fidelity-validation

fidelity-validation is a skill for Claude Code from prime-radiant-inc/greenfield. It costs 40 tokens per session (1,655 once invoked), scanned A, original, Apache-2.0.

A comparison check that tests whether cleaned specifications still contain the important details from the original specifications.

In plain words
What is it for?
Use it after sanitizing and auditing specifications to find missing behaviors, changed constants, vague wording, and incomplete decision paths.
Why use it?
Cleaning requirements can accidentally remove features, limits, error cases, or exact rules that an implementer needs.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the greenfield plugin — 22 skills, 2 commands, 2 agents shipped together

Good fit Use it after sanitizing and auditing specifications to find missing behaviors, changed constants, vague wording, and incomplete decision paths.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/prime-radiant-inc/greenfield/fidelity-validation
Install

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.

Any agent
npx skills add prime-radiant-inc/greenfield --skill fidelity-validation
Clone the repo
git clone --depth 1 https://github.com/prime-radiant-inc/greenfield

Made for: Claude Code.

Or install greenfield, the plugin that ships this one along with the rest of its 22 skills, 2 commands, 2 agents.

Wrote 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.

agentmods badge for fidelity-validation

README.md
[![agentmods](https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/fidelity-validation/github.svg)](https://agentmods.dev/skills/prime-radiant-inc/greenfield/fidelity-validation)
Your own site
<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.

agentmods 80×15 button for fidelity-validation

Your own site · 80×15
<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>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,655 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash 33f469caccc4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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.

skills/fidelity-validation/SKILL.md · 147 lines

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:

  1. Sanitization (Layer 5) is complete
  2. Contamination audit (Layer 6) passes — output specs are confirmed free of source identifiers
  3. 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:

  1. All numeric constants — timeouts, limits, sizes, counts, thresholds, intervals, percentages
  2. All behavioral rules — "when X happens, the system does Y"
  3. All error conditions — what errors occur and how they're handled
  4. All state transitions — state machines, mode changes, lifecycle events
  5. All decision trees — if/else branches, priority orders, cascades
  6. All features — distinct capabilities described

Read the full file on GitHub · 147 lines

Changes

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.

  1. 9d ago First seen · 147 lines · 40 tokens per session scan A 33f469caccc4

Subscribe to this mod's changes

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.