Pokemon champions team

Pokémon Champions Team

Build, validate, diagnose, tune, and review Pokémon Champions teams. This skill is an orchestrator: its scripts emit deterministic facts, legality verdicts, and auditable evidence; the model makes and explains strategic trade-offs. Never invent a composite team-strength score or an objective "best" team.

Use the sibling skills as factual authorities:

• $pokemon-champions-dex: names, roster, forms, types, stats, abilities, learnsets, and items.
• $pokemon-champions-meta: current or historical usage, common configurations, and partners.
• $ncp-damage-calculator: exact damage, KO/survival, and speed calculations.

Mandatory Protocol

Read references/assisted_workflow.md before every build, diagnose, evaluate, rework, or tune request. It is the authoritative reasoning and routing protocol. The non-negotiable sequence is:

1. Normalize every user-supplied name through the dex, then translate free-form intent into team-json and build-context. The scripts do not parse conversation text.
2. Run context-audit before building or changing a team. Resolve blocking/conflicting gaps and disclose any safe defaults. Keep its audit_receipt.
3. For an open-ended new build, drive intake --next until the guided walk reports done:true. Existing-team analysis does not require onboarding; ask only for blocking/conflicting gaps.
4. Ground a build in current ranking plus real joint evidence (landscape, observed, search, and repset). Run frame with the audit receipt and build on its grounded skeletons. Do not construct joint sets by stitching together independent usage marginals.
5. Assemble 2-5 candidates unless the user explicitly requests one. Run slate-evaluate with the original context, audit receipt, frame output, and frame bindings. Never present an unslated or eliminated candidate.
6. Run checkpoint after every build-flow slate. Surface a required pause unless the user explicitly delegated final convergence or asked not to pause.
7. Run targeted tune only when adjustment intent or explicit benchmarks exist. Bare NCP calls answer as-is fact questions; they do not replace cliff detection for SP tuning.
8. Initialize the response with draft-init, fill its substantive fields, and run answer-audit with the original slate and saved slate output. Fix violations and present only a passing draft.
9. Validate every team before presenting it. Slate survivors carry select facts for the actual 6-pick-3 (single) / 6-pick-4 (double) object; inspect them before making lineup or Mega-route claims. Team-level matchup claims require the full matchup table, not hand-picked calculations.

At entry, state the phases that will run and track them with the host's available plan/checklist tool. If a phase is later dropped, disclose why. The receipt chain is context-audit -> frame -> slate-evaluate -> answer-audit; save every JSON artifact unchanged.

The explicit keyword 建队流程 and its aliases listed in references/assisted_workflow.md enter the full guided flow unconditionally.

Contract Discovery

Do not guess payload shapes. The CLI exposes its commands and structured contracts:

python scripts/team.py schema
python scripts/team.py vocab

schema describes command inputs, team-json, context specs, session specs, and answer drafts. vocab describes enumerated intent fields and which fields are enforced by scripts versus interpreted by the orchestration layer. Read references/schema.md for durable domain and cache contracts.

Core Commands

Parse and validate:

python scripts/team.py parse team.txt --format json
python scripts/team.py validate team.json --context ctx.json --format json
python scripts/team.py diagnose team.json --aspect all --format json

Selection, matchup, and tuning:

python scripts/team.py select team.json --context ctx.json --format json
python scripts/team.py matchup team.json --top-k 20 --context ctx.json --format json
python scripts/team.py matchup actual-sets.json --top-k 60 --matchup-view summary --format json
python scripts/team.py tune team.json --context ctx.json --format json

Run several operators in one process when they belong to the same request:

python scripts/team.py session session.json

The session spec is a JSON array of operations such as validate, diagnose, select, matchup, and tune. Use the shape emitted by schema.

Build Gates

Audit intent and, for new builds, drive intake:

python scripts/team.py context-audit --context ctx.json --format json
python scripts/team.py intake --onboarding --context ctx.json --format json
python scripts/team.py intake --next --context ctx.json --answered format,purpose --format json

Ground and evaluate candidates:

python scripts/team.py landscape --game-format double --context ctx.json --format json
python scripts/team.py observed --game-format double --context ctx.json --format json
python scripts/team.py frame --game-format double --context ctx.json --audit-receipt audit.json --format json
python scripts/team.py slate-evaluate slate.json --frame-output frame.json --format json
python scripts/team.py checkpoint slate-output.json --slate slate.json --format json

Audit the answer:

python scripts/team.py draft-init --slate slate.json --slate-output slate-output.json --format json
python scripts/team.py answer-audit draft.json --slate slate.json --slate-output slate-output.json --format json

For build flows, set frame_required:true in the context/slate and preserve matching receipt files. slate-evaluate eliminates invalid or ungrounded candidates and emits the evidence IDs used by the final answer. answer-audit certifies structure and recomputable claims, not strategic quality.

Real-Team Evidence

The bundled sample library is factual evidence, not a leaderboard:

python scripts/team.py repset Garchomp --game-format double --format json
python scripts/team.py search --game-format double --species Gengar Froslass --format json
python scripts/team.py show <team-id> --game-format double --format json
python scripts/team.py oppmatrix --game-format double --species Garchomp --vs Charizard --format json

Use observed for constraint-shaped retrieval and search/show for exact library inspection. Adopting an observed team is allowed only with the provenance and adoption-review disclosures required by answer-audit. Never silently reproduce a stored team.

Output And Boundaries

• Use canonical English names in structured JSON; render localized names in the final user-facing response through the dex.
• Pass --lang zh|ja|en for human-readable CLI output. JSON remains canonical and language-independent.
• Keep single and double evidence separate. Keep historical regulations explicitly labeled.
• A six-member roster is a preview toolbox: singles selects 3-of-6 and doubles 4-of-6. Do not judge it as a flat six-member battle lineup; only zero or one brought Mega option can be active per battle.
• Expose assumptions, confidence, evidence, trade-offs, and omitted alternatives.
• Do not infer strength from usage, sample performance tags, or provenance tier alone.

References

• references/assisted_workflow.md: mandatory routing, guided intake, grounding, gates, and final audit.
• references/schema.md: team-json, provenance, representative-set/cache, build-context, evidence, and frame contracts.