# How to Use Stop Slop Reference Files (phrases.md and structures.md)

> Learn how to use Stop Slop reference files like phrases.md and structures.md to prune filler phrases and structural patterns. Apply fixes for cleaner prose with your language models.

- Repository: [Hardik Pandya/stop-slop](https://github.com/hardikpandya/stop-slop)
- Tags: how-to-guide
- Published: 2026-05-26

---

**Stop Slop reference files are markdown lookup tables loaded via [`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md) that tell language models which filler phrases and structural patterns to prune from text, applying prescribed fixes until the prose is clean.**

The **hardikpandya/stop-slop** repository ships a declarative "skill" for cleaning AI-generated writing. At its core, two markdown files—[`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) and [`structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/structures.md)—provide human-readable, version-controlled guidance that any compatible environment can consume to enforce direct, human-like prose.

## What Are Stop Slop Reference Files?

Stop Slop uses static markdown files as configuration rather than code. These files live in the `references/` directory and define the exact patterns the model must target.

### phrases.md

[`references/phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/phrases.md) contains a curated list of filler phrases, weak adverbs, and meta-commentary that should be removed or rewritten. Each entry pairs a prohibited construction with a concise remediation instruction.

### structures.md

[`references/structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/structures.md) catalogs recurring sentence-level rhetorical patterns—such as binary contrasts ("Not because X, because Y") and negative listings—that force the model to rewrite indirect setups into direct statements.

## How the Reference Files Work

Both files are referenced from the main skill definition [`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md) at the repository root. The first core rule in [`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md) points to [`references/phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/phrases.md), while the second core rule points to [`references/structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/structures.md).

When loaded, the engine applies these rules as **lookup-style filters**:

1. **Identify a match** – The model scans input text for lines matching entries in [`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) (e.g., "Here's the thing:") or structural patterns described in [`structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/structures.md).
2. **Apply the prescribed fix** – Each entry includes an "Instead" recommendation. For binary contrasts, the instruction is "State Y directly." For filler adverbs, it is "Kill the adverb."
3. **Iterate** – The model re-runs the check until no further entries apply, guaranteeing a comprehensive clean-up pass.

## Loading Reference Files in Your Projects

Because the files are plain markdown, you can ingest them into any workflow that consumes text: Python prompt builders, Claude skills, or shell scripts.

### Python Implementation

Fetch the raw files and embed them directly into a system prompt:

```python
import requests

BASE = "https://raw.githubusercontent.com/hardikpandya/stop-slop/main"

def load_md(path: str) -> str:
    resp = requests.get(f"{BASE}/{path}")
    resp.raise_for_status()
    return resp.text

phrases_md = load_md("references/phrases.md")
structures_md = load_md("references/structures.md")

system_prompt = f"""You are a text-cleaner. Follow the rules defined below.

--- PHRASES TO REMOVE ---
{phrases_md}

--- STRUCTURAL PATTERNS TO AVOID ---
{structures_md}

Rewrite any input text accordingly."""

```

Send `system_prompt` to Claude, OpenAI, or any LLM that respects system instructions to apply the Stop Slop rules dynamically.

### Claude Skill Usage

Place the repository folder where Claude can access it, then reference the skill:

```xml
<skill>
  name: stop-slop
  path: /path/to/stop-slop
</skill>

```

With the skill loaded, Claude automatically reads [`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md), follows the links to [`references/phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/phrases.md) and [`references/structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/structures.md), and applies the transformations. For example, given the input:

> "Here's the thing: building products is hard. Not because the tech is complex, because people are complex."

Claude outputs:

> "Building products is hard. Technology is manageable. People aren't."

See [`references/examples.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/examples.md) in the repository for additional before-and-after samples.

### Command-Line Processing

For quick prototyping, download the files and apply phrase filtering with standard Unix tools:

```bash
curl -L https://raw.githubusercontent.com/hardikpandya/stop-slop/main/references/phrases.md -o phrases.md
curl -L https://raw.githubusercontent.com/hardikpandya/stop-slop/main/references/structures.md -o structures.md

# Basic phrase removal using sed (demo only)

sed -e '/Here’s the thing:/d' -e '/Full stop\./d' input.txt > cleaned.txt

```

While structural pattern matching requires a proper parser, the phrase list from [`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) can be processed with simple text manipulation for rapid testing.

## Summary

- **Stop Slop reference files** ([`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) and [`structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/structures.md)) provide declarative, markdown-based rules for text cleanup.
- **[`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md)** serves as the entry point that links to these reference files, creating a portable skill definition.
- The system uses a **three-step lookup filter**: identify matches, apply fixes, and iterate until clean.
- Being plain markdown, the files integrate with Python scripts, Claude skills, and command-line workflows without requiring code execution.

## Frequently Asked Questions

### What is the difference between phrases.md and structures.md?

[`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) targets specific lexical items—filler phrases like "Here's the thing" or weak adverbs like "very"—and instructs the model to delete or replace them. [`structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/structures.md) targets syntactic patterns, such as binary contrasts or rhetorical negations, and instructs the model to rewrite the entire sentence structure into a direct statement.

### How do I add custom phrases to Stop Slop?

Edit [`references/phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/phrases.md) or [`references/structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/structures.md) directly. Because the skill logic remains untouched in [`SKILL.md`](https://github.com/hardikpandya/stop-slop/blob/main/SKILL.md), you can add new rows to the markdown tables without modifying any code. The changes take effect the next time the skill is loaded, whether in Claude or a custom script that reads the files.

### Can I use Stop Slop reference files with GPT-4 or other LLMs?

Yes. Since the reference files are plain text, you can concatenate [`phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/phrases.md) and [`structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/structures.md) into the system prompt of any LLM that follows instructions, including GPT-4, Gemini, or local models. The Python example above demonstrates fetching the files and formatting them for arbitrary APIs.

### Where are the Stop Slop reference files located in the repository?

The files reside in the `references/` directory at the root of the `hardikpandya/stop-slop` repository. [`references/phrases.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/phrases.md) contains the banned phrase list, [`references/structures.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/structures.md) contains the structural patterns, and [`references/examples.md`](https://github.com/hardikpandya/stop-slop/blob/main/references/examples.md) provides sample transformations for testing.