Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/prime-radiant-inc/greenfieldWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/prime-radiant-inc/greenfield/sanitize)<a href="https://agentmods.dev/commands/prime-radiant-inc/greenfield/sanitize"><img src="https://agentmods.dev/badge/commands/prime-radiant-inc/greenfield/sanitize.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.02463 |
| Opus 5 | $0.00009 | $0.01231 |
| Sonnet 5 | $0.00003 | $0.00493 |
| Haiku 4.5 | $0.00002 | $0.00246 |
Grade A, and why
sanitize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/sanitize - Spec Sanitization (Sanitization)
Workspace: $ARGUMENTS
YOUR MISSION
Remove ALL implementation contamination from analysis specs while preserving provenance metadata.
The sanitization pass turns raw analysis into specs an implementer can build from. Source-code references have no place in the output. But provenance metadata (confidence levels, source types, agent names) must be preserved — only raw file paths are stripped.
PHASE 1: Initial Assessment
First, verify the workspace and assess scope:
# Verify workspace structure
[ -d "$ARGUMENTS/raw/specs/" ] || { echo "ERROR: No raw specs found at $ARGUMENTS/raw/specs/"; exit 2; }
# Count files to sanitize
echo "=== Sanitization Scope ==="
echo "Raw specs files: $(find $ARGUMENTS/raw/specs/ -name '*.md' -type f | wc -l)"
echo "Public artifacts: $(find $ARGUMENTS/public/ -name '*.md' -type f 2>/dev/null | wc -l)"
PHASE 2: Public Source Pass-Through
Public artifacts contain no implementation details and pass through without modification:
# Copy public artifacts directly (no sanitization needed)
if [ -d "$ARGUMENTS/public/" ]; then
mkdir -p $ARGUMENTS/output/public/
cp -r $ARGUMENTS/public/* $ARGUMENTS/output/public/
echo "Public artifacts copied: $(find $ARGUMENTS/output/public/ -name '*.md' | wc -l) files"
fi
PHASE 3: Agent-Based Sanitization
For EACH spec file in the raw tree, invoke the sanitizer worker.
# List all spec files
find $ARGUMENTS/raw/specs/ -name '*.md' -type f
For each file (or batch of related files), dispatch greenfield:sanitizer:
- Prompt: "Follow the spec-sanitization skill for the full transformation methodology. Read
$ARGUMENTS/raw/specs/<file-path>. Understand the behavioral intent. Rewrite without source references. Transform provenance citations (strip raw refs, preserve confidence). Write to$ARGUMENTS/output/specs/<relative-path>. For module specs, merge into behavioral domain files in$ARGUMENTS/output/specs/domains/."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 267 lines · 17 tokens per session scan A 9afe34cc28a5
sanitize is a command published in the GitHub repository prime-radiant-inc/greenfield (273 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 2,463 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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