AI4S Skills

---
name: ai4s-agent
description: Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.
---

# AI4S Agent (meta-skill)

## Overview

Top-level entry point for the AI4S research stack. This skill contains **no work of its own** — its only job is to call four downstream skills in the right order, with the right slug, and reuse intermediate artifacts by path convention.

```
direction → research-explorer → topic
topic     → literature-survey  (60+ real bib, 100+ recommended)
topic     → experiment-suite   (design + code + results + figures)
topic     → paper-writer       (assembles into 200+ cite PDF)
```

Each downstream skill is **already single-stage and self-sufficient**: its agent loads that skill's `SKILL.md` and produces the full final-quality artifact directly. There is no skeleton/enrichment split. This meta-skill only handles ordering, the path convention, and disclosure consistency.

## When to use

- User asks for "a paper on X" or "research package on X" and wants the whole stack run end to end.
- User wants to compare what each skill produces — useful for developing or debugging the pipeline itself.

## When NOT to use

- User wants to run only one stage (e.g. only the literature survey) → invoke that skill directly.
- User wants only topic exploration → invoke `research-explorer` directly.

## The slug contract

Every skill computes the same slug from the same topic string:

```python
import re, hashlib
def slug(t):
    n = re.sub(r'[\s_]+', '-', re.sub(r'[^\w\s-]', '', t.lower().strip())).strip('-')[:40].rstrip('-')
    h = hashlib.sha1(t.encode()).hexdigest()[:8]
    return f"{n}-{h}"
```

Use the **same string** across all four skills. If the user provides a direction (not a topic), `research-explorer` runs against the direction; once a topic is chosen, the topic becomes the slug input for the remaining three.

## Workflow

### Step 1 — Understand the user's starting point

- **Direction** ("transformer time series forecasting") — start at `research-explorer`, pick a topic from its `research_exploration.md`, then proceed.
- **Topic** ("Transformer-based long-horizon forecasting with patch tokenisation") — skip `research-explorer`; go straight to the parallel branch (literature-survey, experiment-suite, paper-writer).