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.
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.
npx agentmods add skills/ax-llm/ax/ax-agent-contextnpx skills add ax-llm/ax --skill ax-agent-contextgit clone --depth 1 https://github.com/ax-llm/axWrote 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/skills/ax-llm/ax/ax-agent-context)<a href="https://agentmods.dev/skills/ax-llm/ax/ax-agent-context"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-agent-context.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 | $0.00147 | $0.00857 |
| Opus 5 | $0.00073 | $0.00428 |
| Sonnet 5 | $0.00029 | $0.00171 |
| Haiku 4.5 | $0.00015 | $0.00086 |
Grade A, and why
ax-agent-context 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ax-agent-context — 97% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AxAgent Context Selection (@ax-llm/ax)
Use this skill to route a context-management need to the right AxAgent tool, then open the matching codegen skill. AxAgent manages four distinct context objects; choosing the wrong one is the usual mistake. Do not write tutorial prose; pick the tool and hand off.
Pick The Right Context Tool
| Need | Object | Scope | Use | Next skill |
|---|---|---|---|---|
| Many tasks over the same large corpus (repo, doc set, dataset) | Context map | recurring corpus, persists across runs | contextMap |
ax-agent-rlm |
| One long run whose own history must stay under control | Trajectory compaction | this run only | contextPolicy: { preset, budget } |
ax-agent-rlm |
| Evolve task strategy from examples or live feedback | Context playbook | a stage, offline + online | agent.playbook(...) |
ax-agent-optimize |
| Tune the prompt/instructions/demos offline | Instruction text | a program, offline | agent.optimize(...) (GEPA) |
ax-agent-optimize |
| Pull task-relevant facts or guides for a turn | Retrieval | one turn | recall(...) / skills |
ax-agent-memory-skills |
Defaults
- Recurring corpus + many different questions ->
contextMap(persistent orientation cache). - One long multi-turn run with prompt pressure ->
contextPolicy: { preset: 'checkpointed', budget: 'balanced' }; move toleanfor very long runs with strong models,fullfor short tasks or weak models. - Evolve a context playbook ->
agent.playbook(...)(offline from examples, or online from live feedback). - Tune instructions/demos offline ->
agent.optimize(...)(GEPA). - Fetch facts or guides on demand ->
recall(...)for memories,discover({ skills })for skill guides. - A single oversized input value (a pasted doc, a big JSON blob) -> do nothing;
autoUpgrade(ON by default) keeps it runtime-only with a prompt preview. Reach forcontextFieldsonly when you want a specific inline policy or the value is a large required non-string field. Seeax-agent-rlm.
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.
- yesterday First seen · 44 lines · 147 tokens per session scan A fe26462fe20a
ax-agent-context is a skill published in the GitHub repository ax-llm/ax (2,891 stars, last pushed 4d ago), licensed Apache-2.0. It adds 147 tokens to every session and 857 once invoked, about $0.0007 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 2026-09-03.
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handoff
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hindsight-local
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user).
agentmemory-agents
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last30Days
Resolve "last30Days" to a concrete ISO date range relative to your run time — a rolling 30-day window ending today. Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a "last 30 days" / trailing-month task…
thisQuarter
Resolve "thisQuarter" to a concrete ISO date range relative to your run time — this quarter so far (quarter start → today). Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a quarter-to-date task (QTD…