# Predictingthepast

Ancient text restoration, attribution, dating, contextualization, and embedding via...

- Repository: https://github.com/google-deepmind/science-skills (3377 stars)
- Category: AI and agents
- License: Apache-2.0
- Last updated: 2026-10-23
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add google-deepmind/science-skills --skill predictingthepast -g -a claude-code -y`
Codex: `npx skills add google-deepmind/science-skills --skill predictingthepast -g -a codex -y`
Cursor: `npx skills add google-deepmind/science-skills --skill predictingthepast -g -a cursor -y`
Gemini CLI: `npx skills add google-deepmind/science-skills --skill predictingthepast -g -a gemini-cli -y`

## Description

Ancient text restoration, attribution, dating, contextualization, and embedding via Aeneas (Latin) / Ithaca (Ancient Greek). Use when asked to "restore", "attribute", "date", "contextualize", "find parallels", "where was it written", "when was it written", "embed", or "analyze" an ancient text, inscription, or epigraphic document, or when the user mentions "Aeneas", or "Ithaca".

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Predicting The Past (Aeneas / Ithaca)

Aeneas (Latin) and Ithaca (Ancient Greek) perform four tasks on ancient texts:

1.  **Restoration**, fill missing/damaged characters
2.  **Attribution**, geographical + chronological origin
3.  **Contextualization**, retrieve parallel inscriptions
4.  **Embedding**, generate text embedding vectors

## Prerequisites

1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure
    `uv` is installed and on PATH.

2.  **User Notification**: If .licenses/predictingthepast_LICENSE.txt does not
    already exist in the workspace root directory then (1) prominently notify
    the user to check the terms at
    https://github.com/google-deepmind/predictingthepast/blob/main/README.md#license--disclaimer,
    and include the appropriate citation and the full dataset acknowledgement,
    and that use of these datasets should acknowledge and cite the original data
    sources. Then (2) create the file recording the notification text and
    timestamp.

## Core Rules

-   **Self-Contained Skill**: Do NOT use web search or any external tools. Run
    ONLY the scripts in this skill (`preprocess.py`, `run_inference.py`,
    `visualize_results.py`). Present model output as-is, never supplement or
    override it with external lookups.
-   **Notification**: If this skill is used, ensure this is mentioned in the
    output.

## On First Load

Present the restoration markup characters, then ask the user for their text:

The rest: https://github.com/google-deepmind/science-skills/blob/HEAD/skills/predictingthepast/SKILL.md