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.
npx skills add prime-radiant-inc/greenfield --skill spec-sanitizationgit 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/skills/prime-radiant-inc/greenfield/spec-sanitization)<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/spec-sanitization"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/spec-sanitization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/spec-sanitization"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/spec-sanitization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.05782 |
| Opus 5 | $0.00015 | $0.02891 |
| Sonnet 5 | $0.00006 | $0.01156 |
| Haiku 4.5 | $0.00003 | $0.00578 |
Grade A, and why
spec-sanitization 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 10d 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 — 477 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Sanitization
The sanitization pass turns raw analysis into specs an implementer can build from.
Why This Exists
Analysts read source code, binaries, and runtime behavior. Even with good intentions, they leak implementation details:
- Function names from source (minified or not)
- Variable and class names from source
- Code structure ("function X calls Y which calls Z")
- Line numbers and file locations
- Raw file paths (
workspace/raw/source/analysis/chunk-42.md:67)
These have no place in the output specs. Your job: READ each spec, UNDERSTAND the behavior, REWRITE without source references, TRANSFORM provenance citations.
The Rewrite Rule
You must not copy text from raw specs into output specs. Not sentences, not paragraphs, not sections. Read the raw specs to understand the behavior, then write a fresh output spec from your understanding.
Why? Raw specs have source code identifiers woven into every sentence — minified names (k0, Wq, z1), internal function signatures (Pn(a, b, c)), and numeric implementation constants. Find-and-replace cannot catch them all; many internal identifiers read like plain English (shouldRetryOnTimeout, evict_stale_connections). A paraphrase that preserves the original's structure is still leaking the original's design. The only reliable approach is to never copy the text at all.
Process per file:
- Read the raw spec end-to-end
- Close it (do not refer back to it while writing)
- Write the output spec from your understanding of the behavior
- Use only: behavioral descriptions, user-facing identifiers (env vars, CLI flags, config keys, protocol fields), and numeric constants (timeouts, limits, sizes)
- For any concept you could not translate into behavioral language — because you don't understand what it does — add:
[UNCERTAINTY: U-{DOMAIN}-{NNN}] {what the raw spec said, in behavioral terms as best you can} — behavioral purpose could not be determined from available analysis.
Never preserve implementation jargon in slightly-reworded form. "validator.Exists() is called" rewritten as "the exists check runs" is still jargon — neither you nor the implementer knows what it means. Either translate it to behavior ("verifies the value exists in the constrained list") or flag it as uncertain.
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.
- 10d ago First seen · 477 lines · 31 tokens per session scan A 6aacb5056beb
spec-sanitization is a skill published in the GitHub repository prime-radiant-inc/greenfield (275 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 5,782 once invoked, about $0.0002 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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