predicate AGENTS.md

Repository instructions for Predicate, a framework that helps coding agents stay focused on their goals over long tasks. They describe its purpose, requirements, and correctness rules.

In plain words
What is it for?
Use them when working on Predicate’s skills, rules, ambient guidance, conditioning system, or orientation workflow.
Why use it?
They give agents durable guidance about the project and define how results should be checked, reducing drift during extended work.

Instructions file for CodexOpenCode

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 instructions/nrdxp/predicate/agents-md
Clone the repo
git clone --depth 1 https://github.com/nrdxp/predicate

Made for: Codex, OpenCode.

Per session 1,551 This file is loaded in full into every session.
When invoked 1,551 The same file — it is already loaded in full.
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 $0.01551 $0.01551
Opus 5 $0.00776 $0.00776
Sonnet 5 $0.00310 $0.00310
Haiku 4.5 $0.00155 $0.00155

Measured yesterday against content hash ef03c74bac85, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

predicate 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 yesterday.

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 · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Predicate

This repository is Predicate, the upstream. skills/, rules.md, and ambient.md live at the root because other projects consume them as an installed plugin — see README.md and docs/getting-started.md.

Goal

Predicate is a self-hosting, harness-agnostic framework that keeps AI coding agents anchored to the true goal across long-horizon work. It has two synergistic halves:

  • Correction — externalize correctness to the strongest evaluator (the Verification Dual: verify, then trust — no condition closed by an agent's say-so). Authority: rules.md.
  • Prevention — externalize the goal, requirements, unknowns, and available tools as a durable, selectively-projected conditioning layer (the always-on conditioning/ system-prompt law, the /orient workflow, the nested AGENTS.md hierarchy), so a walk stays focused before drift compounds.

Correction without prevention corrects toward the wrong goal; prevention without correction drifts anyway over a long horizon. Together they bound drift.

Formal substrate

An LLM is an autoregressive stochastic walk over a token state-space; in open-loop generation error compounds, so drift is a statistical inevitability over long horizons. Predicate closes the loop — an external deterministic evaluator computes an error differential and updates the boundary condition toward a fixed point (ΔE → 0). The formalism is non-entropic: it is the anchor the doctrine rests on, not the doctrine. Full treatment: docs/theory/formalism.md; lexicon in rules.md §1. The prevention extension — attention-dilution and phase-space constriction — is derived in docs/theory/formalism.md Part 2.

Requirements (for predicate to be useful)

  • Self-hosting — predicate governs its own development.
  • Harness-agnostic — every capability degrades to a harness-native primitive (git / bash / python / nickel); a harness convenience may accelerate a step but never replaces the primitive path when it is absent or fails.
  • Machine-checkable where possible — artifacts and process are bound by evaluators (footprints), not by an agent's memory of the rules.
  • Composable — co-exists with whatever other plugins / skills / MCP servers the host harness has installed.

Read the full file on GitHub · 124 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. yesterday First seen · 124 lines · 1,551 tokens per session scan A ef03c74bac85

Subscribe to this mod's changes

predicate AGENTS.md is an instructions file published in the GitHub repository nrdxp/predicate (10 stars, last pushed 8d ago), licensed MIT. It adds 1,551 tokens to every session, about $0.0078 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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