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 agentmods add skills/aegntic/compound-engineering/agent-native-auditnpx skills add aegntic/compound-engineering --skill agent-native-auditgit clone --depth 1 https://github.com/aegntic/compound-engineeringWrote 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/aegntic/compound-engineering/agent-native-audit)<a href="https://agentmods.dev/skills/aegntic/compound-engineering/agent-native-audit"><img src="https://agentmods.dev/badge/skills/aegntic/compound-engineering/agent-native-audit.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 | $0.00015 | $0.02492 |
| Opus 5 | $0.00008 | $0.01246 |
| Sonnet 5 | $0.00003 | $0.00498 |
| Haiku 4.5 | $0.00002 | $0.00249 |
Grade A, and why
agent-native-audit 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 3d 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 — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent-Native Audit
Run a comprehensive review of a codebase against agent-native architecture principles, split the work into scored principle-specific audit tracks, and produce a prioritized summary report.
Announce at start: "I'm using the agent-native-audit skill to run a scored agent-native architecture review."
When to Use
- After adding agent tools, prompts, commands, or shared-workspace behavior
- Before shipping major agent-facing product changes
- When you need a numeric baseline for how agent-native a system really is
- When you want prioritized recommendations instead of a vague architectural opinion
Core Principles to Audit
- Action Parity - "Whatever the user can do, the agent can do"
- Tools as Primitives - "Tools provide capability, not behavior"
- Context Injection - "System prompt includes dynamic context about app state"
- Shared Workspace - "Agent and user work in the same data space"
- CRUD Completeness - "Every important entity has full CRUD (Create, Read, Update, Delete)"
- UI Integration - "Agent actions are reflected in the product experience"
- Capability Discovery - "Users can discover what the agent can do"
- Prompt-Native Features - "Features are prompts defining outcomes, not rigid workflow code"
Workflow
Step 1: Load the Local Reference Skill
First, invoke agent-native-architecture to refresh the local vocabulary, principles, checklist, and anti-patterns used in this plugin.
Focus especially on:
- Core principles
- Architecture Review Checklist
- Tool Design
- Files & Workspace
- Context Injection
- UI Integration
- Capability Discovery
- Anti-Patterns
Use the local skill name directly. Do not rely on Every-specific namespaced invocations.
Step 2: Decide Audit Scope
If $ARGUMENTS names a single principle, audit only that principle.
Otherwise, audit all 8 principles.
When auditing a plugin, CLI, or developer-tooling codebase, map "user actions" and "UI" broadly:
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.
- 3d ago First seen · 365 lines · 15 tokens per session scan A f444c5c61cd8
agent-native-audit is a skill published in the GitHub repository aegntic/compound-engineering (2 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 2,492 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 2026-08-31.
Other skills, from other repositories
methodology
Analyzes captured HTTP traffic, designs the CLI architecture, and implements the Python CLI package (Phase 2): parse raw-traffic.json, identify the protocol, write api-spec.json, scaffold from templates, and implement endpoint methods and Click command groups. Use after a capture completes and raw-traffic.json exists.
standards
Runs Phase 4 review/publish/verify for a cli-web- CLI: implementation review by 3 parallel agents, the tiered quality checklist (Tier 1 critical fail-fast, then comprehensive), pip install + smoke test, and per-CLI skill generation. Use when a CLI's tests pass and it is ready to be validated and published.
testing
Writes and documents the test suite for a generated cli-web- CLI (Phase 3): unit tests with mocked HTTP, live E2E tests, subprocess tests via resolvecli, and the TEST.md plan/results record. Use after the methodology skill completes implementation.
sync-check
Walks the documentation dependency web after a CLI code change and reports which downstream files (skills, SOPs, READMEs, plugin references) are out of sync. Use after fixing a bug, adding a command, changing auth behavior, refactoring, or before committing — and when the user says "sync check", "update docs"…
boilerplate
Documents the template inventory and variable contract behind scaffold-cli.py — which Jinja2 template renders with which variables for each site profile. Use during Phase 2 scaffolding when choosing scaffold flags or understanding what the generated boilerplate contains. The scaffold-cli.py script is the primary path.
futbin-cli
Queries FUTBIN (EA FC Ultimate Team database) via cli-web-futbin — player search, prices and price history, comparisons, SBCs, evolutions, and market analytics (index, trending, cheapest by rating, movers, fodder, buy/sell signals, undervalue scans, PS/PC arbitrage). Use when the user asks about EA FC player prices…