bizinsight-agent: Instructions file for Codex

AGENTS.md

bizinsight-agent AGENTS.md is an instructions file for Codex, OpenCode from sAjAd-2006/bizinsight-agent. It costs 709 tokens per session, scanned A, original, MIT.

Repository instructions for BizInsight Agent, a Python system that analyzes CSV business data and creates structured reports using multiple AI workers.

In plain words
What is it for?
Use them when modifying the data analysis, report generation, charts, MCP data access, or CrewAI-based agent workflow.
Why use it?
They define the project's tools and coding rules, including small, focused changes and explicit handling of uncertainty.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is sAjAd-2006/bizinsight-agent's own configuration. It tells Codex and OpenCode how to work on bizinsight-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything bizinsight-agent configures →

Reuse

Borrowing it

Nothing to install: this file belongs to sAjAd-2006/bizinsight-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/sAjAd-2006/bizinsight-agent/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/sAjAd-2006/bizinsight-agent

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 709 This file is loaded in full into every session.
When invoked 709 The same file — it is already loaded in full.
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 $0.00709 $0.00709
Opus 5 $0.00354 $0.00354
Sonnet 5 $0.00142 $0.00142
Haiku 4.5 $0.00071 $0.00071

Measured 10d ago against content hash 27cd7c22afed, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

bizinsight-agent 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 10d 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.

AGENTS.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — BizInsight Agent Project Context

Project Overview

BizInsight Agent is a multi-agent business intelligence system built with CrewAI. It analyzes business data (CSV files), generates insights, and produces structured reports.

Stack

  • Agent Framework: CrewAI (multi-agent orchestration)
  • MCP Servers: Custom data-access and chart-generation servers (stdio transport)
  • LLM: Google Gemini (configurable via GOOGLE_API_KEY in .env)
  • Data: pandas, numpy
  • Visualization: matplotlib, seaborn
  • Language: Python 3.10+

Project Conventions

  • Always begin by thinking deeply before coding — explicitly state assumptions, surface tradeoffs, and halt to ask for clarification the moment you encounter ambiguity rather than guessing silently.
  • Write only the absolute minimum amount of code required to solve the immediate problem, strictly avoiding speculative features, unrequested abstractions, or predictive configurations.
  • When editing existing code, make highly surgical changes by restricting your updates only to the exact lines necessary to fulfill the request, maintaining the existing style perfectly, and leaving adjacent, unbroken code completely untouched unless your changes directly orphaned an import or variable.
  • Approach every task through goal-driven execution by breaking it down into a clear, step-by-step plan with strong success criteria.
  • All MCP tools must validate inputs before execution.
  • All file I/O is scoped to the data/ and output/ directories. Never read or write outside these paths.
  • Never hardcode API keys. Use environment variables only.
  • Use [[VARIABLE]] placeholder syntax in all agent-facing templates. Never hardcode PII.

Spec-Driven Development (Day 5)

  • BDD specifications live in specs/ using Gherkin format (Given / When / Then)
  • Specs are the source of truth — if code diverges from specs, the code is wrong
  • Use the spec to drive test creation and agent behavior verification

Zero-Trust Governance (Day 5)

  • All tool calls pass through the Policy Server (policy_server.py)
  • Policies are defined in policies.yaml — structural gating via role/environment
  • Context hygiene is enforced via context_resolver.py — PII masking + placeholder resolution
  • No tool has ambient authority; every action is checked before execution

Read the full file on GitHub · 55 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. 10d ago First seen · 55 lines · 709 tokens per session scan A 27cd7c22afed

Subscribe to this mod's changes

bizinsight-agent AGENTS.md is an instructions file published in the GitHub repository sAjAd-2006/bizinsight-agent (2 stars, last pushed 2mo ago), licensed MIT. It adds 709 tokens to every session, about $0.0035 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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