band, wavelength-dependent sources.
-- [`ac_weak_lensing.md`](./ac_weak_lensing.md) (stub) — shear catalogue fits
-  (`WeakDataset` / `AnalysisWeak`).
-- [`ac_datacube_modeling.md`](./ac_datacube_modeling.md) (stub) — interferometer
-  spectral cubes.
-
-**Dark-matter substructure**
-
-- [`ac_subhalo_detect.md`](./ac_subhalo_detect.md) (stub) — Bayesian-evidence
-  grid search for perturbing subhaloes.
-- [`ac_sensitivity_mapping.md`](./ac_sensitivity_mapping.md) (stub) — quantitative
-  detectability calibration.
-
-**Advanced techniques**
-
-- [`ac_hierarchicac_inference.md`](./ac_hierarchicac_inference.md) (stub) —
-  population-level / graphical models, expectation propagation.
-- [`ac_aggregator_bulk_analysis.md`](./ac_aggregator_bulk_analysis.md) (stub) —
-  bulk operations across many completed fits, optional result database.
-- [`ac_adaptive_pixelization.md`](./ac_adaptive_pixelization.md) (stub) — adaptive
-  mesh + adaptive regularisation source reconstructions.
-- [`ac_mge_decomposition.md`](./ac_mge_decomposition.md) (stub) — Multi-Gaussian
-  Expansion workflows for lens / source.
-- [`ac_custom_analysis.md`](./ac_custom_analysis.md) (stub) — subclassing
-  `Analysis` to add custom likelihood terms.
-
-**Queue (catalogued, not yet stubbed):** `ac_multi_plane`, `ac_los_halos`,
-`ac_over_sampling`, `ac_workflow_outputs`, `ac_data_prep_interactive`,
-`ac_bayesian_model_comparison`.
+- [`start-new-project.md`](./start-new-project.md) — bridge to a standalone
+  **science project** repo and its lifecycle (Create → Work → Collaborate →
+  Publish).
+- [`contribute-upstream.md`](./contribute-upstream.md) — prepare a scoped change
+  and open a draft PR into `PyAutoLabs/autocti_assistant`.

skills/_style.md

@@ -67,7 +67,7 @@ This is the rule that distinguishes the workspace from a tutorial workspace.
 Every Python script the agent saves — whether to `scripts/` or `scripts/scratch/` — follows the
 PyAutoCTI **workspace** style, not ad-hoc banner comments. It is the same style used by
 every script in `autocti_workspace/scripts/` (canonical example:
-`autocti_workspace:scripts/imaging/start_here.py`), and it exists for two reasons: it
+`autocti_workspace:scripts/dataset_1d/modeling/start_here.py`), and it exists for two reasons: it
 keeps the science and inference narrative inline with the code, and it makes the script
 mechanically convertible to a Jupyter notebook — each top-level `"""..."""` block becomes a
 markdown cell and the code between blocks becomes a code cell.