governance-guardrail

governance-guardrail is a skill for Claude Code from jpantsjoha/ai-native-developer-experience. It costs 56 tokens per session (1,236 once invoked), scanned A, original, Apache-2.0.

A check that compares a proposed technology stack, data movement, cloud setup, and delivery process with the organisation’s policies, compliance rules, and security controls.

In plain words
What is it for?
Reviewing regulated or high-risk work and decisions about data classification, data location, vendors, approved technologies, security, and compliance.
Why use it?
It exposes policy gaps before architecture decisions are fixed and avoids assuming that an unverified rule is acceptable.

Skill for Claude Code

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

Part of the join-the-team plugin — 21 skills, 3 commands, 1 hook shipped together

Good fit Reviewing regulated or high-risk work and decisions about data classification, data location, vendors, approved technologies, security, and compliance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jpantsjoha/ai-native-developer-experience/governance-guardrail
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 jpantsjoha/ai-native-developer-experience --skill governance-guardrail
Clone the repo
git clone --depth 1 https://github.com/jpantsjoha/ai-native-developer-experience

Made for: Claude Code.

Or install join-the-team, the plugin that ships this one along with the rest of its 21 skills, 3 commands, 1 hook.

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 governance-guardrail

README.md
[![agentmods](https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail/github.svg)](https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail)
Your own site
<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail/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 governance-guardrail

Your own site · 80×15
<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/governance-guardrail.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,236 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.
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 $0.00056 $0.01236
Opus 5 $0.00028 $0.00618
Sonnet 5 $0.00011 $0.00247
Haiku 4.5 $0.00006 $0.00124

Measured 9d ago against content hash cb694397af28, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

governance-guardrail 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/governance-guardrail/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Governance Guardrail

A policy position the team cannot cite is a policy the team will unknowingly violate.

This skill checks alignment between what the team is building and the enterprise policies, compliance frameworks, and security controls that govern it. It never invents a policy position — it surfaces gaps as explicitly owned unknowns.

When to use

  • At R2/R3 risk classification, before architecture decisions are locked
  • When the operating profile names a governance pointer (policy doc, compliance framework, security baseline, approved-technology list)
  • Before any decision that touches data classification, residency, procurement, or approved-vendor constraints
  • As a pre-condition for adversarial-gate on high-stakes or regulated work
  • When delivery-orchestrator identifies a compliance, security, or data-handling concern

Operating model context

Governance alignment is not an audit that happens after delivery. It is a constraint that shapes architecture from day one. Discovering a compliance gap after a decision is locked is expensive; discovering it during bootstrap or spec is cheap.

This skill operates at the policy layer, above the cloud-expert skills:

  • gcp-expert / aws-expert / azure-expert / alibaba-expert — vendor-specific technical guardrails: IAM, data residency, cost. Use them to implement correctly within a chosen platform.
  • governance-guardrail (this skill) — checks whether the chosen platform, stack, and data model are permitted by enterprise policy in the first place.

Route cloud-specific implementation questions to the cloud-expert skills after this skill confirms the architecture is policy-compliant. Feed open findings into adversarial-gate before high-stakes decisions are locked.

Procedure

1. Locate the governance pointer

The project operating profile (docs/operating-model/PROJECT-OPERATING-PROFILE.md) should name one of:

  • A policy document (URL, file path, or shared drive location)
  • A compliance framework (SOC 2, ISO 27001, GDPR, HIPAA, etc.)
  • An approved-technology or approved-vendor list
  • A security baseline or architecture review board record

Read the full file on GitHub · 124 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 · 124 lines · 56 tokens per session scan A cb694397af28

Subscribe to this mod's changes

governance-guardrail is a skill published in the GitHub repository jpantsjoha/ai-native-developer-experience (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,236 once invoked, about $0.0003 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.