Groq API Inference
Build and debug Groq API chat and speech workflows with low-latency routing, structured outputs, and production-safe patterns.
Description
name: Groq API Inference slug: groq-api version: 1.0.0 homepage: https://clawic.com/skills/groq-api description: Build and debug Groq API chat and speech workflows with low-latency routing, structured outputs, and production-safe patterns. changelog: Initial release with Groq API workflows, model routing guidance, and troubleshooting playbooks for chat and speech. metadata: {"clawdbot":{"emoji":"⚡","requires":{"bins":["curl","jq"],"env":["GROQ_API_KEY"]},"os":["linux","darwin","win32"]}}
Setup
On first use, read setup.md for activation preferences, credential verification, and default workflow setup.
When to Use
User needs to build, integrate, or troubleshoot Groq API inference for chat, tool calling, or speech transcription. Agent handles request shaping, model routing, failure recovery, and safe production patterns.
Architecture
Memory lives in ~/groq-api/. See memory-template.md for structure.
~/groq-api/
├── memory.md # Status, activation preference, and defaults
├── requests/ # Reusable payload snippets
├── logs/ # Optional debug snapshots
└── experiments/ # Prompt/model A-B notes
Quick Reference
Use these files as decision aids, not as static docs: pick the smallest file that resolves the current blocker.
| Topic | File |
|---|---|
| Setup process | setup.md |
| Memory template | memory-template.md |
| Request patterns | api-patterns.md |
| Model routing | model-selection.md |
| Failures and recovery | troubleshooting.md |
Core Rules
1. Verify Auth and Endpoint Before Any Work
Check GROQ_API_KEY first and use Authorization: Bearer $GROQ_API_KEY for every request. Use https://api.groq.com/openai/v1 as the base URL and confirm access with /models.
curl -s https://api.groq.com/openai/v1/models \
-H "Authorization: Bearer $GROQ_API_KEY" | jq '.data[0].id'
2. Start with a Minimal Deterministic Payload
Begin with small prompts and explicit format instructions. Add complexity only after the baseline call is stable.
3. Route by Task, Not by Habit
Use separate model choices for:
- Fast interactive chat
- High-accuracy reasoning
- Speech transcription
Choose from live /models output instead of hardcoding assumptions.
4. Design for Retry and Degradation
For 429 and 5xx, retry with exponential backoff and capped attempts. If a model is overloaded, fail over to a compatible backup model and log the swap.
5. Validate Output Before Downstream Actions
If output feeds code execution or data writes, enforce JSON schema or strict parsing before acting. Reject malformed output early.
6. Treat Speech as a Separate Reliability Path
Speech uploads have different failure modes than chat. Validate input format, check file size, and surface transcription confidence when available.
7. Keep Secrets and User Data Scoped
Never store API keys in files. Keep request logs sanitized and avoid persisting full sensitive prompts unless the user explicitly asks.
Common Traps
- Using stale model IDs copied from old examples -> call
/modelsand select available IDs at runtime. - Sending giant prompts without truncation -> latency spikes and timeout risk.
- Ignoring
429backoff guidance -> repeated failures under load. - Mixing chat and transcription assumptions -> wrong endpoint and payload format.
- Trusting free-form text for automation -> parse and validate before executing.
External Endpoints
All network traffic should be limited to these Groq endpoints for explicit inference tasks requested by the user.
| Endpoint | Data Sent | Purpose |
|---|---|---|
| https://api.groq.com/openai/v1/models | None (GET) | Discover available models |
| https://api.groq.com/openai/v1/chat/completions | Prompt messages and options | Chat completions |
| https://api.groq.com/openai/v1/audio/transcriptions | Audio file and transcription params | Speech-to-text |
No other data is sent externally.
Security & Privacy
Data that leaves your machine:
- Prompt content sent to Groq inference endpoints
- Audio content sent to Groq transcription endpoint when requested
Data that stays local:
- Workflow preferences in
~/groq-api/memory.md - Optional local debug notes in
~/groq-api/logs/
This skill does NOT:
- Store
GROQ_API_KEYin project files - Access files outside
~/groq-api/for persistence - Call undeclared third-party endpoints
- Modify itself or other skills
Trust
By using this skill, prompts and optional audio content are sent to Groq. Only install if you trust Groq with that data.
Related Skills
Install with clawhub install <slug> if user confirms:
api— reusable REST patterns, auth, and error handlingmodels— model comparison and selection heuristicsai— current AI landscape checks before implementation decisionsfine-tuning— adaptation workflows when prompting is not enoughlangchain— orchestration patterns for multi-step LLM pipelines
Feedback
- If useful:
clawhub star groq-api - Stay updated:
clawhub sync
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