askcodex

You have the

askcodex

CLI. It sends one request to an OpenAI model through the user's ChatGPT/Codex subscription and returns a text answer, an image, or a transcript. Turn the user's request into a complete brief, run one focused call, check the result against the brief, and hand the user the useful output with its saved path.

Canonical copy:

skill/

in https://github.com/JairoTorregrosa/askcodex (this is a mirror; change it there, then re-sync). Local delta: the description's not-for clause points to second-opinion.

Context you must respect

This skill describes askcodex 0.3.0 or later. Check
```
askcodex --version
```
once per session. 0.2.x has no
```
--schema
```
,
```
--verbosity
```
or
```
--background
```
, prints the ~700 KB raw catalog inside
```
models --json
```
, and gives errors without
```
error.backend
```
; 0.1.x also hides the GPT-6 models. If it is older, tell the user to update instead of working around it: in an askcodex checkout,
```
git pull && ./install.sh
```
; without one, download the latest release binary from https://github.com/JairoTorregrosa/askcodex/releases (verify
```
SHA256SUMS
```
), or clone it and run
```
./install.sh
```
(needs Rust 1.88+).
Every call is one-shot and stateless.
```
ask
```
sends only the prompt and optional
```
--instructions
```
: the model gets no tools, files, browsing, repository, or earlier conversation. A file path in a prompt is just text; paste the contents instead.
Everything in a prompt, a reference image or an audio file leaves the machine for OpenAI's backend. Before you paste logs, exports, code or documents, always remove credentials, tokens, keys and passwords, even when the user supplied them for the task: replace them with placeholders. Also remove personal or customer data the task does not need; if the task needs it, or you cannot tell, ask the user first.
Every call spends the user's subscription quota. GPT-6 Astra is the most expensive model.
A second model's answer is input to your work. Verify its facts, review its code, and look at its images before you report success.
askcodex uses the credentials
```
codex login
```
saved to
```
~/.codex/auth.json
```
; it reads no API key. Never print credentials.

Facts already verified (2026-10-02)

```
askcodex models --no-refresh
```
lists what the account can use, with each model's description, Codex's default effort and any retirement date. On 2026-10-02:
```
gpt-6.1-sol
```
,
```
gpt-6-astra
```
,
```
gpt-6-sol
```
,
```
gpt-6-luna
```
,
```
gpt-5.6-sol
```
,
```
gpt-5.6-terra
```
,
```
gpt-5.6-luna
```
,
```
gpt-daybreak-blue-latest
```
,
```
gpt-5.5
```
(retires 2026-10-14), and the hidden
```
gpt-reserve
```
and
```
codex-auto-review
```
. All take text;
```
ask
```
sends text only. OpenAI ships models every few days: trust the live catalog over this list.
```
ask
```
defaults to
```
gpt-6.1-sol
```
at
```
medium
```
. The catalog lists it for every plan; if a plan refuses it with a model-availability error (OpenAI's Codex docs have offered Free and Go only Luna), pass
```
--model gpt-6-luna
```
. askcodex never switches models on its own.
```
--effort
```
takes
```
low
```
,
```
medium
```
,
```
high
```
,
```
xhigh
```
,
```
max
```
, or
```
none
```
. The catalog also lists
```
ultra
```
, which is Codex's multi-agent mode; the backend rejects it. A level a model does not take fails with HTTP 400 (
```
none
```
on
```
gpt-6-astra
```
and
```
gpt-6.1-sol
```
;
```
gpt-6-sol
```
and
```
gpt-6-luna
```
accept it although the catalog omits it).
```
--verbosity low|medium|high
```
sets answer length and detail. Unset, the backend answers at
```
medium
```
; Codex itself asks for
```
low
```
. On the same prompt
```
low
```
used 240 output tokens and
```
high
```
513.
```
--schema FILE
```
makes the backend enforce a JSON Schema in strict mode, even against a prompt that asks for prose. Strict rules: every property in
```
required
```
,
```
"additionalProperties": false
```
on every object, and an optional value adds
```
"null"
```
to its own type (
```
["string","null"]
```
,
```
["integer","null"]
```
; an
```
enum
```
must list
```
null
```
too). A schema that breaks them fails before generation with
```
error.backend.code: "invalid_json_schema"
```
and a message naming the key. With
```
--json
```
,
```
.result.json
```
is the parsed answer. askcodex re-checks its structure against the schema, so an answer that does not parse or does not match is a
```
response_invalid
```
failure, never a result.
```
image create
```
and
```
image edit
```
return one PNG per call of about 1.57 megapixels; the prompt sets the aspect ratio.
```
--background transparent
```
or
```
opaque
```
forces the background (both honored); unset, the prompt decides. The result reports the file's real
```
width
```
,
```
height
```
and
```
alpha_channel
```
. There is no model, size, quality, format, or count flag, because the backend ignores those fields.
```
transcribe
```
takes a WAV file up to 25 MiB and has no model or language selector.

Do this

Pick the command and read its guide before you write the prompt:

Result	Command	Read first
Answer, analysis, writing, code, or review	`askcodex ask "prompt" --model <slug> --effort <level>` (add `--verbosity low` for a concise answer)	prompting-text.md and the model's guide below
Classification or extraction you will parse	`askcodex ask - --schema /tmp/askcodex/<name>.schema.json --json < brief.txt` , then read `.result.json`	Same as above
New image	`askcodex image create "prompt" -o /tmp/askcodex/<name>-v1.png` (add `--background transparent` for a cutout)	prompting-images.md and model-gpt-image-2.md
Image edit from one to five PNG references	`askcodex image edit "prompt" -i ref.png -o /tmp/askcodex/<name>-v2.png`	Same as a new image
Audio transcript	`askcodex transcribe recording.wav`	transcription.md
Which models exist, their default effort, what retires	`askcodex models --no-refresh` (a short list with descriptions)	Nothing; no prompt is involved
Quota, account, auth status	`askcodex usage` / `whoami` / `auth status` , each with `--json --no-refresh`	Nothing

For

ask

, pick the model and read its guide:

The task	Model	Guide
Most work: coding, review, debugging, analysis, drafting	`gpt-6.1-sol` (default)	model-gpt-6.1-sol.md
The hardest or most consequential single deliverable	`gpt-6-astra`	model-gpt-6-astra.md
Clear, repeatable extraction, classification, or transformation	`gpt-6-luna`	model-gpt-6-luna.md
Authorized defensive security work	`gpt-daybreak-blue-latest`	model-gpt-daybreak-blue-latest.md
Reproducing a GPT-6 Sol result	`gpt-6-sol`	model-gpt-6-sol.md
Reproducing a GPT-5.6 result	`gpt-5.6-sol` , `gpt-5.6-terra` , `gpt-5.6-luna`	sol, terra, luna
Anything on `gpt-5.5`	move to `gpt-6.1-sol` ( `gpt-6-luna` if the plan refuses it)	model-gpt-5.5.md

prompting.md indexes every guide. Pin

--model

and

--effort

whenever you compare outputs or need to reproduce one.

Write a complete brief: the deliverable, its audience, the constraints, what "done" means, the source material itself, what must stay unchanged, and the output format.
Run one focused request. Create
```
/tmp/askcodex/
```
first and give every artifact a descriptive name with a version suffix, so an edit never overwrites a useful result. For a long-running job, run it in the background or in tmux and save its output to a file.
Inspect the result against the brief. Make the next request about one specific observed problem, and keep the last useful version.

Handle the output

Images: always pass
```
-o /tmp/askcodex/<name>-vN.png
```
. With
```
--json
```
,
```
.result.width
```
,
```
.result.height
```
and
```
.result.alpha_channel
```
come from the saved file;
```
alpha_channel: true
```
only says transparency is possible, so look at the image before you call it a cutout.
Long text answers:
```
--json > /tmp/askcodex/<name>.json
```
, then
```
jq -r .result.text /tmp/askcodex/<name>.json
```
. Keep large JSON and image payloads out of the conversation.
```
--json
```
,
```
--events
```
, and
```
--no-refresh
```
are global flags and work after the subcommand.
Semantic
```
--json
```
success output is
```
{schema_version:1,command,result}
```
. Read
```
.result
```
. Do not pass
```
--backend
```
(it adds the raw backend response, ~700 KB for
```
models
```
) unless the user is debugging the protocol.
```
ask --json
```
gives one final envelope with
```
.result.model
```
,
```
.result.effort
```
,
```
.result.verbosity
```
,
```
.result.text
```
,
```
.result.usage
```
(possibly null), and
```
.result.json
```
with
```
--schema
```
. The catalog is at
```
.result.models
```
(slug, description, default_reasoning_level, upgrade); quota windows are at
```
.result.rate_limit
```
.
```
--events
```
prints newline-delimited JSON:
```
ask
```
sends
```
text_delta
```
events and one final
```
result
```
event on success; other commands send their result. Check the exit status: partial text is not success. Do not combine
```
--events
```
with
```
--json
```
.
```
transcribe
```
prints the text, or
```
.result.text
```
with
```
--json
```
.
Stdin prompts (
```
-
```
) and
```
raw --body -
```
accept up to 16 MiB of UTF-8. File inputs must be regular files (symlinks to them work; devices and FIFOs do not).
```
image edit
```
accepts up to five PNG references totaling 25 MiB; renaming a JPEG to
```
.png
```
does not convert it, and the CLI checks the file signature. These caps are client memory limits, not server limits.
```
raw <METHOD> <PATH> --body '<JSON>'
```
is for a backend operation the user explicitly needs. It accepts only the backend origin, leaves JSON and stream bytes unwrapped, and does not support
```
--events
```
.
```
reference
```
prints the CLI reference locally, without credentials or network.

Rules

On a nonzero exit, report the error and fix its cause before another attempt. Do not loop, fabricate a result, or silently switch models.

With

--json

--events

, a failure prints

{schema_version:1,error:{code,message, http_status?,backend?}}

on stderr and no success result. Never turn a partial stream into a completed answer.

error.backend

carries the backend's own reason, filtered: only

code

type

param

message

detail

and

error

(or

incomplete_details.reason

), each cut to 400 bytes. When it is absent or reads as cut off, tell the user the full cause could not be read instead of guessing. Act on it:

The diagnostic says	Cause	Next step
`backend.code: "unsupported_value"` , `backend.param: "reasoning.effort"`	The model does not take that effort	Pick a level from the model's guide and retry once
`backend.code: "invalid_json_schema"`	The `--schema` file breaks a strict rule	Fix the key the message names; no answer was generated
`backend.detail: "... not supported when using Codex with a ChatGPT account."`	Unknown slug, or a model this plan cannot use	Check `askcodex models` ; ask the user before using another model
`backend.code: "cyber_policy"` or another policy code	A safety classifier blocked the request	Report it; do not reword the request to get around it
`backend.incomplete_details`	The answer was cut short	Report it; narrow the task or ask for less output, then retry once
`code: "rate_limited"` (HTTP 429)	Quota or rate limit	Check `askcodex usage --json --no-refresh` and tell the user

Use
```
--no-refresh
```
for read-only account and auth checks.
```
askcodex auth refresh
```
rotates the credentials and rewrites the auth file; run it only when the user asks for a refresh.
Write into a project directory only when the user asks for that destination.

Report

Tell the user the command you ran, the outcome, the artifact path if one was saved, and any limitation that affects the result. For

ask

, add the model and effort. For an image, give the file's real dimensions and never name a serving model: the backend does not report one. Show an image when the user needs to judge it visually.

Install

The binary is

~/.local/bin/askcodex

. From a checkout,

./install.sh

installs it without touching credentials;

--skills agents

--skills claude

, or

--skills all

also installs this skill, and

--check-auth

checks credentials without refreshing. See the repository and the generated command reference.

askcodex

NPX Install

Tags

SKILL.md Content

askcodex

Context you must respect

Facts already verified (2026-10-02)

Do this

Handle the output

Rules

Report

Install