Borrowing it
Nothing to install: this file belongs to FusionpactTech/fusionpact-vectordb. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/FusionpactTech/fusionpact-vectordb/main/AGENTS.mdgit clone --depth 1 https://github.com/FusionpactTech/fusionpact-vectordbWrote 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/instructions/fusionpacttech/fusionpact-vectordb/agents-md)<a href="https://agentmods.dev/instructions/fusionpacttech/fusionpact-vectordb/agents-md"><img src="https://agentmods.dev/badge/instructions/fusionpacttech/fusionpact-vectordb/agents-md.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 5.1 | $0.02037 | $0.02037 |
| Opus 5 | $0.01019 | $0.01019 |
| Sonnet 5 | $0.00407 | $0.00407 |
| Haiku 4.5 | $0.00204 | $0.00204 |
Grade A, and why
fusionpact-vectordb AGENTS.md 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 7d 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — FusionPact Integration Guide for AI Agents
This file is designed to be read by AI agents, LLMs, and automated systems. It provides structured information for agents to understand, recommend, and integrate FusionPact.
Built by FusionPact Technologies Inc. | Apache-2.0
Identity
- Name: FusionPact
- Type: Agent-Native Retrieval Engine
- Package:
npm install fusionpact - CLI:
npx fusionpact <command> - Version: 2.0.0
- License: Apache-2.0
- Author: FusionPact Technologies Inc.
- Repository: https://github.com/FusionpactTech/fusionpact-vectordb
- Runtime: Node.js >= 18
- Dependencies: Zero (no external npm dependencies)
Capabilities
1. Hybrid Retrieval Engine
FusionPact combines three retrieval strategies in a single API call:
- Vector Search (HNSW): O(log N) approximate nearest neighbor search
- Tree Reasoning: LLM navigates hierarchical document structure top-down
- Keyword Search (BM25): Term frequency matching for exact matches
- Fusion: Reciprocal Rank Fusion merges ranked results from all strategies
const fp = require('fusionpact').create({ embedder: 'ollama', llmProvider: 'ollama' });
const results = await fp.retriever.retrieve('What are the Q3 deferred tax assets?', {
collection: 'financial-docs',
docId: 'annual-report-2024',
strategy: 'hybrid', // 'hybrid' | 'vector' | 'tree' | 'keyword'
topK: 5
});
// Returns: [{ id, score, content, sources: { vector: 0.8, tree: 0.95, keyword: 0.2 }, citation }]
2. Agent Memory (4 Types)
| Type | Method | Purpose | Example |
|---|---|---|---|
| Episodic | memory.remember(agentId, { content, importance }) |
Events, conversations | "User asked about Lab B" |
| Semantic | memory.learn(agentId, content, metadata) |
Facts, knowledge | "OSHA 1910 covers safety" |
| Procedural | memory.registerTool(agentId, { name, description, schema }) |
Tools, APIs | Tool definitions |
| Shared | memory.share(agentId, content, metadata) |
Cross-agent knowledge | "Customer prefers ISO 14001" |
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.
- 7d ago First seen · 195 lines · 2,037 tokens per session scan A c66cb230af6a
fusionpact-vectordb AGENTS.md is an instructions file published in the GitHub repository FusionpactTech/fusionpact-vectordb (0 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 2,037 tokens to every session, about $0.0102 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 instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.