dyz-gongwen-skills
公文写作 Skills|AI 公文写作助手:防编造、守保密、GB/T 9704 一键排版,覆盖 22 种文书,支持 Claude Code / Codex / Cursor
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Fiskwise knowledge pack for survey indices using sdmTMB
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Read the full README ↗Version 0.2.32 (2026-11-13)
Teach your AI coding agent to build a spatiotemporal survey index for stock assessment — for any species, on your own machine.
index-wise is a knowledge pack that turns a general coding agent (Claude Code, Codex, Cursor, Gemini CLI, Mistral, …) into a competent assistant for building sdmTMB (Anderson et al., 2025) survey indices from IMR bottom-trawl data, reproducing the method of Vihtakari et al. (2026, ICES Journal of Marine Science).
Tell your agent which species you want an index for, and it will:
docs/, data/, R/, figures/, ai/, logs/, config/).It is not a trained model. Your data never leaves your machine and never enters any model's weights. The agent simply reads this repo while it helps you. See Privacy.
index-wise owns the sdmTMB index-building workflow. BAIT handles Biotic data access, the database, privacy, maps, and life-history. Install BAIT on demand before compiling index data from Biotic; installing index-wise does not install or refresh the database.
You may install and update packs through Fiskwise's managed lifecycle, or use the standalone
pack skills in this repository. Shared writing/reporting dependencies are installed on demand;
they are not a prerequisite for the index-wise pack itself.
The versioned assessment index also feeds survey indices of spict-wise and gadget-wise models.
Use fiskwise-workflow for requests spanning packs. For managed R tasks, always use
r-code-style. The coordinator's lifecycle skills are fiskwise-install,
fiskwise-update, and fiskwise-uninstall.
install https://github.com/DeepWaterIMR/BAIT
This repo is public and contains instructions only — never data:
data/, logs/, and ai/review/ are git-ignored.~/IMR_biotic_BES_database/).install https://github.com/DeepWaterIMR/BAIT. Database setup is a separate choice.install https://github.com/DeepWaterIMR/index-wise
The agent runs index-install: a privacy check → cloning index-wise → installing the skills globally → verifying BAIT and the R packages (sdmTMB, sdmTMBexperiments, ggOceanMaps).Let's make a biomass index for snabeluer (beaked redfish) using all bottom trawl data
collected during surveys, using index-wise.
The agent runs the questionnaire, plans, scaffolds a project, and drives the four-step workflow.| Step | Skill |
|---|---|
| Scaffold a project (questionnaire + plan) | index-new-project |
| Create valid study-region polygons | index-make-regions |
| Ask about or review an sdmTMB index in any project | index-sdmtmb |
| 1. Compile & report the data | index-compile-data |
| 2. Fit the first feasible model | index-fit-model |
| 3. Validate / select the model | index-validate-model |
| 4. Final report + extensions | index-final-report |
| CPUE — prepare logbook / sales-note records | index-cpue-data |
| CPUE — standardise and export (glmmTMB, mgcv, sdmTMB) | index-cpue-model |
The two CPUE skills are an optional track for a commercial CPUE index beside the survey index. Logbook and sales-note data are not Biotic data; the background is in knowledge/cpue.md and knowledge/cpue-models.md, and examples/snowcrab-ers-cpue/ runs all three engines on synthetic data with a known trend.
Each step's document lives in project-template/docs/ and is index-wise's own, evolving implementation — improve it directly as the routine matures. knowledge/workflow.md points to the (IMR-internal) background material the method was originally distilled from, if you want the history.
Long renders are compiled with index-render in a screen session with a log in logs/.
This is the beginning of the README. Read the rest at the original. Read the full README ↗