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 fidelity-validationgit 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/fidelity-validation)<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/fidelity-validation"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/fidelity-validation/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/fidelity-validation"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/fidelity-validation.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 | $0.00040 | $0.01655 |
| Opus 5 | $0.00020 | $0.00827 |
| Sonnet 5 | $0.00008 | $0.00331 |
| Haiku 4.5 | $0.00004 | $0.00166 |
Grade A, and why
fidelity-validation 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fidelity Validation
Sanitization removes source code identifiers. But aggressive sanitization can also remove behavioral detail that an implementor needs. This skill detects information loss.
Why This Exists
The sanitization pass rewrites raw specs into output specs. Each rewrite risks:
- Dropped behaviors: A feature or edge case described in the raw specs that doesn't appear in the output specs
- Lost constants: A numeric threshold, timeout, limit, or size that was accidentally removed or changed during rewriting
- Diluted precision: A specific behavioral rule replaced with vague language ("the system handles errors" instead of "the system retries with configured backoff — N attempts, base delay, maximum delay, and jitter")
- Missing decision trees: A conditional behavior with multiple branches that was simplified to just the happy path
- Dropped error conditions: Error handling that was described in the raw specs but omitted from the output specs
- Feature gaps: Entire features or sub-features present in the raw specs but missing from the output domain spec
When to Run
Run this AFTER:
- Sanitization (Layer 5) is complete
- Contamination audit (Layer 6) passes — output specs are confirmed free of source identifiers
- All remediation/rewriting rounds are done
This is the final quality gate before handing the output to the implementer.
The Principle
Every behavioral claim in the raw specs must have a corresponding claim in the output specs — with equal or greater precision.
The output specs may use different words (that's the point of sanitization), but it must convey the same behavior. If the raw spec says "retry N times with a specific base, cap, and jitter", the output specs must say the same — not just "the system retries on failure."
Process
Phase 1: Build the Source Claim Inventory
For each raw module spec (workspace/raw/specs/modules/*.md), extract:
- All numeric constants — timeouts, limits, sizes, counts, thresholds, intervals, percentages
- All behavioral rules — "when X happens, the system does Y"
- All error conditions — what errors occur and how they're handled
- All state transitions — state machines, mode changes, lifecycle events
- All decision trees — if/else branches, priority orders, cascades
- All features — distinct capabilities described
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 · 147 lines · 40 tokens per session scan A 33f469caccc4
fidelity-validation is a skill published in the GitHub repository prime-radiant-inc/greenfield (273 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 40 tokens to every session and 1,655 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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