PJuniszewski Context Guard Skill
Epistemic safety analysis for JSON data in prompts. Prevents LLMs from reasoning with unjustified certainty when input data is incomplete.
Features
- Lossless reduction - Minify, columnar transform, remove nulls
- Token counting - API or heuristic fallback
- Decision engine - ALLOW / SAMPLE / BLOCK
- Intelligent trimming - First + last + evenly-spaced sampling
- Forensic detection - Warns when specific record queries detected
Usage
When /guard is invoked, execute the guard script:
For file paths:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/guard_cmd.py" "<file_path>" [options]
For inline JSON data:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/guard_cmd.py" - [options] <<'GUARD_INPUT'
<json_data>
GUARD_INPUT
Options
| Option | Description |
|---|---|
--mode |
analysis|summary|forensics (default: auto-detect) |
--force |
Bypass blocks, emit warnings only |
--allow-sampling |
Permit sampling for forensic queries |
--no-reduce |
Skip lossless reduction phase |
--budget-tokens N |
Token budget (default: 3500) |
--print-only |
Output report only, never auto-send |
--json |
Output result as JSON |
Semantic Modes
| Mode | Sampling | Use Case |
|---|---|---|
analysis |
Allowed | "What categories exist?", "Price range?" |
summary |
Aggressive | "Describe the data structure" |
forensics |
BLOCKED | "Why did request id=X fail?" |
Output
============================================================
CONTEXT GUARD ANALYSIS
============================================================
Decision: [OK] ALLOW | [~] SAMPLE | [X] BLOCK
Mode: analysis | summary | forensics
TOKEN ANALYSIS:
Original: 5,234 tokens
After reduce: 4,891 tokens (-343)
Budget: 3,500 tokens
============================================================
Requirements
- Python 3.8+
ANTHROPIC_API_KEYenvironment variable (for token counting)