prompt-engineering-inconsistent-outputs
Sub-skill of prompt-engineering: Inconsistent Outputs (+2).
Best use case
prompt-engineering-inconsistent-outputs is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of prompt-engineering: Inconsistent Outputs (+2).
Teams using prompt-engineering-inconsistent-outputs should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/inconsistent-outputs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How prompt-engineering-inconsistent-outputs Compares
| Feature / Agent | prompt-engineering-inconsistent-outputs | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of prompt-engineering: Inconsistent Outputs (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Inconsistent Outputs (+2)
## Inconsistent Outputs
```python
# Lower temperature for consistency
response = client.chat.completions.create(
model="gpt-4",
messages=messages,
temperature=0.1 # Lower = more consistent
)
# Or use seed for reproducibility
response = client.chat.completions.create(
model="gpt-4",
messages=messages,
seed=42
)
```
## Outputs Too Long/Short
```python
# Control length explicitly
prompt = """
Provide a summary in exactly 3 sentences.
Do not exceed 100 words.
"""
# Or use max_tokens
response = client.chat.completions.create(
model="gpt-4",
messages=messages,
max_tokens=150
)
```
## Wrong Format
```python
# Be very explicit about format
prompt = """
Return ONLY a JSON object. No explanation, no markdown.
{
"key": "value"
}
"""
# Validate and retry
def get_json_response(prompt, max_retries=3):
for attempt in range(max_retries):
response = llm(prompt)
try:
return json.loads(response)
except json.JSONDecodeError:
prompt = f"Your response was not valid JSON. Try again.\n\n{prompt}"
raise ValueError("Failed to get valid JSON")
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