ConferenceWatch

An Agent Skill that watches upcoming AI/ML conferences and reports, for each one: submission deadlines (every stage), dates, location, special sessions / call for papers, official web links, and a 5-year acceptance-rate trend. It is written to be reusable across common coding agents that can search the web — Claude Code, Codex, and similar.

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What it produces

Every run yields two artifacts:

1. conferences.<date>.json — the structured source of truth. One object per conference (keyed by acronym), each holding the upcoming edition (deadlines, location, special sessions, links) and a 5-year acceptance-rate trend. Schema: references/json-schema.md.
2. conference-report.<date>.md — a human-readable report with a short summary, a nearest-deadlines table, a per-conference breakdown, and a clearly separated "approximate / inferred" section. Template: assets/report.template.md.

The agent also answers directly in chat with the most time-sensitive items.

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How to use

This skill is plain Markdown + JSON, so it can be used by Codex, Claude Code, or any agent that can read SKILL.md, search/fetch the web, and write files.

Install for Codex

Clone directly into Codex's personal skills directory:

git clone https://github.com/Zsun79/ConferenceWatch.git ~/.codex/skills/conference-watch

If you already cloned the project somewhere else, run this from the root of this cloned skill repository to link the current checkout into Codex:

mkdir -p ~/.codex/skills
ln -s "$(pwd)" ~/.codex/skills/conference-watch

Then ask Codex naturally for AI/ML conference deadlines, venue comparisons, or submission planning. Codex will use SKILL.md as the workflow when the request matches the skill description.

Install for Claude Code

Clone directly into Claude's personal skills directory:

git clone https://github.com/Zsun79/ConferenceWatch.git ~/.claude/skills/conference-watch

If you already cloned the project somewhere else, run this from the root of this cloned skill repository to link the current checkout into Claude:

mkdir -p ~/.claude/skills
ln -s "$(pwd)" ~/.claude/skills/conference-watch

If this checkout is the project where you want Claude to load the skill, run this from the repository root to link the current directory into .claude/skills/conference-watch:

mkdir -p .claude/skills
ln -s "$(pwd)" .claude/skills/conference-watch

The skill activates from its description when your request matches.

Use with other agents

For agents without a dedicated skill folder, use this repository as a local instruction bundle:

• Point the agent at SKILL.md as the task instructions.
• Keep references/conference-catalog.md, references/json-schema.md, and the files in assets/ available as supporting context.
• Ask the agent to follow the workflow and write the JSON/report artifacts into your project folder.

Requirement: the host agent must have a web search / fetch capability (and, to save files, filesystem access). No API keys or build step required.

Example prompts

> What are the deadlines for the top NLP conferences in the next 6 months?
> Track NeurIPS, ICML, and ICLR 2026 for me.
> Compare the top-tier CV venues by acceptance rate and next deadline.
> List the top 5 AI conferences with deadlines before end of 2026.
> I work in computer vision -- track the A* venues and show acceptance-rate trends.
> Just give me the top conferences, I don't want to specify an area.

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How it works (workflow)

The full logic lives in SKILL.md. In short:

flowchart TD
    A[Anchor on today's date] --> B[Analyze request and narrow scope]
    B --> C{Named venues or clear filters?}
    C -- No --> D[Ask 1-3 follow-up questions<br/>or use top-venue defaults]
    C -- Yes --> E[Build initial conference JSON]
    D --> E
    E --> F[Confirm candidate conference list]
    F --> G[Research upcoming edition first<br/>official CFP and important dates]
    G --> H[Collect every deadline stage,<br/>location, sessions, and links]
    H --> I[Gather last 5 editions<br/>acceptance-rate trend]
    I --> J{Upcoming dates confirmed?}
    J -- Yes --> K[Mark confirmed with sources]
    J -- No --> L[Infer approximate window<br/>from historical pattern]
    K --> M[Validate JSON]
    L --> M
    M --> N[Write JSON dataset]
    M --> O[Write Markdown report]
    N --> P[Answer in chat<br/>nearest deadlines first]
    O --> P

1. Anchor on today's date — all "future vs past" decisions are relative to the current date, not the model's training cutoff.
2. Analyze the request & narrow scope — the agent asks 1–3 follow-up questions to filter by area (NLP/CV/RL/…), reputation/tier (CORE A*/A/B), difficulty (acceptance rate), and horizon. If you decline, it defaults to the top AI venues (see references/conference-catalog.md).
3. Build the initial JSON — the candidate conference list is written out first, then confirmed with you before the long search phase.
4. Research the upcoming edition first — searches official CFP/"important dates" pages, records every deadline stage, location, special sessions, and links; marks them confirmed with sources.
5. Historical anchor (last 5 editions) — builds the acceptance-rate trend and, when a future edition isn't announced yet, infers an approximate deadline window from the historical pattern — always flagged as approximate.
6. Output — validates the JSON, writes the Markdown report with a short synthesized summary, and answers in chat.

Core rule: never fabricate dates. Anything not on an authoritative source is either null (with a note) or clearly marked approximate/inferred.

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Repository layout

ConferenceWatch/
├── SKILL.md                          # main skill: workflow + rules (entry point)
├── README.md                         # this file
├── references/
│   ├── conference-catalog.md         # curated venues by area/tier + source sites
│   └── json-schema.md                # JSON schema + field rules
└── assets/
    ├── conference-data.template.json # starting JSON structure
    └── report.template.md            # Markdown report template

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Notes & limitations

• Deadlines and rankings change; the skill confirms on official sites and cites sources, but always re-check the CFP before submitting.
• Acceptance-rate numbers can differ by source (main track vs. all tracks); the skill records the source alongside each figure.
• Inferred future dates are estimates only — labeled approximate everywhere.
• ⚠️ Generated reports are marked PRIVATE classification by default; handle the output accordingly.