Pp Soccer Goat

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soccer-goat — Printing Press CLI

Prerequisites: Install the CLI

This skill drives the soccer-goat-pp-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:

1. Install via the Printing Press installer. It defaults binaries to $HOME/.local/bin on macOS/Linux and %LOCALAPPDATA%\Programs\PrintingPress\bin on Windows:

   npx -y @mvanhorn/printing-press-library install soccer-goat --cli-only

2. Verify: soccer-goat-pp-cli --version
3. Ensure the reported install directory is on $PATH for the agent/runtime that will invoke this skill.

If the npx install fails (no Node, offline, etc.), fall back to a direct Go install (requires Go 1.26.6 or newer). This installs into $GOPATH/bin (default $HOME/go/bin), so add that directory to $PATH instead:

go install github.com/mvanhorn/printing-press-library/library/media-and-entertainment/soccer-goat/cmd/soccer-goat-pp-cli@latest

If --version reports "command not found" after install, the runtime cannot see the binary directory on $PATH. Do not proceed with skill commands until verification succeeds.

soccer-goat resolves a name once and fans out to Transfermarkt market value, EA Sports FC ratings and attribute stats, sofifa/fifacm potential, and ESPN context, then merges them into a single report. A local SQLite store unlocks cross-source queries no single site can answer: over/under-rated vs the market, potential growth gaps, and wonderkid scouting.

When to Use This CLI

Use soccer-goat when you want a player's or club's market value, game rating, potential, and stats together in one shot, or when you want to run cross-source queries like over/under-rated or wonderkid scouting that need value and rating joined locally. It is the right tool any time the answer spans Transfermarkt plus EA FC plus FIFA-style potential.

Anti-triggers

Do not use this CLI for:

• Do not use for live match scores or fixtures; use a dedicated ESPN or scores tool.
• Do not use for fantasy-football price/points optimization; it reports market value and game ratings, not FPL prices.
• Do not use for betting odds.

Unique Capabilities

These capabilities aren't available in any other tool for this API.

Cross-source reports

• player — Type any player name and get market value, EA FC rating, potential, and key stats in one report.

  Reach for this first: it answers what's he worth, how good is he, how good will he get, in one call.

  soccer-goat-pp-cli player schjelderup --json

• team — Type a club name and get the full squad with each player's market value and rating, plus squad totals.

  Use for scouting a whole squad's value and quality at once instead of N single lookups.

  soccer-goat-pp-cli team benfica --json

• compare — Side-by-side value, rating, potential, and stats for two players.

  Settle debates with value + rating + potential + stats in one view.

  soccer-goat-pp-cli compare mbappe haaland --json

Local joins that compound

• over-under-rated — Flag players whose transfer-market value is far above or below their EA game rating.

  Surfaces market bargains and hype the raw rating alone can't show.

  soccer-goat-pp-cli over-under-rated --team benfica --json

• potential-gap — Rank players by headroom (potential minus current rating).

  Find who still has the most room to grow. Best-effort on potential source.

  soccer-goat-pp-cli potential-gap --team benfica --json

• wonderkids — Find young players with high potential and rising market value.

  The scouting query football data tools can't run because the inputs live in different silos.

  soccer-goat-pp-cli wonderkids --team benfica --max-age 21 --json

Command Reference

clubs — Manage clubs

• soccer-goat-pp-cli clubs <club_name> — Search Clubs

competitions — Manage competitions

• soccer-goat-pp-cli competitions <competition_name> — Search Competitions

players — Manage players

• soccer-goat-pp-cli players <player_name> — Search Players

Finding the right command

When you know what you want to do but not which command does it, ask the CLI directly:

soccer-goat-pp-cli which "<capability in your own words>"

which resolves a natural-language capability query to the best matching command from this CLI's curated feature index. Exit code 0 means at least one match; exit code 2 means no confident match — fall back to --help or use a narrower query.

Recipes

Full player report

soccer-goat-pp-cli player schjelderup

One name in, market value + EA rating + potential + key stats out.

Squad board

soccer-goat-pp-cli team benfica --json --select players.name,players.marketValue,players.rating

Narrow a large squad payload to just name, value, and rating.

Find market bargains

soccer-goat-pp-cli over-under-rated --team benfica

Players the game rates high but the market rates low, and vice versa.

Scout wonderkids

soccer-goat-pp-cli wonderkids --max-age 21 --team benfica

Young, high-potential, rising-value players in one filtered list.

Auth Setup

No authentication required.

Run soccer-goat-pp-cli doctor to verify setup.

Data source (Transfermarkt) and outages

Market value / squad / identity data comes from a Transfermarkt API instance. The CLI ships an ordered default list and fails over automatically on 5xx/unreachable; a source that answers (including "not found") is used as-is.

If player/team/compare exit with code 5 and a "data source is unavailable" hint, every configured Transfermarkt source is down. Recovery, in order of preference:

# See which sources are up:
soccer-goat-pp-cli doctor --agent          # inspect the "sources" array

# Point at a known-working instance for this run (wins over everything, no failover):
soccer-goat-pp-cli player "<name>" --base-url https://your-instance.example --agent

# Or set an ordered failover list for the session:
export SOCCER_GOAT_BASE_URLS=https://a.example,https://b.example

# Most reliable: self-host felipeall/transfermarkt-api (Docker) and point at it:
docker run -p 8000:8000 felipeall/transfermarkt-api:latest
soccer-goat-pp-cli player "<name>" --base-url http://localhost:8000 --agent

Resolution precedence: --base-url > SOCCER_GOAT_BASE_URL > base_url config > SOCCER_GOAT_BASE_URLS > base_urls config > default list. The public instances are best-effort, not guaranteed; self-hosting is the durable path.

Agent Mode

Add --agent to any command. Expands to: --json --compact --no-input --no-color --yes.

• Pipeable — JSON on stdout, errors on stderr

• Filterable — --select keeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:

  soccer-goat-pp-cli clubs mock-value --agent --select id,name,status

• Previewable — --dry-run shows the request without sending

• Offline-friendly — sync/search commands can use the local SQLite store when available

• Non-interactive — never prompts, every input is a flag

• Read-only — do not use this CLI for create, update, delete, publish, comment, upvote, invite, order, send, or other mutating requests

Response envelope

Commands that read from the local store or the API wrap output in a provenance envelope:

{
  "meta": {"source": "live" | "local", "synced_at": "...", "reason": "..."},
  "results": <data>
}

Parse .results for data and .meta.source to know whether it's live or local. A human-readable N results (live) summary is printed to stderr only when stdout is a terminal AND no machine-format flag (--json, --csv, --compact, --quiet, --plain, --select) is set — piped/agent consumers and explicit-format runs get pure JSON on stdout.

Paths and state

Agents should treat the CLI's path resolver as part of the runtime contract:

• Use --home <dir> for one invocation, or set SOCCER_GOAT_HOME=<dir> to relocate all four path kinds under one root.

• Use per-kind env vars only when a specific kind must diverge: SOCCER_GOAT_CONFIG_DIR, SOCCER_GOAT_DATA_DIR, SOCCER_GOAT_STATE_DIR, SOCCER_GOAT_CACHE_DIR.

• Resolution order is per-kind env var, --home, SOCCER_GOAT_HOME, XDG (XDG_CONFIG_HOME, XDG_DATA_HOME, XDG_STATE_HOME, XDG_CACHE_HOME), then platform defaults.

• config contains settings like config.toml and profiles. data contains credentials.toml, data.db, cookies, and auth sidecars. state contains persisted queries, jobs, and teach.log. cache contains regenerable HTTP/cache files.

• Stored secrets live in credentials.toml under the data dir. Existing legacy config.toml secrets are read for compatibility and leave config.toml on the first auth write.

• Run soccer-goat-pp-cli doctor --fail-on warn to surface path and credential-location warnings. agent-context exposes a schema v4 paths block for agents that need the resolved dirs.

• For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags:

  {
    "mcpServers": {
      "soccer-goat": {
        "command": "soccer-goat-pp-mcp",
        "env": {
          "SOCCER_GOAT_HOME": "/srv/soccer-goat"
        }
      }
    }
  }

Fleet precedence: an inherited per-kind env var overrides an explicit --home for that kind. Use SOCCER_GOAT_HOME or per-kind vars as durable fleet levers, and use --home only for a single invocation. Relocation is not reversible by unsetting env vars; move files manually before clearing SOCCER_GOAT_HOME, or doctor will not find credentials left under the former root.

Automatic learning

This CLI ships a self-capturing learning loop. The CLI does its own bookkeeping: every invocation is journaled locally, a failed flag followed by a corrected retry auto-derives a flag_alias candidate, and a teach on a query family without a playbook auto-synthesizes a playbook_candidate from the session's journal. Your job is judgment only: recall first, act on surfaced candidates, teach the final answer, playbook amend when you observe a correction. You never record failures by hand.

Step 1: recall before any discovery

Before list/search/drill commands on a new user question, run:

soccer-goat-pp-cli recall "<user's question>" --agent

The response envelope:

{
  "query": "...",
  "normalized": "<normalized form>",
  "query_entities": ["..."],
  "found": true | false,
  "match_score": 0.0,
  "results": [
    { "resource_id": "...", "resource_type": "...", "venue": "...",
      "confidence": 2, "entity_match": "exact|partial|unknown",
      "source": "taught|preseed|pattern", "warnings": ["..."] }
  ],
  "mismatches": [ /* only when --debug-mismatches */ ],
  "warnings": [ /* top-level */ ],
  "candidates": [
    { "id": 12, "class": "flag_alias | playbook_candidate",
      "summary": "...", "sightings": 3, "last_seen": "...",
      "rationale": "...",
      "next_action": ["<trial command>", "soccer-goat-pp-cli learnings confirm 12"] }
  ],
  "playbook": {
    "query_family": "...",
    "playbook": {
      "steps": [ { "cmd": "<command with {slot} substitution>", "purpose": "..." } ],
      "entity_slots": ["$ENTITY"],
      "expected_tool_calls": 3
    },
    "slots_resolved": { "$ENTITY": { "token": "<live token>", "canonical": "<canonical>" } },
    "notes": "<workarounds + gotchas for this query family>"
  },
  "notes": "<duplicate surface for non-playbook callers>"
}

Empty-store short-circuit: if the store has no learnings, playbooks, or candidates yet (recall finds nothing and learnings list and learnings candidates are both empty), skip recall for the rest of this session instead of taxing every query; resume recall-first once something has been taught.

Step 2: decision tree

Read candidates, playbook, notes, results[0], and warnings in that order:

if Candidates present (warnings include "candidates_present"):
    -> candidates are try-then-confirm, never facts. Follow each candidate's
       two-step next_action verbatim: run the trial command first, then run
       `learnings confirm <id>` only after the trial verified the behavior.
       Reject a wrong candidate with `learnings reject <id>`.
    -> NEVER re-teach something recall surfaced as a candidate; confirm or
       reject that candidate instead of teaching a duplicate.
    -> candidates ride alongside playbooks and resource hits, not instead of
       them; continue with the branches below after acting on them.

if Playbook present:
    -> READ Playbook.notes verbatim FIRST (workarounds + gotchas the CLI surface doesn't expose)
    -> replay Playbook.steps in order, substituting Playbook.slots_resolved entries
       for the entity slot tokens. If a step's slot is unresolved, fall back to
       discovery for that step only.
    -> the Playbook's expected_tool_calls is a budget; if you find yourself running
       materially more, record the divergence via `soccer-goat-pp-cli playbook amend`
       at end-of-session.

elif Notes present (no Playbook):
    -> read Notes verbatim before any discovery step; they carry known gotchas
       for this query family even when no structured choreography exists yet.

elif Found AND Results[0].EntityMatch == "exact" AND Results[0].Confidence >= 2:
    -> skip discovery; fetch live data for Results[*].ResourceID in parallel

elif Found AND Results[0].EntityMatch == "partial":
    -> candidate hint, NOT a hit; read the resource title to validate before trusting

elif (any row in Mismatches[] when --debug-mismatches was passed):
    -> treat as cold start; the stored learning is for a different entity
       (different canonical resolved from query_entities)

else:  // Found == false, no playbook, no notes
    -> cold start; run discovery normally; teach the answer afterward (Step 4).
       If the family has no playbook yet, that teach auto-synthesizes a
       playbook candidate from this session's journal - you do not need to
       record one by hand.

Playbook and Notes are orthogonal to the per-resource path. A recall response can carry both a Playbook AND a Results[] hit - use both: the Playbook tells you which choreography to run; the resource hits short-circuit specific steps. Default to skipping mismatches; pass --debug-mismatches only when investigating cold-start surprises.

Candidate judgment details: learnings confirm <id> prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. learnings reject <id> tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; soccer-goat-pp-cli learnings candidates lists the full open set.

Graceful degradation: if learnings confirm is an unknown command, you are driving an older binary - ignore the candidates guidance and follow the rest of the protocol.

Step 3: always read warnings

• low_confidence: row exists at confidence<2. Treat as a hint, not a skip-discovery hit.
• resource_not_in_store: the local store doesn't have the resource the learning points at. The match validator couldn't classify entities — direct-fetch and re-evaluate.
• cross_alias_match (per-result): the row was taught under a different alias and matched the live query's canonical via entity_lookups (e.g., a "USA" teach satisfying a "United States" recall). Trust the resource_id.
• similar_shape_different_entity:<canonical> (top-level): a structurally matching row exists but its canonical entity differs from the live query's. Treated as cold start; the warning carries the conflicting canonical as a hint, but the row is NOT promoted into Results.
• ambiguous_alias (top-level): a single query entity resolved to multiple canonicals (e.g., "Cards" → Arizona Cardinals + St. Louis Cardinals). Surface the ambiguity from context before committing to a resource.
• candidates_present (top-level): the envelope carries a candidates section. Handle it via the candidates branch in Step 2 before anything else.
• lookup_refresh_available (top-level): an entity in the query has no lookup row yet, but synced data could provide one. Run soccer-goat-pp-cli sync to refresh entity lookups.
• Top-level no_learnings_for_query_family: the table had no rows above the Jaccard floor. Pure cold start.