{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_betafish-js","slug":"betafish-js","name":"Betafish.js","type":"webapp","url":"https://betafish.gavinong.com","page_url":"https://unfragile.ai/betafish-js","categories":["data-analysis"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_betafish-js__cap_0","uri":"capability://data.processing.analysis.fen.based.chess.position.import.and.export","name":"fen-based chess position import and export","description":"Parses Forsyth-Edwards Notation (FEN) strings to reconstruct complete chess board states including piece placement, active player, castling rights, en passant targets, and move counters. Enables bidirectional conversion between FEN format and internal board representation, allowing users to load specific positions from games or export analyzed positions for external use. Implements standard FEN parsing with validation of piece placement, turn indicators, and special move flags.","intents":["Load a specific chess position from my game database or PGN notation for analysis","Export an analyzed position in FEN format to share with other chess tools or players","Analyze endgame positions or puzzle positions without replaying entire games","Integrate position data from Lichess, Chess.com, or other platforms that use FEN"],"best_for":["Chess students and coaches analyzing specific positions from their games","Players integrating analysis into study workflows across multiple platforms","Developers building chess analysis pipelines that need position interchange"],"limitations":["FEN format is position-only — does not preserve game history or move sequence","No validation of position legality (e.g., impossible pawn placements or multiple kings)","Cannot reconstruct full game context from FEN alone, only current board state"],"requires":["Valid FEN string in standard notation (8 fields separated by spaces)","Modern browser with JavaScript ES6+ support"],"input_types":["text (FEN string)"],"output_types":["text (FEN string)","structured data (board state object)"],"categories":["data-processing-analysis","chess-notation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_1","uri":"capability://planning.reasoning.configurable.search.depth.chess.engine.analysis","name":"configurable search depth chess engine analysis","description":"Executes minimax-based chess position evaluation with adjustable search depth (thinking time) to balance analysis quality against computation latency. Implements alpha-beta pruning to reduce the game tree search space, allowing users to control the trade-off between deeper analysis and faster results. The thinking time parameter directly maps to search depth, enabling users to analyze positions in seconds (shallow) or minutes (deep) depending on device capability and analysis requirements.","intents":["Analyze a position with quick shallow evaluation for rapid feedback during game review","Run deep analysis on critical positions to find best moves and tactical patterns","Adjust analysis depth based on my device's processing power to avoid browser freezing","Compare how evaluation changes as the engine thinks deeper about a position"],"best_for":["Individual chess players studying positions on consumer hardware","Students who need flexible analysis depth without cloud dependencies","Players with varying device capabilities (mobile, laptop, desktop)"],"limitations":["Browser-based computation means analysis speed is bounded by client CPU, not cloud resources — deep analysis on complex positions may take minutes","Alpha-beta pruning effectiveness depends on move ordering heuristics; poor heuristics reduce pruning efficiency","No distributed computing or GPU acceleration — single-threaded JavaScript execution limits practical search depth to ~8-10 plies on typical hardware","Blocking UI during analysis — no background worker implementation mentioned, so browser becomes unresponsive during deep searches"],"requires":["Modern browser with JavaScript execution (Chrome, Firefox, Safari, Edge)","Sufficient CPU and RAM for minimax tree expansion (typically 512MB+ for deep searches)","No external API calls — entirely local computation"],"input_types":["structured data (board state)","integer (search depth or thinking time in seconds)"],"output_types":["structured data (evaluation score, best move, principal variation)","numeric (centipawn advantage)"],"categories":["planning-reasoning","chess-engine"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_2","uri":"capability://data.processing.analysis.real.time.position.evaluation.scoring","name":"real-time position evaluation scoring","description":"Computes numeric evaluation scores (in centipawns) for chess positions using a heuristic evaluation function that assesses material balance, piece positioning, pawn structure, and king safety. Returns evaluation from the perspective of the side to move, with positive scores indicating advantage for the moving player and negative scores indicating disadvantage. Updates evaluation dynamically as the engine searches deeper, allowing users to observe how the assessment changes with additional computation.","intents":["See a numeric score for the current position to understand who is winning","Watch the evaluation change as the engine thinks deeper to understand position complexity","Compare evaluations across different positions to assess relative advantage","Identify if a position is winning, drawn, or losing based on the score"],"best_for":["Chess players learning position evaluation and material counting","Students analyzing whether their moves improved or worsened their position","Coaches reviewing games to identify critical turning points"],"limitations":["Evaluation function is heuristic-based and may not match human intuition in complex positions, especially endgames with non-obvious strategic factors","Centipawn scores are relative to the evaluation function's weights — different engines produce different scores for identical positions","No distinction between 'winning' and 'drawn' positions in the numeric score alone; requires additional analysis","Evaluation assumes optimal play from both sides; does not account for opponent skill level or practical winning chances"],"requires":["Valid chess position (board state)","Completed search or partial search results from the minimax engine"],"input_types":["structured data (board state)"],"output_types":["numeric (centipawn score, typically -3000 to +3000)","text (human-readable assessment like 'White is winning')"],"categories":["data-processing-analysis","chess-engine"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_3","uri":"capability://planning.reasoning.best.move.recommendation.with.principal.variation","name":"best move recommendation with principal variation","description":"Identifies the strongest move in a position by selecting the move with the highest evaluation score from the minimax search tree, and returns the principal variation (PV) — the sequence of best moves both sides would play in response. Implements move ordering heuristics (killer moves, history heuristics) to prioritize promising moves early in the search, improving alpha-beta pruning efficiency. Returns both the recommended move in algebraic notation and the full line of play that justifies the recommendation.","intents":["Get the best move recommendation for the current position","See the expected line of play (principal variation) to understand why a move is best","Analyze what happens after I play the recommended move","Compare alternative moves by seeing their evaluations and resulting lines"],"best_for":["Chess players seeking move suggestions during game analysis","Students learning tactical patterns by studying recommended lines","Coaches preparing opening repertoires or endgame positions"],"limitations":["Move recommendation is only as strong as the search depth — shallow searches may miss tactics or strategic ideas","Principal variation assumes both players play optimally; does not account for practical considerations or opponent tendencies","Move ordering heuristics may fail in unusual positions, causing the engine to explore inferior moves first and reduce pruning effectiveness","No explanation of WHY a move is best — only the move and the resulting line; requires user interpretation"],"requires":["Valid chess position","Completed minimax search with sufficient depth (minimum 4-6 plies for reasonable recommendations)"],"input_types":["structured data (board state)","integer (search depth)"],"output_types":["text (move in algebraic notation, e.g., 'e4', 'Nf3')","text (principal variation as sequence of moves)","numeric (evaluation score of the recommended move)"],"categories":["planning-reasoning","chess-engine"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_4","uri":"capability://automation.workflow.interactive.board.state.manipulation.and.visualization","name":"interactive board state manipulation and visualization","description":"Provides a graphical chess board interface that allows users to place pieces, set up custom positions, and visualize the current board state with piece symbols and square highlighting. Implements click-based piece movement with validation to ensure moves are legal (no moving opponent pieces, respecting piece movement rules). Updates the visual board representation in real-time as positions change, and maintains internal board state synchronized with the displayed board.","intents":["Set up a custom chess position by clicking pieces onto the board","Play moves against the engine by clicking pieces and dragging to destination squares","Visualize the current position clearly with piece symbols and board coordinates","Highlight legal moves for the selected piece to understand available options"],"best_for":["Chess players who prefer graphical board interaction over notation entry","Casual players learning chess who benefit from visual feedback","Users analyzing positions without prior experience with algebraic notation"],"limitations":["Click-based interaction may be slow for rapid position setup compared to FEN import","No drag-and-drop or multi-piece selection — each piece must be moved individually","Board visualization is 2D static rendering; no 3D board or animated piece movement","No undo/redo functionality mentioned — users cannot easily correct mistakes during position setup"],"requires":["Modern browser with DOM manipulation and event handling (JavaScript)","Mouse or touch input device","Screen resolution sufficient to display 8x8 board clearly (minimum ~400x400 pixels)"],"input_types":["user interaction (mouse clicks, piece selection)","text (FEN for position import)"],"output_types":["visual (rendered chess board with pieces)","structured data (board state object)"],"categories":["automation-workflow","chess-ui"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_5","uri":"capability://automation.workflow.browser.based.local.computation.without.cloud.dependency","name":"browser-based local computation without cloud dependency","description":"Executes all chess engine analysis entirely within the browser using JavaScript, eliminating the need for external API calls or cloud servers. The engine runs as client-side code, processing positions and computing evaluations on the user's device without transmitting position data to remote servers. This architecture ensures privacy (positions never leave the device), offline functionality (analysis works without internet), and zero latency for engine communication (no network round-trips).","intents":["Analyze chess positions offline without requiring an internet connection","Keep my game analysis private without sending positions to external servers","Avoid API rate limits or subscription costs associated with cloud-based engines","Analyze positions with minimal latency since computation is local"],"best_for":["Players in regions with unreliable internet connectivity","Users concerned about privacy and data transmission","Budget-conscious players avoiding subscription-based analysis services","Developers building offline-first chess applications"],"limitations":["Analysis speed is limited by client CPU — cannot leverage cloud computing power or GPU acceleration","Deep analysis on complex positions may cause browser to freeze or become unresponsive due to blocking JavaScript execution","Memory constraints of browser environment limit the size of transposition tables and search trees","No parallelization — JavaScript is single-threaded, so multi-core CPUs cannot be fully utilized","Requires users to download and run the entire engine code in their browser, increasing initial load time"],"requires":["Modern browser with JavaScript ES6+ support (Chrome, Firefox, Safari, Edge)","Sufficient local CPU and RAM for minimax computation","No external dependencies or API keys required"],"input_types":["structured data (board state)"],"output_types":["structured data (evaluation, best move, principal variation)"],"categories":["automation-workflow","privacy-architecture"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_6","uri":"capability://automation.workflow.move.legality.validation.and.piece.movement.rules.enforcement","name":"move legality validation and piece movement rules enforcement","description":"Validates that moves conform to chess rules by checking piece movement patterns (pawns move forward one square or two from starting position, knights move in L-shape, bishops move diagonally, rooks move horizontally/vertically, queens move any direction, kings move one square). Prevents illegal moves such as moving into check, capturing your own pieces, or moving opponent pieces. Implements special move handling for castling (king and rook movement with position requirements), en passant (pawn capture of enemy pawn that just moved two squares), and pawn promotion (automatic or user-selected piece).","intents":["Ensure only legal moves are played during interactive board analysis","Prevent accidental illegal moves by validating moves before executing them","Handle special moves like castling, en passant, and pawn promotion correctly","Reject moves that would leave the king in check"],"best_for":["Chess players learning the rules and needing move validation feedback","Developers building chess applications that require strict rule enforcement","Casual players who want the system to prevent illegal moves"],"limitations":["Move validation adds computational overhead to every move — may cause slight UI lag on slower devices","No distinction between illegal moves and impossible moves in error messaging","Pawn promotion requires user input to select piece; no default promotion handling mentioned","No validation of position legality after move execution (e.g., detecting impossible positions)"],"requires":["Valid board state with piece positions","Source and destination squares for the move","Current player turn information"],"input_types":["structured data (board state, source square, destination square)"],"output_types":["boolean (move is legal or illegal)","text (error message if move is illegal)"],"categories":["automation-workflow","chess-rules"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_betafish-js__cap_7","uri":"capability://memory.knowledge.game.state.persistence.and.move.history.tracking","name":"game state persistence and move history tracking","description":"Maintains a complete record of moves played during a game session, allowing users to navigate backward and forward through the move history to review the game progression. Stores each position state and the move that led to it, enabling undo/redo functionality and position replay. Implements move history as a linear sequence (no branching variations), allowing users to step through the game move-by-move or jump to specific positions.","intents":["Review my game by stepping backward through moves to see how the position evolved","Undo a move if I made a mistake during interactive analysis","Jump to a specific move in the game to analyze that position","Compare positions at different points in the game to understand the game flow"],"best_for":["Players reviewing their own games move-by-move","Students analyzing game progression and critical moments","Coaches reviewing student games with detailed position analysis"],"limitations":["Move history is linear — no support for analyzing multiple variations or branches from a single position","No persistence across browser sessions — move history is lost when the page is closed unless explicitly exported","No branching variations — cannot explore 'what if' scenarios without overwriting the original game","Memory usage grows with game length — very long games (100+ moves) may consume significant browser memory"],"requires":["Valid board state","Move history data structure (array or linked list of moves)"],"input_types":["structured data (move in algebraic notation or source/destination squares)"],"output_types":["structured data (updated board state after move)","text (move history as sequence of moves)"],"categories":["memory-knowledge","chess-game-state"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"low","permissions":["Valid FEN string in standard notation (8 fields separated by spaces)","Modern browser with JavaScript ES6+ support","Modern browser with JavaScript execution (Chrome, Firefox, Safari, Edge)","Sufficient CPU and RAM for minimax tree expansion (typically 512MB+ for deep searches)","No external API calls — entirely local computation","Valid chess position (board state)","Completed search or partial search results from the minimax engine","Valid chess position","Completed minimax search with sufficient depth (minimum 4-6 plies for reasonable recommendations)","Modern browser with DOM manipulation and event handling (JavaScript)"],"failure_modes":["FEN format is position-only — does not preserve game history or move sequence","No validation of position legality (e.g., impossible pawn placements or multiple kings)","Cannot reconstruct full game context from FEN alone, only current board state","Browser-based computation means analysis speed is bounded by client CPU, not cloud resources — deep analysis on complex positions may take minutes","Alpha-beta pruning effectiveness depends on move ordering heuristics; poor heuristics reduce pruning efficiency","No distributed computing or GPU acceleration — single-threaded JavaScript execution limits practical search depth to ~8-10 plies on typical hardware","Blocking UI during analysis — no background worker implementation mentioned, so browser becomes unresponsive during deep searches","Evaluation function is heuristic-based and may not match human intuition in complex positions, especially endgames with non-obvious strategic factors","Centipawn scores are relative to the evaluation function's weights — different engines produce different scores for identical positions","No distinction between 'winning' and 'drawn' positions in the numeric score alone; requires additional analysis","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.714Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=betafish-js","compare_url":"https://unfragile.ai/compare?artifact=betafish-js"}},"signature":"0+I+blbO/1+DA8kAcvL72tdOB6mHWDBYT/cDxxHnqUSl6XrYrb+rNrYxujN0Vp41k/qZm6dADzuUunIc7Tr5DQ==","signedAt":"2026-06-19T23:51:36.158Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/betafish-js","artifact":"https://unfragile.ai/betafish-js","verify":"https://unfragile.ai/api/v1/verify?slug=betafish-js","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}