New:Microsoft Teams Notifications Are Now Available in Socket.Learn more
Get Started

manifest-aim

Package Overview
Dependencies
Maintainers
1
Versions
1
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

manifest-aim

The Agent Instruction Manifest platform — Define it. Manifest it.

latest
Source
npmnpm
Version
0.1.0
Version published
Maintainers
1
Created
Source

Manifest

The Agent Instruction Manifest Platform

Define it. Manifest it.

Manifest is the platform that implements the AIM (Agent Instruction Manifest) protocol — a portable, composable, progressively-loaded specification that tells AI agents what they can do, how to do it well, and what they must never do.

The Problem

AI agents today operate with fragmented instructions. MCP burns tokens loading every tool schema upfront. Skills files are local and non-portable. Rules files are static with no conditional logic. System prompts are ephemeral. The result: you can't trust agent output meets your standards.

The Solution

AIM unifies four concerns into a single manifest:

ConcernWhat it answersToday's fragmented approach
CapabilitiesWhat can the agent do?MCP servers, tool definitions
KnowledgeHow should it approach the work?Skills files, system prompts
GovernanceWhat must/must not it do?Rules files, hope
ExecutionHow does it actually run?MCP, CLI, REST, code

Progressive Disclosure (Why Token Burn Dies)

AIM uses four tiers. Agents only load what they need, when they need it:

TierToken CostWhen Loaded
0 — Index~5 per itemAlways
1 — Schema~50-200 per itemOn relevance match
2 — InstructionsVariableOn commitment
3 — Execution0 (never enters context)On dispatch

50 capabilities via MCP: ~25,000 tokens burned upfront. 50 capabilities via AIM: ~250 tokens at init. 99% reduction.

Enforceable Governance (Why "Hope" Dies)

AIM governance isn't a suggestion. Three enforcement mechanisms ensure compliance:

  • Static Analysis — Real tools (semgrep, ESLint, tsc) validate output. Deterministic. High trust.
  • Semantic (LLM-as-Judge) — A second LLM evaluates against nuanced rules. Generalizable. Medium trust.
  • Injected — Rules injected into agent context. Zero overhead. For style/preference guidance.

Quick Start

# Install
npm install -g manifest-aim

# Initialize a manifest in your project
manifest init

# Validate your manifest
manifest validate

# Compile (resolve dependencies, check conflicts)
manifest compile

# Health check
manifest doctor

# Wrap an agent with AIM enforcement
manifest wrap claude-code

Example aim.yaml

aim: "1.0"

metadata:
  name: my-project-standards
  version: 1.0.0
  description: "Production TypeScript development standards"

context:
  domain: software-engineering
  environment: production
  compliance: [soc2]

governance:
  rules:
    - name: no-hardcoded-secrets
      enforcement: static
      detect:
        type: tool
        command: "semgrep --config=p/secrets --json {{file}}"
        match_condition: "results.length > 0"
      action: block
      severity: critical
      message: "Hardcoded secrets detected. Use environment variables."

    - name: strict-typescript
      enforcement: static
      detect:
        type: tool
        command: "npx tsc --noEmit --strict {{file}}"
        exit_code_fail: non-zero
      action: block
      severity: error

    - name: clean-architecture
      enforcement: semantic
      detect:
        type: semantic
        criteria: "Domain modules must not import from infrastructure layers"
        model: fast
        threshold: 0.9
      action: warn
      severity: warning

  quality_gates:
    code:
      test_coverage_minimum: 80
      require_types: strict
      max_complexity: 10
      require_error_handling: true
      require_logging: structured

knowledge:
  - name: security-checklist
    trigger: "creating API endpoints, auth flows, or data handlers"
    content: |
      Before delivering code that handles user input or sensitive data:
      1. All inputs validated (use zod schemas)
      2. Auth middleware on protected routes
      3. Rate limiting on public endpoints
      4. Secrets from environment, never hardcoded
      5. SQL queries parameterized
      6. Error responses never leak internals

CLI Commands

CommandDescription
manifest initCreate a new aim.yaml in current directory
manifest validateValidate manifest against AIM JSON Schema
manifest compileResolve dependencies, detect conflicts, produce compiled manifest
manifest inspectShow what an agent sees at each tier
manifest doctorVerify tools, auth, and environment health
manifest wrap <agent>Wrap an agent with AIM enforcement
manifest enforce <path>Run enforcement checks standalone
manifest publishPublish manifest to Manifest Registry
manifest install <name>Install manifest from registry
manifest auditShow governance report
manifest generateAuto-generate manifest from project analysis (via Rebar)

Product Family

ProductRole
AIMThe protocol — the instruction language for AI agents
ManifestThe platform — CLI, runtime, registry, enterprise governance
RebarThe generator — analyzes projects, outputs aim.yaml automatically

Documentation

  • AIM Protocol Specification
  • Enforcement Architecture
  • Manifest Schema Reference
  • Writing Your First Manifest
  • Reference Manifests

License

Copyright © 2026 Vaspera Capital. All rights reserved.

See LICENSE for details.

Keywords

aim

FAQs

Package last updated on 14 Mar 2026

Related posts