| name | chatgpt-direct-api |
| description | Use when Codex should ask ChatGPT through the local Second Braincell runner, use a ChatGPT Project conversation, search or resume ChatGPT chats, upload files/PDFs to ChatGPT, generate images, run Deep Research, or inspect/update ChatGPT Project instructions from any repository. |
| metadata | {"short-description":"Use Second Braincell to talk to ChatGPT"} |
Second Braincell
Use this skill from any local repository to send prompts, files, images, or Deep Research tasks through Second Braincell.
Rules
- Use the direct API CLI. Do not use Playwright, Chrome UI automation, or browser clicking for normal ChatGPT requests.
- Keep
.local/ private. It contains auth headers and must not be printed, committed, copied into docs, or included in outputs.
- Keep generated artifacts in ignored
output/.
- Do not print cookies, auth headers, proof tokens, signed upload URLs, HARs, cURLs, file ids, or account identifiers.
Runner Root
Before running commands, resolve the Second Braincell repo root:
- If the current working directory's
package.json has "name": "second-braincell", use the current directory.
- Else if
SECOND_BRAINCELL_HOME is set, use that path.
- Else if this installed skill directory contains
RUNNER_ROOT.txt, read the repo root from that file.
- Else ask the user to run
npm run install-skill from the cloned Second Braincell repo.
Prefer the global sbc command when it is available:
sbc capabilities
sbc converse --prompt "..."
If sbc is not available, and the runner root differs from the current project, run commands with npm --prefix "$SBC_ROOT" run <script> -- .... For example:
npm --prefix "$SBC_ROOT" run capabilities
npm --prefix "$SBC_ROOT" run converse -- --prompt "..."
Connect
Check setup first:
sbc capabilities
This prints a human-readable readiness summary. Use sbc capabilities --detailed when structured debug JSON is needed.
If connection is missing, ask the user to run:
sbc connect
Connect is clipboard-based. Tell the user to create a new ChatGPT Project named Codex, click the settings button before creating it, and set Project memory to project-only. Then they should open that Project, right-click the ChatGPT page, click Inspect, open DevTools Network, clear the network log button in the top-left of Network (⊘), click the Network filter box directly below it, type conversation, send a short Project message, right-click the conversation request with the orange square <> icon, choose Copy > Copy as cURL, and press Enter in connect. There is no need to paste into the terminal; connect reads from the clipboard and ignores typed or pasted prompt input. The runner stores extracted headers in .local/auth.json and the extracted Project ID in .local/config.json.
If a command returns needs_connect or says the ChatGPT session credentials expired, ask the user to run npm run connect again and copy a fresh authenticated Project conversation cURL.
Commands
Send a text prompt or start a response-aware conversation:
sbc converse --prompt "..."
Use converse as the default path for normal text chat, including one-question requests. It prints ChatGPT's response after each turn, keeps a combined transcript under output/conversations/, and continues the same ChatGPT thread until you end with a blank prompt, /end, end, /done, or done. If converse is run non-interactively with --prompt, it sends one turn and exits.
List recent ChatGPT Project chats:
sbc chats
Default chat listing and search are scoped to the configured ChatGPT Project. Only use --all or another Project when the user explicitly asks to find, inspect, summarize, export, or resume a chat outside the configured Project.
Search ChatGPT chats with ChatGPT's native search:
sbc search-chats "observability roadmap"
sbc search-chats --all "observability roadmap"
For simple questions about what an old chat was about, fetch a lightweight local summary instead of exporting Markdown:
npm run chat-summary -- --search "observability roadmap"
npm run chat-summary -- --all --search "observability roadmap"
Use chat-summary when the user asks to find, identify, or briefly explain a prior chat. Use transcript only when the user asks to export the chat, quote/review the full conversation, or discuss the old chat in depth with Codex.
Read or update the configured ChatGPT Project instructions:
npm run project-instructions
npm run project-instructions -- --set-file ./instructions.md
npm run project-instructions -- --set-file ./instructions.md --yes
Instruction updates require --yes and create a local backup first. Do not update Project instructions unless the user explicitly asks to change them.
Resume a previous ChatGPT Project chat by recent-chat number, conversation id, or local job id:
npm run resume -- 1 --prompt "Pick this back up."
npm run resume -- --search "observability roadmap" --prompt "Continue this thread."
Export a previous ChatGPT Project chat to Markdown:
npm run transcript -- 1
npm run transcript -- --search "observability roadmap"
For lower-level one-shot calls or scripted continuation, ask remains available:
npm run ask -- --prompt "First message."
npm run ask -- --continue-job <previous-job-id> --prompt "Follow-up message."
npm run ask -- --continue-job <latest-job-id> --prompt "Another follow-up."
Use the most recent returned job id for each follow-up. The runner reuses the stored conversation_id and fetches the latest parent message id from ChatGPT before sending. If you already have a ChatGPT conversation id, use --conversation-id <id>; if you also know the exact parent node, use --parent-message-id <id>.
When asked to "chat back and forth with ChatGPT", "have a conversation", "send a follow-up", or otherwise continue context, prefer npm run converse. If using ask directly, always use --continue-job after the first request. Do not simulate continuity by pasting a transcript into a new prompt, and do not put labels like Codex: and ChatGPT: into a new prompt as a substitute for threading.
Prompt Style
When having a multi-message conversation with ChatGPT, send natural user-facing messages. Do not include narrator framing, turn labels, or delegation disclaimers unless the user explicitly asks for them. The prompt should be only what ChatGPT should respond to in that moment.
Avoid prompts like:
I'm Codex, acting on behalf of Bob. Let's have a brief three-turn conversation. Turn 1: pick a practical software/product topic...
Turn 2: We see the usual problem...
Prefer prompts like:
Pick a practical software/product topic you think is worth discussing this week, explain why it matters, and ask me one focused follow-up question.
We see the usual problem: logs, metrics, and traces exist, but they are fragmented across tools, too noisy, and rarely tied cleanly to product impact. What would you do first to make observability more useful without turning it into a large platform project?
Assume the stack is Datadog, Sentry, OpenTelemetry, and scattered product analytics. Give me a crisp final recommendation: one first-week plan, one metric that proves this is helping, and one anti-pattern to avoid.
Use converse or --continue-job for continuity; do not encode the turn number or conversation mechanics into the prompt.
Models
Default to ChatGPT auto mode unless the user asks for a specific model.
npm run ask -- --prompt "..."
npm run ask -- --model auto --prompt "..."
npm run ask -- --model instant --prompt "..."
npm run ask -- --model thinking --reasoning standard --prompt "..."
npm run ask -- --model thinking --reasoning extended --prompt "..."
npm run ask -- --model pro --reasoning standard --prompt "..."
npm run ask -- --model pro --reasoning extended --prompt "..."
npm run ask -- --model 5.3 --prompt "..."
npm run ask -- --model best --prompt "..."
Model meanings:
auto: ChatGPT's Auto mode; this is the default.instant: GPT-5.5 Instant.thinking: GPT-5.5 Thinking with standard or extended.pro: GPT-5.5 Pro with standard or extended, only when the signed-in account has access.5.3: GPT-5.3 Instant legacy fallback.best: use cached model-check results, preferring pro extended, then thinking extended, thinking standard, instant, 5.3, and auto.
Run a model check when connection changes or when model availability matters:
npm run model-check
npm run model-check -- --model pro
If the user explicitly asks for pro and it is unavailable, report that clearly instead of silently falling back. Use best only when the user asks for the best available model or allows fallback. Do not use light or heavy; local endpoint tests returned HTTP 422 for those reasoning values.
Ask about a file:
npm run ask -- --attach-file ./file.pdf --prompt "..."
Generate an image:
npm run ask -- --kind image --quality high --prompt "..."
npm run ask -- --kind image --quality instant --prompt "..."
Run Deep Research:
npm run ask -- --kind deep-research --prompt "..."
Refresh a job:
npm run status -- <job-id>
Normal text chat is synchronous by default. Image generation and Deep Research are async by default.
Default agent behavior for image generation and Deep Research is fire-and-forget: run the submit command, create a thread heartbeat automation when available, confirm the job was submitted, then end the response or move to the user's next task. Creating the heartbeat is required in Codex sessions with automation support. Use a 1-minute heartbeat for image jobs and a 10-minute heartbeat for Deep Research jobs. Do not use the Deep Research 10-minute heartbeat schedule for image jobs. The submit command starts the background watcher.
Do not run status, watch-api-job, sleep loops, polling loops, or wait for the artifact unless the user explicitly asks to wait, check progress, retrieve the result, debug the watcher, or use --sync.
Use the printed status command or npm run watch-api-job -- <job-id> --once only when a manual check is explicitly requested.
