AI agent skill · by @WILLOSCAR

Taxonomy Builder

Build a 2+ level taxonomy (`outline/taxonomy.yml`) from a core paper set and scope constraints, with short descriptions per node.

Archived 2026-10-23 · Source updated 2026-10-05. Check the original repository for the latest version.

SKILL.md instructions

# Taxonomy Builder (router, compatibility mode)

## Triggers & routing

- **Trigger**: taxonomy, taxonomy builder, 分类, 主题树, taxonomy.yml.
- **Use when**: survey/snapshot 的结构阶段（NO PROSE），已有 `papers/core_set.csv`，需要生成可映射且读者友好的主题结构。
- **Skip if**: 已经有批准过且可映射的 taxonomy（不要无意义重构）。
- **Network**: none.
- **Guardrail**: 避免泛化占位桶；保持 2+ 层且每节点有具体描述。


Build `outline/taxonomy.yml` from `papers/core_set.csv`.

P0 compatibility note:
- The output contract stays the same (`outline/taxonomy.yml`, YAML list, >=2 levels, concrete descriptions).
- Curated domain taxonomies now live in `assets/domain_packs/*.yaml` instead of Python prose.
- `scripts/run.py` stays a deterministic scaffold/helper: detect domain pack -> load pack when available -> otherwise fall back to the generic builder.

## Load Order

1. `references/overview.md`
2. `references/taxonomy_principles.md`
3. If a domain pack applies, read its `references/domain_pack_<domain>.md` and `assets/domain_packs/<domain>.yaml`
4. Otherwise read `references/archetypes_generic.md`
5. Calibrate naming/description quality with `references/examples_good.md` and `references/examples_bad.md`

Current compatibility packs:
- `llm_agents`
- `gen_image`
- `embodied_ai`
- `rag_evaluation`

## Explicit refinement marker

Create `outline/taxonomy.refined.ok` only after reviewing a manually refined taxonomy. The marker is honored only while it is newer than the taxonomy, its upstream evidence, and the generator; stale markers are removed and the prior taxonomy is backed up before regeneration.

## Inputs

- `papers/core_set.csv` (required)
- Optional: `papers/papers_dedup.jsonl`
- Optional: `DECISIONS.md`, `GOAL.md`, `queries.md`

## Outputs

- `outline/taxonomy.yml`

## Asset contract

- `assets/taxonomy_schema.json`: machine-readable shape for domain packs / output expectations
- `assets/domain_packs/*.yaml`: compatibility domain packs for supported domains

## Script role

Use `scripts/run.py` only for deterministic help:
- never overwrite non-placeholder user taxonomy
- preserve current CLI flags / output path
- load a supported domain taxonomy only when `GOAL.md` / `queries.md` explicitly match its detection contract
- keep the generic fallback builder for non-packed domains

## When to refine manually

Refine the generated taxonomy before marking the unit `DONE` if:
- top-level buckets feel like keyword clusters instead of chapter-level questions
- leaf names are generic (`Overview`, `Benchmarks`, `Open Problems`, `Misc`)
- descriptions lack scope cues or representative paper anchors
- domain detection chose the wrong pack

## Quick start

- `uv run python .codex/skills/taxonomy-builder/scripts/run.py --help`
- `uv run python .codex/skills/taxonomy-builder/scripts/run.py --workspace <workspace>`


## Execution notes

When running in compatibility mode, `scripts/run.py` currently reads:
- `papers/core_set.csv` as the required corpus input
  - `papers/papers_dedup.jsonl` when present for generic corpus signals
  - `GOAL.md` and `queries.md` as the authoritative domain-pack selection intent; corpus term co-occurrence cannot override them

## Script

### Quick Start

- `uv run python .codex/skills/taxonomy-builder/scripts/run.py --workspace <workspace>`

### All Options

- `--workspace <dir>`
- `--top-k <int>`
- `--min-freq <int>`
- `--unit-id <id>`
- `--inputs <a;b;...>`
- `--outputs <a;b;...>`
- `--checkpoint <C*>`

### Examples

- `uv run python .codex/skills/taxonomy-builder/scripts/run.py --workspace <workspace>`

## Troubleshooting

- If the wrong domain pack is chosen, inspect `GOAL.md`, `queries.md`, and the pack `detect` rules before changing Python.
- If `outline/taxonomy.yml` already contains a real non-placeholder taxonomy, the script intentionally returns without overwriting it.
- If no pack matches, the script falls back to the generic builder.