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 skills add JairoTorregrosa/jaiskills --skill askcodexgit clone --depth 1 https://github.com/JairoTorregrosa/jaiskillsWrote 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/jairotorregrosa/jaiskills/askcodex)<a href="https://agentmods.dev/skills/jairotorregrosa/jaiskills/askcodex"><img src="https://agentmods.dev/badge/skills/jairotorregrosa/jaiskills/askcodex.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 5.1 | $0.00173 | $0.01282 |
| Opus 5 | $0.00086 | $0.00641 |
| Sonnet 5 | $0.00035 | $0.00256 |
| Haiku 4.5 | $0.00017 | $0.00128 |
Grade A, and why
askcodex 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
askcodex — OpenAI models as a CLI
The binary lives at ~/.local/bin/askcodex. If it is missing, clone
https://github.com/JairoTorregrosa/askcodex and run ./install.sh. It authenticates with the
credentials codex login already stored — if they are missing, askcodex says so; tell the user to run
codex login.
Intent → command
| The user wants | Run |
|---|---|
| ask GPT-5 / complete text | askcodex ask "prompt" [--model <slug>] [--effort low|medium|high|xhigh|max|ultra] |
| make an image of X | askcodex image create "X" -o /tmp/askcodex/x.png |
| edit / restyle this image | askcodex image edit "change ..." -i ref.png -o /tmp/askcodex/x-edited.png |
| which models are available | askcodex models |
| how much quota / rate-limited? | askcodex usage |
| who am I / which plan | askcodex whoami |
| is the auth still valid | askcodex auth status --no-refresh |
| refresh the auth token | askcodex auth refresh |
| any other backend endpoint | askcodex raw GET /codex/... [--body '{…}'] [--stream] |
Two global flags, accepted anywhere on the command line, including after the deepest subcommand:
--json— exactly one JSON document on stdout, nothing else.--no-refresh— the command will not rewrite the auth file. Use it for read-only checks.
Prompting
Before writing a prompt — picking a model, choosing a reasoning effort, or phrasing an image prompt — read references/prompting.md. It has the per-model notes (which slug for which job), per-use-case recipes (one-shot Q&A, codegen, extraction, long context, creative), an effort decision table, and the image-prompt structure that works.
Outputs go to /tmp/askcodex/
Save every artifact under /tmp/askcodex/ (mkdir -p /tmp/askcodex first) instead of the working
directory, so large outputs never flood the conversation and stay recoverable by path:
- Images:
-o /tmp/askcodex/<descriptive-name>.png, then report the path (and send the file if the user should see it). - Answers you expect to be long:
askcodex ask "..." --json > /tmp/askcodex/<name>.json— read back just the parts you need (jq -r .text). Short answers can stream to stdout normally. - Raw endpoint dumps:
askcodex raw ... > /tmp/askcodex/<name>.json.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 82 lines · 173 tokens per session scan A 21b03c6e3fb3
askcodex is a skill published in the GitHub repository JairoTorregrosa/jaiskills (5 stars, last pushed 7d ago), licensed MIT. It adds 173 tokens to every session and 1,282 once invoked, about $0.0009 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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