programasweights-python AGENTS.md

A set of project instructions for using ProgramAsWeights, a tool that compiles plain-language descriptions into small local text-processing functions.

In plain words
What is it for?
Use it for fuzzy search, typo-tolerant matching, format repair, classification, extracting details, log triage, intent routing, and preparing or checking agent tool calls.
Why use it?
It helps handle messy text when fixed patterns such as regular expressions are not reliable and a full language model would be unnecessary.

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/programasweights/programasweights-python/agents-md
Clone the repo
git clone --depth 1 https://github.com/programasweights/programasweights-python

Made for: Codex, OpenCode.

Per session 2,567 This file is loaded in full into every session.
When invoked 2,567 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 $0.02567 $0.02567
Opus 5 $0.01283 $0.01283
Sonnet 5 $0.00513 $0.00513
Haiku 4.5 $0.00257 $0.00257

Measured 2d ago against content hash 5a9cc3b4c385, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

programasweights-python 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 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.

AGENTS.md · 250 lines

How it starts

The opening of the file, as written. The whole thing — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ProgramAsWeights (PAW)

PAW compiles natural language specifications into tiny neural functions that run locally. Each function takes a single text input and returns a single text output. Use it when you need fuzzy text processing — classification, extraction, format repair, search, triage — that regex can't handle but a full LLM is overkill for.

Website: https://programasweights.com Full documentation: https://programasweights.readthedocs.io

When to Use PAW

  • Fuzzy search — typo-tolerant matching, semantic search, near-duplicate detection
  • Format repair — fix broken JSON, normalize dates, repair malformed inputs
  • Classification — sentiment, urgency, categories defined in your own words
  • Extraction — emails, names, dates from messy unstructured text
  • Log triage — extract errors from verbose output, filter noise
  • Intent routing — map user descriptions to the closest URL, menu item, or setting
  • Agent preprocessing — parse tool calls, validate outputs, route tasks

Install

pip install programasweights --extra-index-url https://pypi.programasweights.com/simple/

Quickstart

import programasweights as paw

# Use a pre-compiled function (downloads once, runs locally forever)
fn = paw.function("email-triage")
fn("Urgent: server is down!")  # "immediate"
fn("Newsletter: spring picnic")  # "wait"

# Compile your own from a description
program = paw.compile(
    "Fix malformed JSON: repair missing quotes and trailing commas"
)
fn = paw.function(program.id)
fn("{name: 'Alice',}")  # '{"name":"Alice"}'

# Or compile and load in one step
fn = paw.compile_and_load("Classify sentiment as positive or negative")
fn("I love this!")  # "positive"

If you want the smaller browser-compatible runtime explicitly, pass compiler="paw-4b-gpt2". Otherwise, omit compiler and let the server default decide.

Current Public Compilers

  • Standard (paw-4b-qwen3-0.6b) — higher accuracy, 594 MB base + ~22 MB/program. This is the current server default.
  • Compact (paw-4b-gpt2) — smaller (134 MB base + ~5 MB/program), runs in browser via WebAssembly.

Read the full file on GitHub · 250 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 · 250 lines · 2,567 tokens per session scan A 5a9cc3b4c385

Subscribe to this mod's changes

programasweights-python AGENTS.md is an instructions file published in the GitHub repository programasweights/programasweights-python (268 stars, last pushed 1mo ago), licensed MIT. It adds 2,567 tokens to every session, about $0.0128 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 2026-08-30.

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