Request or Build a Missing Skill

The user needs a DSPy capability that doesn't have a skill yet. Help them contribute it or request it.

Step 1: Confirm the gap

If $ARGUMENTS is provided, use it. Otherwise ask: "What DSPy capability do you need that isn't covered by an existing skill?"

Verify this is something DSPy actually supports. If it's outside DSPy's scope entirely (e.g., "build a React frontend"), say so and suggest appropriate tools instead. Do not proceed with a skill request for non-DSPy capabilities.

Summarize back to the user:

• What they need: one sentence
• DSPy features involved: which DSPy modules, integrations, or patterns are relevant

Step 2: Choose a path

Ask the user:

Would you like to:

1. Build the skill — I'll help you create it following the repo conventions and prepare a PR
2. Request the skill — I'll draft a GitHub issue so the maintainers know it's needed

Path A: Build the skill

Create the skill directory

Create skills/ai-<problem-name>/SKILL.md where <problem-name> describes the user's problem (not the DSPy module). Follow these conventions from this repo:

• Problem-first naming: Name after what the user is solving, with ai- prefix (e.g., ai-observability not dspy-phoenix)
• Web developer language: Use phrases developers actually say, not ML jargon
• Provider-agnostic: Don't hardcode specific LM providers

Write the SKILL.md

Use this structure:

---
name: ai-<problem-name>
description: "<What problem it solves>. Use when <trigger phrases the user would say>."
---

Body should follow the pattern used by other skills in this repo:

1. A step to gather requirements (ask the user 2-4 questions about their specific needs)
2. Implementation steps with code examples using DSPy
3. A verification/testing step
4. Next steps pointing to related skills (e.g., /ai-improving-accuracy, /ai-serving-apis)

Keep the SKILL.md under 500 lines. If more detail is needed, create a reference.md or examples.md alongside it.

Reference docs/dspy-reference.md for correct DSPy API usage (modules, optimizers, signatures).

Prepare the PR

After creating the skill files:

1. Update README.md — add a row to the problem catalog table in the appropriate position
2. Create a branch named add-ai-<problem-name>
3. Commit with message: Add ai-<problem-name> skill
4. Open a PR to lebsral/DSPy-Programming-not-prompting-LMs-skills with:
   • Title: Add ai-<problem-name> skill
   • Body: What problem it solves, what DSPy features it uses, and an example invocation

Path B: Request the skill

Draft a GitHub issue for lebsral/DSPy-Programming-not-prompting-LMs-skills with this format:

Title: Skill request: ai-<problem-name>

Body:

## Problem
<What the user is trying to do, in their words>

## DSPy capability
<Which DSPy modules, integrations, or patterns would power this>

## Example use case
<A concrete scenario where this skill would help>

## Suggested trigger phrases
<2-3 phrases a developer might say that should route to this skill>

Use gh issue create to submit it, assigning it to the repo owner.