api-audit

A structured review process for a code API, meaning the functions, types, and entry points other code can use. It examines whether the interface is clear, consistent, type-safe, and easy to combine.

In plain words
What is it for?
Use it to audit API designs, public interfaces, type safety, design consistency, and constraints such as avoiding breaking changes.
Why use it?
It helps find confusing or unsafe interfaces before they cause errors for users or other parts of the codebase. It also adds explicit checkpoints for agreeing on the review scope.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/nrdxp/predicate/api-audit
Any agent
npx skills add nrdxp/predicate --skill api-audit
Clone the repo
git clone --depth 1 https://github.com/nrdxp/predicate

Made for: Claude Code, Codex.

Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,327 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00049 $0.03327
Opus 5 $0.00024 $0.01664
Sonnet 5 $0.00010 $0.00665
Haiku 4.5 $0.00005 $0.00333

Measured 2d ago against content hash 28c4172225ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

api-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 2d 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/api-audit/SKILL.md · 348 lines

How it starts

The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.

API Coherence Audit Protocol

A thorough, piecemeal framework for auditing code API surfaces. Designed to maintain agent coherence by working iteratively through the codebase with explicit human checkpoints.

Adversarial path anchor. This lens is invoked on the Verification Dual's adversarial path (rules.md §2 Invariant 1): when no deterministic evaluator can close an API-surface correctness condition, context-free agents using this protocol supply the decorrelated review. See skills/refine/SKILL.md AUDIT §"Sibling Skills Consultation" for the wiring point.

Guiding Principle: An ideal API is minimal, well-scoped, type-safe, elegantly composable, and monosemic. It leverages language features to make error states unrepresentable.


Phase 0: Scope Definition

Before beginning, establish the audit scope with the user. Confirm: target language and version; type system strength; public API entry points; explicit exclusions (generated code, vendored deps); user-defined constraints (e.g., no breaking changes, no-std compatibility).

Checkpoint: Present scope to user for approval before proceeding.

Phase 1: Surface Discovery (Full Codebase Ingestion)

Objective: Build a complete mental model of the public API surface before any analysis.

1.1 Enumerate Public Surface

For each entry point, catalog:

  • Exported Types: Structs, enums, classes, interfaces, type aliases
  • Exported Functions: Free functions, associated functions, methods
  • Exported Constants: Public constants, static values
  • Re-exports: Items re-exported from internal modules
  • Traits/Interfaces: Abstractions meant for external implementation

1.2 Generate Surface Map

Produce a structured inventory:

## Module: `crate::auth`
### Types
- `Principal` (struct) — L23-L45
- `AuthState` (enum) — L47-L62
### Functions
- `Principal::verify(&self, sig: &Signature) -> Result<()>` — L67
- `validate_token(token: &str) -> Result<Claims>` — L89
### Traits
- `Authenticator` — L12-L21
  - `fn authenticate(&self, credentials: &Credentials) -> Result<Session>`

Read the full file on GitHub · 348 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. 2d ago First seen · 348 lines · 49 tokens per session scan A 28c4172225ae

Subscribe to this mod's changes

api-audit is a skill published in the GitHub repository nrdxp/predicate (10 stars, last pushed 8d ago), licensed MIT. It adds 49 tokens to every session and 3,327 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 2026-08-31.

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