Borrowing it
Nothing to install: this file belongs to yusifeng/formax. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yusifeng/formax/main/.codex/skills/webgpt-todo-response/SKILL.mdgit clone --depth 1 https://github.com/yusifeng/formaxWrote 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/yusifeng/formax/webgpt-todo-response)<a href="https://agentmods.dev/skills/yusifeng/formax/webgpt-todo-response"><img src="https://agentmods.dev/badge/skills/yusifeng/formax/webgpt-todo-response/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.
<a href="https://agentmods.dev/skills/yusifeng/formax/webgpt-todo-response"><img src="https://agentmods.dev/badge/skills/yusifeng/formax/webgpt-todo-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00066 | $0.00975 |
| Opus 5 | $0.00033 | $0.00487 |
| Sonnet 5 | $0.00013 | $0.00195 |
| Haiku 4.5 | $0.00007 | $0.00097 |
Grade A, and why
webgpt-todo-response 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 10d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WebGPT Todo Response
Purpose
Generate the message to send back to WebGPT after we have read its previous
analysis and drafted or updated docs/todolist.md.
Use this skill when the user asks:
- whether we have rebuttals or questions for WebGPT
- what to include when sending our todo back to WebGPT for another pass
- to prepare a response asking WebGPT to evaluate, improve, or challenge our todo
- to compare WebGPT's recommendations against our chosen implementation scope
Inputs To Inspect
Read only the files needed for the current handoff:
- WebGPT response, usually under
repomix-output/ - current todo, usually
docs/todolist.md - relevant canonical docs under
docs/contracts/*,docs/frontend/*, or other explicitly governing docs when the todo depends on them - optional other LLM replies if the user asks for a multi-model synthesis
Do not re-run broad repository analysis unless the todo or WebGPT response depends on code facts that are unclear.
Workflow
-
Identify WebGPT's strongest recommendations.
- Mark which ones are adopted in the todo.
- Mark which ones are intentionally deferred.
- Mark which ones are rejected or still need clarification.
-
Check the todo against Formax boundaries.
- Canonical semantics belong in
docs/contracts/*and canonical runtime layers, not only UI. - Web reference UI should reflect runtime/platform truth, not invent it.
- Do not move thread/runtime state ownership into ad hoc component-local logic when the task is structurally runtime-driven.
- Preserve parity-sensitive behavior when relevant: transcript surface semantics, URL/thread sync, prompt/tool exposure boundaries, permissions flow, and active-thread canonical gating.
- Avoid turning a focused task into a broad cleanup or cross-subsystem redesign unless explicitly requested.
- Canonical semantics belong in
-
Find weak spots in the todo.
- Missing canonical-doc step
- Missing data/type/interface step before UI
- Runtime state ownership drift
- Welcome/draft/thread semantics being mixed together
- Scope creep into unrelated app-server, terminal, diff, approval, or desktop integration work
- Missing tests or review gates
- Missing statement of protocol constraints or non-atomic failure boundaries
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.
- 10d ago First seen · 114 lines · 66 tokens per session scan A 1def8bdb6c2e
webgpt-todo-response is a skill published in the GitHub repository yusifeng/formax (193 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 975 once invoked, about $0.0003 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 2026-08-30.
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