confer

confer is a skill for Codex from Wang-Cankun/cankun-skills. It costs 111 tokens per session (1,122 once invoked), scanned A, original, MIT.

A way to ask another AI model for a second opinion and continue the same conversation later. It supports Claude, Codex, Pi, and GPT Pro through Oracle when explicitly requested.

In plain words
What is it for?
Use it to open, continue, compare, list, inspect, and troubleshoot cross-model consultations.
Why use it?
It gives you another model's review when you want to test an idea, compare answers, or catch problems before proceeding.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Codex.

Good fit Use it to open, continue, compare, list, inspect, and troubleshoot cross-model consultations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wang-cankun/cankun-skills/confer
Install

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.

Any agent
npx skills add Wang-Cankun/cankun-skills --skill confer
Clone the repo
git clone --depth 1 https://github.com/Wang-Cankun/cankun-skills

Made for: Codex.

Wrote 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.

agentmods badge for confer

README.md
[![agentmods](https://agentmods.dev/badge/skills/wang-cankun/cankun-skills/confer/github.svg)](https://agentmods.dev/skills/wang-cankun/cankun-skills/confer)
Your own site
<a href="https://agentmods.dev/skills/wang-cankun/cankun-skills/confer"><img src="https://agentmods.dev/badge/skills/wang-cankun/cankun-skills/confer/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.

agentmods 80×15 button for confer

Your own site · 80×15
<a href="https://agentmods.dev/skills/wang-cankun/cankun-skills/confer"><img src="https://agentmods.dev/badge/skills/wang-cankun/cankun-skills/confer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 111 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,122 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00111 $0.01122
Opus 5 $0.00056 $0.00561
Sonnet 5 $0.00022 $0.00224
Haiku 4.5 $0.00011 $0.00112

Measured 9d ago against content hash dc2abd9df68d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

confer 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 9d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/confer-test.mjs, scripts/confer.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/confer/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Confer — cross-model consultation with resumable threads

Requires bun plus at least one provider CLI (claude, codex, pi, or Oracle >= 0.16.2 with an authenticated ChatGPT browser profile).

You talk to a peer model through threads: open one with a question, the peer's session id is stored, and any later round — today or next week, from any host session — resumes the same peer-side context. All mechanics live in scripts/confer.mjs (single source of truth); use it instead of assembling provider CLI calls.

scripts/confer.mjs open <provider> [-t name] <prompt|->   # start thread (claude|codex|pi|oracle)
scripts/confer.mjs reply <thread> <prompt|->              # continue with full peer-side context
scripts/confer.mjs all [--with-oracle] <prompt|->         # default claude+codex; flag explicitly adds GPT Pro
scripts/confer.mjs list | show <thread>                   # registry / transcript
scripts/confer.mjs doctor [--live [provider]]             # live defaults to claude+codex

Pass - as the prompt and pipe stdin for anything long or containing quotes.

A round can take minutes. When you expect a long consultation and have other work, run the call in the background and pick the reply up when notified — never relay a peer through a subagent: the peer's own words must reach the user undiluted. Each transcript header records which model answered (and cost/tokens where the CLI reports them).

Steps

  1. Resolve the target. Which provider, and new thread or continuation? "Ask Kimi" routes to pi, whose default model is cation/fw-kimi-k3; set CONFER_PI_MODEL to another model already configured in Pi. Route to oracle only when the user explicitly asks to use/ask GPT Pro or Oracle. Bare all and bare doctor --live remain Claude + Codex; use doctor --live pi to test Pi and all --with-oracle or doctor --live oracle only on explicit request. Otherwise prefer a peer outside your own model family. When the user says 继续/上次/"what does it say now", run list and match the existing thread. Name threads you expect to revisit (-t zhang-pe-review); let one-shots auto-name. Done when: provider + thread decided.

Read the full file on GitHub · 48 lines

Files

What ships with it

4 files 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.

Changes

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.

  1. 9d ago First seen · 48 lines · 111 tokens per session scan A dc2abd9df68d

Subscribe to this mod's changes

confer is a skill published in the GitHub repository Wang-Cankun/cankun-skills (2 stars, last pushed 12d ago), licensed MIT. It adds 111 tokens to every session and 1,122 once invoked, about $0.0006 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.

Related

Other skills, from other repositories

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

google-ads-audit

Google Ads account audit and business context setup. Run this first — it gathers business information, analyzes account health, and saves context that all other ads skills reuse. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should…

nowork-studio/notfair-plugin · 114 tokens

data-charts-tako

Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.

gooseworks-ai/goose-skills · 35 tokens

webhook-management

Configure and validate CCAM webhook targets across supported chat, incident, automation, and generic providers. Use when listing provider requirements, creating or updating a target, scoping it to alert rules, sending a test notification, reviewing delivery history, or deleting a target.

hoangsonww/Claude-Code-Agent-Monitor · 56 tokens

gesellschaftsrechtliche-satzungen-agb

Für Gesellschaftsrechtliche Satzungen AGB Abgrenzung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gesellschaftsrechtliche-satzungen-agb.

Klotzkette/claude-fuer-deutsches-recht · 69 tokens

master-yinguang

A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.

xr843/Master-skill · 274 tokens