How do I install the Txpipe skill?

Run npx skillmds@latest add jfcrenshaw/txpipe in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Txpipe safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Txpipe?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Txpipe free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Txpipe?

jfcrenshaw (@jfcrenshaw) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Txpipe by jfcrenshaw — Agent Skill

Name: Txpipe
Author: jfcrenshaw

Txpipe

How to work with TXPipe, the DESC 3x2pt weak-lensing pipeline. Covers all pipeline phases (ingestion → photo-z → selection → calibration → masks → maps → noise maps → 2pt → covariance → theory → diagnostics), key stage names, file tags, pipeline YAML structure, and critical gotchas. Use this skill whenever the user imports txpipe; works with any TXPipe stage (TXTwoPoint, TXTwoPointFourier, TXSourceMaps, TXLensMaps, TXSourceSelector*, TXShearCalibration, TXTracerMetadata, TXSimpleMask, TXCustomMask, TXIngest*, TXBlinding, TXFourierNamasterCovariance, TXRealNamasterCovariance, TXJackknifeCenters, TXPSFDiagnostics, TXRoweStatistics, TXTauStatistics, etc.); writes a TXPipe pipeline YAML; asks about shape or shear catalogs, metacalibration or metadetect, source or lens selection, tomographic binning, 3x2pt two-point functions (shear-shear, galaxy-galaxy lensing, angular clustering), map generation, noise maps, jackknife covariance, PSF diagnostics, or theory predictions.

jfcrenshaw Updated Sep 22, 2026

File contents

TXPipe — DESC 3×2pt weak-lensing pipeline

You're helping a user work with TXPipe, the main DESC analysis workhorse. TXPipe processes shear and photometric catalogs through sample selection, map generation, two-point measurements (real and Fourier space), covariance estimation, theory comparison, and diagnostics. All stages are ceci PipelineStage subclasses; for ceci conventions see the ceci skill. For NERSC job submission, see the nersc skill. Key library dependencies: NaMaster (namaster skill) for Fourier C_ℓ measurements and covariance; CCL (ccl skill) for theory predictions; Firecrown (firecrown skill) is used internally by theory/blinding stages and consumes TXPipe's sacc output for parameter inference.

Pipeline phases (in order)

Ingestion — TXIngestDataPreview02, TXCosmoDC2Mock, etc. — source-specific; using the wrong ingester silently reads wrong columns
Photo-z — RAIL stages (PZEstimatorLens/Source, PZRailSummarizeLens/Source); must produce QPNOfZFile before 2pt
Selection — TXSourceSelectorMetadetect/Metacal/Lensfit/HSC + TXSourceTomography; TXMeanLensSelector for lenses
Calibration — TXShearCalibration then TXTracerMetadata (both required; calibration must precede tomography)
Masks — TXSimpleMask or TXCustomMask; nside must match map nside everywhere
Maps — TXSourceMaps, TXLensMaps, TXAuxiliarySourceMaps/LensMaps, TXLSSWeights
Noise maps — TXSourceNoiseMaps (~~30 realisations), TXLensNoiseMaps (~~5); required for covariance
Two-point real — TXTwoPoint (TreeCorr; ξ±, γ_t, w(θ)); uses TXJackknifeCenters for jackknife cov
Two-point Fourier — TXTwoPointFourier (NaMaster; C_ℓ for shear-shear, shear-pos, pos-pos; see namaster skill)
Covariance — TXFourierNamasterCovariance / TXRealNamasterCovariance (expensive; use TXFourierGaussianCovariance for quick tests; see namaster skill)
Theory & blinding — TXTwoPointTheoryReal/Fourier (CCL; see ccl skill); TXBlinding (Firecrown internally; see firecrown skill)
Diagnostics — TXPSFDiagnostics, TXRoweStatistics, TXTauStatistics, TXSourceDiagnosticPlots, TXTwoPointPlots

The examples/metadetect/ pipeline is the canonical full-pipeline reference.

Reference

Topic	Reference
Pipeline phases and stage names	`references/txpipe-stages.md`
Key file types, pipeline YAML structure, example pipelines, gotchas	`references/txpipe-pipeline.md`

---name: txpipedescription: How to work with TXPipe, the DESC 3x2pt weak-lensing pipeline. Covers all pipeline phases (ingestion → photo-z → selection → calibration → masks → maps → noise maps → 2pt → covariance → theory → diagnostics), key stage names, file tags, pipeline YAML structure, and critical gotchas. Use this skill whenever the user imports txpipe; works with any TXPipe stage (TXTwoPoint, TXTwoPointFourier, TXSourceMaps, TXLensMaps, TXSourceSelector*, TXShearCalibration, TXTracerMetadata, TXSimpleMask, TXCustomMask, TXIngest*, TXBlinding, TXFourierNamasterCovariance, TXRealNamasterCovariance, TXJackknifeCenters, TXPSFDiagnostics, TXRoweStatistics, TXTauStatistics, etc.); writes a TXPipe pipeline YAML; asks about shape or shear catalogs, metacalibration or metadetect, source or lens selection, tomographic binning, 3x2pt two-point functions (shear-shear, galaxy-galaxy lensing, angular clustering), map generation, noise maps, jackknife covariance, PSF diagnostics, or theory predictions.---# TXPipe — DESC 3×2pt weak-lensing pipelineYou're helping a user work with TXPipe, the main DESC analysis workhorse.TXPipe processes shear and photometric catalogs through sample selection, map generation, two-point measurements (real and Fourier space), covariance estimation, theory comparison, and diagnostics.All stages are ceci `PipelineStage` subclasses; for ceci conventions see the `ceci` skill.For NERSC job submission, see the `nersc` skill.Key library dependencies: NaMaster (`namaster` skill) for Fourier C_ℓ measurements and covariance; CCL (`ccl` skill) for theory predictions; Firecrown (`firecrown` skill) is used internally by theory/blinding stages and consumes TXPipe's sacc output for parameter inference.## Pipeline phases (in order)1. **Ingestion** — `TXIngestDataPreview02`, `TXCosmoDC2Mock`, etc. — source-specific; using the wrong ingester silently reads wrong columns2. **Photo-z** — RAIL stages (`PZEstimatorLens/Source`, `PZRailSummarizeLens/Source`); must produce `QPNOfZFile` before 2pt3. **Selection** — `TXSourceSelectorMetadetect/Metacal/Lensfit/HSC` + `TXSourceTomography`; `TXMeanLensSelector` for lenses4. **Calibration** — `TXShearCalibration` then `TXTracerMetadata` (both required; calibration must precede tomography)5. **Masks** — `TXSimpleMask` or `TXCustomMask`; nside must match map nside everywhere6. **Maps** — `TXSourceMaps`, `TXLensMaps`, `TXAuxiliarySourceMaps/LensMaps`, `TXLSSWeights`7. **Noise maps** — `TXSourceNoiseMaps` (~30 realisations), `TXLensNoiseMaps` (~5); required for covariance8. **Two-point real** — `TXTwoPoint` (TreeCorr; ξ±, γ_t, w(θ)); uses `TXJackknifeCenters` for jackknife cov9. **Two-point Fourier** — `TXTwoPointFourier` (NaMaster; C_ℓ for shear-shear, shear-pos, pos-pos; see `namaster` skill)10. **Covariance** — `TXFourierNamasterCovariance` / `TXRealNamasterCovariance` (expensive; use `TXFourierGaussianCovariance` for quick tests; see `namaster` skill)11. **Theory & blinding** — `TXTwoPointTheoryReal/Fourier` (CCL; see `ccl` skill); `TXBlinding` (Firecrown internally; see `firecrown` skill)12. **Diagnostics** — `TXPSFDiagnostics`, `TXRoweStatistics`, `TXTauStatistics`, `TXSourceDiagnosticPlots`, `TXTwoPointPlots`The `examples/metadetect/` pipeline is the canonical full-pipeline reference.## Reference| Topic | Reference ||---|---|| Pipeline phases and stage names | [`references/txpipe-stages.md`](references/txpipe-stages.md) || Key file types, pipeline YAML structure, example pipelines, gotchas | [`references/txpipe-pipeline.md`](references/txpipe-pipeline.md) |

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