anycap-worldcup-predict

Q: How do I install anycap-worldcup-predict?

Run npx skills add https://github.com/anycap-ai/anycap --skill anycap-worldcup-predict in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/anycap-worldcup-predict/ (personal) or .claude/skills/anycap-worldcup-predict/ (project).

by anycap-aiProductivity & Automation

World Cup match prediction and pre-match intel for football (soccer) fans: predict who will win and a likely scoreline, backed by structured, verifiable evidence -- player profiles, squad dossiers, current form, head-to-head records, and past-tournament history -- using AnyCap web search and crawl. Weighs FIFA ranking, recent form, head-to-head, and key players, plus any user-defined dimensions (home advantage, injuries, rest, weather, vibes), then makes a clearly-labeled for-fun call with a confidence level and a mandatory disclaimer. Built on the 'search less, not faster' strategy: narrow the search space first, retrieve only what matters, then verify against authoritative sources. Use when a fan wants a World Cup match prediction, predicted score, or who-will-win call; wants a player's profile, bio, form, or stats; wants a full World Cup squad or national-team lineup table; wants to size up two teams before a match; or wants head-to-head and past World Cup context. Trigger on: World

Installs: 573
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/anycap-ai/anycap --skill anycap-worldcup-predict

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads anycap-worldcup-predict automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

AnyCap World Cup Predict

Read this entire file before starting. It defines a reliable workflow for turning a player name (or a whole squad) into structured, verifiable World Cup pre-match intel using AnyCap, then optionally calling a winner and scoreline for fun.

World Cup match prediction and pre-match intel for serious football fans. Turn player names and lineups into structured, verifiable profiles, stats, and matchup briefings so you can read a World Cup matchup before kickoff -- then, if you want, finish with a for-fun prediction (likely winner + scoreline + confidence). Built for World Cup squads and national-team lineups, and works for any footballer.

This skill is about how to retrieve and verify player data. For CLI command reference (flags, output, jq), read the anycap-cli skill and its references/search.md / references/crawl.md.

This skill surfaces public information (profiles, form, historical stats) and can finish with an optional for-fun prediction (likely winner + a playful scoreline) derived from that data. It does not set betting odds, output win probabilities as if they were facts, or place wagers. Every prediction must ship with the disclaimer in predict.md. Treat everything as informational and form your own judgment.

Prerequisites

anycap CLI installed and authenticated (anycap status to verify). Read the anycap-cli skill if setup is needed.
jq for parsing JSON output.

Core Principle: Search Less, Not Faster

Do not crawl the whole web for every player. Narrow the search space first, then retrieve only what matters:

Grounding first -- ask for a structured profile in one shot (anycap search --prompt). This is the fastest path to clean data.
Disambiguate -- when a name is shared by several players, add context (nationality, position, birth year, club) to lock onto the right one.
Verify only when accuracy matters -- cross-check against an authoritative, crawlable source (Wikipedia) instead of trusting a single answer.
Prune, don't dump -- in batch mode, fetch one structured profile per player; never crawl every search result.

Workflow

Goal	Route	Reference
One player's basic info	Grounding structured JSON	lookup.md
Right player when name is shared	Add context / pre-scan with `--query`	lookup.md
High-accuracy, sourced profile	Cross-check vs Wikipedia	verify.md
A whole squad / roster	Loop grounding, aggregate to table	batch.md
Career + current World Cup stats	Grounding stats JSON (with caveats)	stats.md
Size up a matchup (Team A vs Team B)	Build both squads via batch, compare side by side	batch.md
Add past World Cup context	Format, group + knockout results, key players, team history, head-to-head	history.md
Call a winner + scoreline (for fun)	Weigh the gathered layers (plus any user-defined dimensions), then predict with a mandatory disclaimer	predict.md

For a matchup, run the squad workflow for both teams, then layer in historical context (tournament track record + head-to-head from history.md). Present three layers side by side -- squad quality, current form, historical context -- and highlight differences in key positions and availability. Then, if a prediction is wanted, finish with an optional for-fun call (likely winner + playful scoreline + confidence) per predict.md. Always keep the factual layers clearly separated from the prediction, and always attach the disclaimer.

Fast path (single player)

anycap search --prompt 'Give the basic profile of footballer Jude Bellingham as JSON with fields: full_name, date_of_birth, nationality, height, position, current_club, shirt_number, national_team. Only the JSON.' \
  | jq -r '.data.content'

Returns (verified):

{
  "full_name": "Jude Victor William Bellingham",
  "date_of_birth": "2003-06-29",
  "nationality": "English",
  "height": "1.86 m",
  "position": "Midfielder",
  "current_club": "Real Madrid",
  "shirt_number": 5,
  "national_team": "England"
}

Grounding search costs 5 credits per call. General search (--query) and crawl cost 1 credit each.

Output Schema

Normalize every profile to this schema so single-player and batch results are consistent:

Field	Type	Notes
`full_name`	string	Legal/full name
`date_of_birth`	string	`YYYY-MM-DD`; use `null` if unknown
`nationality`	string	Primary nationality
`height`	string	e.g. `1.86 m`; `null` if unknown
`position`	string	e.g. `Midfielder`, `Goalkeeper`
`current_club`	string	Club as of retrieval date
`shirt_number`	int/null	Club or national-team number
`national_team`	string	National team

Rules:

Use null for missing fields. Never invent values.
current_club and shirt_number change frequently -- treat them as point-in-time and note the retrieval date.
When a field cannot be confirmed, mark it and (if accuracy matters) verify via verify.md.

Important: Source Reliability (verified)

Wikipedia is reliably crawlable (anycap crawl https://en.wikipedia.org/wiki/<Player> returns full Markdown). Use it as the primary verification source.
Transfermarkt blocks crawling -- anycap crawl returns a short Human Verification page, not data. Do not rely on crawling it; use grounding search or Wikipedia instead.
Other stats sites may also bot-block. Always check the crawled title/length before trusting content.

Prediction (for fun)

After the factual layers, you may add an optional, clearly-labeled prediction so the briefing is fun to read. See predict.md for the method and the required disclaimer. Non-negotiable rules:

Facts first, prediction last. Never blend the guess into the data tables; put it in its own clearly-marked block.
Always attach the disclaimer from predict.md. A prediction without the disclaimer is incomplete output.
Entertainment, not betting. Do not present win probabilities or odds as facts, do not give wagering advice, and do not tell anyone to bet.
Show the reasoning. Base the call on the gathered signals (ranking, form, head-to-head, key players), not a coin flip.
Let the user steer. Users can add, drop, or re-weight prediction dimensions (e.g. home advantage, injuries, rest, weather, "vibes"). Honor their weights, retrieve any missing data first, and list the final dimension set used. See predict.md.

Limitations

Live data (current club, shirt number, latest stats) reflects whatever the web returns at call time and can lag real events.
Grounding stats numbers are best-effort and can be approximate; verify critical figures against Wikipedia.
Generic player names need disambiguation context or the wrong person may be returned.
This skill retrieves data on demand; it is not a stored database of all players.

Quick Reference

Tool	Purpose
`anycap search --prompt "...JSON..."`	Structured profile / stats in one shot (5 cr)
`anycap search --query "..." --no-crawl`	Find/disambiguate the right player page (1 cr)
`anycap crawl https://en.wikipedia.org/wiki/<Player>`	Authoritative verification source (1 cr)
`anycap status`	Check auth before a batch run

FAQ

What does the anycap-worldcup-predict skill do?

How do I install anycap-worldcup-predict?

Run npx skills add https://github.com/anycap-ai/anycap --skill anycap-worldcup-predict in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/anycap-worldcup-predict/ (personal) or .claude/skills/anycap-worldcup-predict/ (project).

Which AI agents can use anycap-worldcup-predict?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is anycap-worldcup-predict safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains anycap-worldcup-predict?

It is published by anycap-ai in anycap-ai/anycap. It has 573 recorded installs.

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anycap-worldcup-predict

Install

Install

Describe the task

Review the result

SKILL.md

AnyCap World Cup Predict

Prerequisites

Core Principle: Search Less, Not Faster

Workflow

Fast path (single player)

Output Schema

Important: Source Reliability (verified)

Prediction (for fun)

Limitations

Quick Reference

FAQ

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