ax-python-agent-memory-skills

ax-python-agent-memory-skills is a skill for Claude Code, Codex from ax-llm/ax. It costs 40 tokens per session (944 once invoked), scanned A, original, Apache-2.0.

A guide for writing Python code with axllm, a package for building language-model agents. It covers loading memories and skills, discovering them, and tracking which ones affected a response.

In plain words
What is it for?
Use it when building Python agents that need memory recall, dynamic skill discovery, preloaded skills, or records of loaded and used skills.
Why use it?
It gives the agent a defined way to manage remembered information and skill instructions instead of handling that state inconsistently.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when building Python agents that need memory recall, dynamic skill discovery, preloaded skills, or records of loaded and used skills.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ax-llm/ax/ax-python-agent-memory-skills
About the project

Ax is a TypeScript-first programming framework for building applications with large language models through typed generation, agents, workflows, and optimization tools. It is intended for developers who want one model for LLM programs across TypeScript, Python, Java, C++, Go, Rust, and other runtimes.

ax-llm/ax · 2,968 stars · on GitHub · axllm.dev

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.

Any agent
npx skills add ax-llm/ax --skill ax-python-agent-memory-skills
Clone the repo
git clone --depth 1 https://github.com/ax-llm/ax

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ax-python-agent-memory-skills

README.md
[![agentmods](https://agentmods.dev/badge/skills/ax-llm/ax/ax-python-agent-memory-skills/github.svg)](https://agentmods.dev/skills/ax-llm/ax/ax-python-agent-memory-skills)
Your own site
<a href="https://agentmods.dev/skills/ax-llm/ax/ax-python-agent-memory-skills"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-python-agent-memory-skills/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ax-python-agent-memory-skills

Your own site · 80×15
<a href="https://agentmods.dev/skills/ax-llm/ax/ax-python-agent-memory-skills"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-python-agent-memory-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 944 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00040 $0.00944
Opus 5.5 $0.00016 $0.00378
Sonnet 5.5 $0.00008 $0.00189
Haiku 4.5 $0.00004 $0.00094

Measured yesterday against content hash 387ec2b60193, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ax-python-agent-memory-skills 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

packages/python/skills/ax-python-agent-memory-skills/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AxAgent Memory And Skills For Python

This skill helps an agent write Python code with the generated Ax package axllm. Use the generated package API, examples, and manifests; do not import TypeScript-only APIs unless you are editing the TypeScript package.

When To Use

  • Load memories or skill guides into an RLM agent run.
  • Use static skillsCatalog or memoriesCatalog search without host callbacks.
  • Preload constructor or forward-time skills with deterministic id merging.
  • Track which memories or skills actually influenced a turn.
  • Register non-fatal loaded/used observers in native option maps or target callback wrappers.

Package Facts

  • Language: Python.
  • Package: axllm.
  • Package API docs: API.md and axir-api.json.
  • Capability manifest: axir-capabilities.json.
  • Runnable examples: examples/.
  • Real network support: yes.
  • Scripted no-key transport support: yes.
  • Runtime profiles: javascript-quickjs, python-pyodide.

Core Pattern

from axllm import agent

helper = agent("question:string -> answer:string")
out = helper.forward(llm, {"question": "How should I proceed?"})

Lifecycle And State

  • Constructor skills seed the loaded-skill prompt without firing load observers.
  • Forward-time skills override constructor entries by normalized ID and remain loaded for later calls. IDs and names are trimmed, malformed entries are skipped, valid empty content is preserved, and rendered entries are ID-sorted.
  • A forward input named memories seeds the first actor turn. Recalled entries merge by ID for that run, then memory state resets before the next forward.
  • onSkillsSearch / onMemoriesSearch take precedence over static catalogs. Without a host callback, skillsCatalog / memoriesCatalog use the built-in deterministic lexical ranker.
  • onLoadedMemories / onLoadedSkills observe runtime recall and discovery, not constructor presets. onUsedMemories / onUsedSkills emit one consolidated notification per forward. Forward observers override constructor observers, and observer errors are ignored.
  • relevanceRanking produces advisory skill and memory hints using the same tokenization, weighting, tie suppression, limits, snippets, and already-loaded exclusion as TypeScript.
  • contextMap is TypeScript's context map: the distiller reads its text (TypeScript's section template when it has none), and after each completed run the context-map Distiller and Cartographer programs update it in place. Since 25.0.0 the text and item ids follow TypeScript's format ([rr-00002], a blank line before each section, a trailing newline); a map saved by a 24.x port loads with its items and is normalized by its next update.
  • get_state() and set_state(...) preserve the legacy bare-runtime snapshot shape. Use export_runtime_state() and restore_runtime_state(...) for the complete portable agent snapshot, including loaded skills and constructor-preset reapplication. Do not interchange the two shapes.

Read the full file on GitHub · 66 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 Changed 387ec2b60193
  2. 2d ago Changed 24ca7ee6d045
  3. 4d ago Changed 95e6e9ba18c0
  4. 5d ago Changed 24a0cff935e0
  5. 7d ago Changed 4245696f762a
  6. 9d ago Changed 22058c92786d
  7. 11d ago Changed 79f034503978
  8. 14d ago Changed 2c95addb7fd1
  9. 15d ago Changed 99b283a16c40
  10. 16d ago First seen · 66 lines · 40 tokens per session scan A 2c872559cfd0

Subscribe to this mod's changes

ax-python-agent-memory-skills is a skill published in the GitHub repository ax-llm/ax (2,968 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 944 once invoked, about $0.0002 per session on Opus 5.5. 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.

Related

Other skills, from other repositories

knowledge-wiki

Manage the personal knowledge wiki. Use when the user shares articles, documents, or asks to organize knowledge; when a conversation produces insights worth preserving as structured knowledge; or when the user asks about the knowledge base.

zhayujie/CowAgent · 46 tokens

build-with-tinybase

Scaffold, extend, and verify reactive local-first JavaScript or TypeScript applications with TinyBase. Use when choosing TinyBase for in-memory tabular or key-value state, generating an app with create-tinybase, adding schemas or UI bindings, resolving TinyBase import paths, configuring browser or database…

tinyplex/tinybase · 90 tokens

stripe-directory

Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request…

stripe/ai · 212 tokens

output-dev-evaluator-function

Create evaluator functions in evaluators.ts for Output SDK workflows. Use when implementing quality assessment, validation logic, or content evaluation.

growthxai/output · 31 tokens

output-dev-prompt-file

Create .prompt files for LLM operations in Output SDK workflows. Use when designing prompts, configuring LLM providers, or using Liquid.js templating.

growthxai/output · 36 tokens

output-meta-project-context

Comprehensive guide to Output.ai Framework for building durable, LLM-powered workflows orchestrated by Temporal. Covers project structure, workflow patterns, steps, LLM integration, HTTP clients, CLI commands, and the full inventory of available agents and skills.

growthxai/output · 54 tokens