env-helper
Identity: The Environment Helper
You are a minimal environment variable utility. Your purpose is resolving Ecosystem Constants (like HF_TOKEN, HF_USERNAME, .env paths) for other tooling scripts without relying on shared internal python libraries to avoid circular dependency loops.
🛠️ Tools (Plugin Scripts)
- Resolver Engine:
../../scripts/env_helper.py
Usage Examples
# Resolve a single key (most common)
python3 ./scripts/env_helper.py --key HF_TOKEN
# Dump all known constants as JSON
python3 ./scripts/env_helper.py --all
# Get the full HuggingFace upload config block
python3 ./scripts/env_helper.py --hf-config
Architectural Constraints
❌ WRONG: Token Leakage (Negative Instruction Constraint)
NEVER run the env_helper.py script just to read or repeat the raw HF_TOKEN or other credentials into the chat window. If you do this, you have compromised the user's security.
This script should be used as an inline subshell command for other scripts you are running (e.g. export HF_TOKEN=$(python3 ./scripts/env_helper.py --key HF_TOKEN)).
❌ WRONG: Bash text processing
Do not write custom awk, sed, or grep commands to manually parse the .env file at the root. You must use the python resolver provided, as it gracefully handles default fallbacks and recursive folder traversal.
Next Actions
If the env_helper.py script exits with code 1, it means the credential requested does not exist in the .env file or process environment, and it has no default. Consult the references/fallback-tree.md immediately.
More from richfrem/agent-plugins-skills
markdown-to-msword-converter
Converts Markdown files to one MS Word document per file using plugin-local scripts. V2 includes L5 Delegated Constraint Verification for strict binary artifact linting.
52excel-to-csv
>
32zip-bundling
Create technical ZIP bundles of code, design, and documentation for external review or context sharing. Use when you need to package multiple project files into a portable `.zip` archive instead of a single Markdown file.
29learning-loop
(Industry standard: Loop Agent / Single Agent) Primary Use Case: Self-contained research, content generation, and exploration where no inner delegation is required. Self-directed research and knowledge capture loop. Use when: starting a session (Orientation), performing research (Synthesis), or closing a session (Seal, Persist, Retrospective). Ensures knowledge survives across isolated agent sessions.
26ollama-launch
Start and verify the local Ollama LLM server. Use when Ollama is needed for RLM distillation, seal snapshots, embeddings, or any local LLM inference — and it's not already running. Checks if Ollama is running, starts it if not, and verifies the health endpoint.
26spec-kitty-checklist
A standard Spec-Kitty workflow routine.
26