{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_songs-like-x","slug":"songs-like-x","name":"Songs Like X","type":"webapp","url":"https://songslikex.com","page_url":"https://unfragile.ai/songs-like-x","categories":["voice-audio"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_songs-like-x__cap_0","uri":"capability://search.retrieval.single.track.audio.similarity.matching.with.playlist.generation","name":"single-track audio similarity matching with playlist generation","description":"Analyzes acoustic and metadata features of a user-provided song to identify similar tracks across a music database, then synthesizes results into a ranked playlist. The system likely uses audio fingerprinting (e.g., Spotify's Echo Nest API or MusicBrainz) combined with collaborative filtering on track embeddings to surface recommendations. Results are ordered by similarity score and presented as a browsable playlist without requiring user authentication or streaming service integration.","intents":["I want to find songs similar to a track I love without manually searching through streaming platforms","I need to discover lesser-known artists and deep cuts in a genre I already enjoy","I want to break out of algorithmic bubbles by getting recommendations outside my usual listening patterns","I need quick song suggestions for a specific mood or vibe without building a full playlist manually"],"best_for":["casual music listeners seeking friction-free discovery","indie musicians researching competitive sound landscapes","playlist curators looking for quick inspiration without streaming service logins","music fans exploring niche genres with limited algorithmic exposure"],"limitations":["No collaborative filtering across user listening history — treats each query in isolation, limiting personalization depth","Lacks real-time streaming service integration, requiring manual song addition to playlists post-discovery","Recommendation model likely trained on smaller dataset than Spotify/Apple Music, reducing accuracy for obscure or very recent tracks","No contextual filtering by mood, era, or subgenre — returns similarity matches without semantic refinement","Single-song input constraint prevents multi-track context (e.g., 'songs like X but with Y's energy')"],"requires":["Web browser with JavaScript enabled","Song title and artist name (or ability to search/identify track in underlying music database)","No authentication or API keys required for free tier"],"input_types":["text (song title + artist name)","potentially audio fingerprint or Spotify/Apple Music track URI if integrated"],"output_types":["structured playlist (JSON or HTML list with track metadata)","similarity scores per recommendation","track metadata (artist, album, release year, preview/stream links if available)"],"categories":["search-retrieval","music-discovery"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_songs-like-x__cap_1","uri":"capability://search.retrieval.music.database.search.and.track.identification","name":"music database search and track identification","description":"Provides a search interface to locate and identify songs within the underlying music database, accepting partial matches on song title, artist name, or album. The system likely queries a music metadata API (MusicBrainz, Last.fm, or Spotify) with fuzzy matching to handle typos and variations in artist/song naming. Results are ranked by relevance and presented with standardized metadata (artist, album, release year, ISRC code if available).","intents":["I want to find the exact song I'm thinking of when I only remember partial lyrics or artist name","I need to verify a song exists in the recommendation database before requesting similar tracks","I want to explore an artist's discography to find specific tracks for similarity matching"],"best_for":["users with imperfect song recall needing fuzzy matching","music researchers validating track availability across databases","casual listeners unfamiliar with exact song/artist naming conventions"],"limitations":["Fuzzy matching may return false positives for common song titles (e.g., 'Love Song' by multiple artists)","Limited to songs in underlying database — very recent releases or independent/underground tracks may not be indexed","No filtering by region, language, or release format (vinyl vs. digital) — returns global results only","Search latency depends on database size and query complexity; no caching of popular searches"],"requires":["Web browser with JavaScript enabled","Text input capability (keyboard or voice-to-text)"],"input_types":["text (song title, artist name, album name, or partial combinations)"],"output_types":["ranked list of matching tracks with metadata (artist, album, year, ISRC)","relevance scores per result","clickable track cards linking to similarity analysis"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_songs-like-x__cap_2","uri":"capability://search.retrieval.playlist.composition.and.ranking.by.similarity.score","name":"playlist composition and ranking by similarity score","description":"Aggregates similarity-matched tracks into a coherent playlist, ranking results by a composite similarity score derived from audio features (tempo, key, energy, danceability) and metadata similarity (genre, era, artist collaborations). The system likely normalizes individual similarity metrics and applies a weighted ranking algorithm to surface the most relevant recommendations first. Playlist structure may include optional metadata like average BPM, dominant genre, or mood tags for user context.","intents":["I want recommendations ordered by how closely they match my original song, not randomly shuffled","I need to understand why a song was recommended (similarity reasoning) to evaluate its relevance","I want a playlist long enough for continuous listening (20-50 tracks) without manual curation"],"best_for":["users building workout or study playlists with consistent energy/tempo","DJs researching track transitions based on audio feature similarity","music producers studying sonic characteristics of comparable artists"],"limitations":["Similarity scoring is opaque to end users — no explainability for why Track A ranks higher than Track B","Weighted ranking algorithm may over-emphasize audio features (tempo, energy) at expense of cultural/contextual similarity","No dynamic reranking based on user feedback — playlist order is static once generated","Playlist length is fixed or limited (likely 20-50 tracks) rather than infinite scrolling or pagination","No deduplication of artists — may return multiple songs by the same artist, reducing discovery breadth"],"requires":["Successful track identification from prior search step","Access to audio feature database (Spotify API, Echo Nest, or proprietary analysis)"],"input_types":["structured track object (title, artist, ISRC, audio features)"],"output_types":["ranked playlist array with per-track similarity scores","playlist metadata (average BPM, dominant genre, mood tags)","track cards with artist, album, preview links"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_songs-like-x__cap_3","uri":"capability://data.processing.analysis.audio.feature.extraction.and.comparison","name":"audio feature extraction and comparison","description":"Analyzes acoustic properties of the input track (tempo, key, energy, danceability, acousticness, instrumentalness, valence) and compares them against candidate recommendations to compute similarity metrics. The system likely leverages a third-party audio analysis API (Spotify's audio features endpoint, Echo Nest, or Essentia) rather than performing raw audio processing, then normalizes feature vectors for comparison using cosine similarity or Euclidean distance. Results inform the ranking algorithm and may be exposed to users as 'why this song' explanations.","intents":["I want to find songs with the same energy and tempo as my favorite track for workout playlists","I need to understand the acoustic characteristics of a song to find similar-sounding alternatives","I want to filter recommendations by specific audio properties (e.g., 'acoustic only' or 'high-energy dance tracks')"],"best_for":["fitness/workout playlist builders seeking consistent BPM and energy","music producers analyzing sonic characteristics of reference tracks","audio engineers studying frequency/timbre similarity across tracks"],"limitations":["Audio feature extraction is API-dependent — accuracy varies by provider (Spotify's features are proprietary and may not align with perceptual similarity)","No real-time audio analysis — relies on pre-computed features from music database, limiting coverage of very recent or independent releases","Feature normalization may lose nuance — treating all 'energy' values equally regardless of genre context (e.g., high-energy classical vs. high-energy EDM)","No user-facing filtering by audio features — recommendations cannot be refined by BPM range, key, or acousticness threshold","Cosine similarity in audio feature space may not correlate with human perception of 'similar-sounding' tracks"],"requires":["Access to audio feature API (Spotify, Echo Nest, or proprietary analysis service)","Pre-computed audio features for all tracks in recommendation database"],"input_types":["structured audio feature vector (tempo, key, energy, danceability, etc.)","raw audio file (if performing local analysis, unlikely given architecture)"],"output_types":["normalized audio feature vectors","similarity scores per audio dimension","aggregate audio similarity metric (0-1 scale)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_songs-like-x__cap_4","uri":"capability://tool.use.integration.stateless.recommendation.api.with.no.user.persistence","name":"stateless recommendation api with no user persistence","description":"Operates as a stateless web service where each recommendation request is independent and isolated — no user accounts, session storage, or listening history tracking. The system accepts a single track identifier (song title + artist, or Spotify URI) and returns a playlist without maintaining any state between requests. This architecture eliminates authentication overhead and database persistence costs but prevents personalization based on user preferences or history.","intents":["I want instant song recommendations without creating an account or logging in","I need to share a recommendation link with friends without requiring them to sign up","I want to use this tool anonymously without tracking or data collection concerns"],"best_for":["casual music listeners seeking zero-friction discovery","privacy-conscious users avoiding account creation","developers integrating song recommendations into third-party apps via API"],"limitations":["No personalization — each user receives identical recommendations for the same input track, regardless of their taste profile","No recommendation history — users cannot revisit or refine previous searches without re-entering the song","No saved playlists — recommendations are ephemeral and must be manually copied to streaming services","No user feedback loop — system cannot learn from user acceptance/rejection of recommendations","Stateless design prevents A/B testing or progressive refinement of recommendation quality per user cohort"],"requires":["Web browser or HTTP client","No authentication or API key required"],"input_types":["HTTP GET/POST request with song title + artist name (or Spotify track URI)"],"output_types":["JSON playlist array or HTML page with track cards","HTTP response with CORS headers for cross-origin requests"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Web browser with JavaScript enabled","Song title and artist name (or ability to search/identify track in underlying music database)","No authentication or API keys required for free tier","Text input capability (keyboard or voice-to-text)","Successful track identification from prior search step","Access to audio feature database (Spotify API, Echo Nest, or proprietary analysis)","Access to audio feature API (Spotify, Echo Nest, or proprietary analysis service)","Pre-computed audio features for all tracks in recommendation database","Web browser or HTTP client","No authentication or API key required"],"failure_modes":["No collaborative filtering across user listening history — treats each query in isolation, limiting personalization depth","Lacks real-time streaming service integration, requiring manual song addition to playlists post-discovery","Recommendation model likely trained on smaller dataset than Spotify/Apple Music, reducing accuracy for obscure or very recent tracks","No contextual filtering by mood, era, or subgenre — returns similarity matches without semantic refinement","Single-song input constraint prevents multi-track context (e.g., 'songs like X but with Y's energy')","Fuzzy matching may return false positives for common song titles (e.g., 'Love Song' by multiple artists)","Limited to songs in underlying database — very recent releases or independent/underground tracks may not be indexed","No filtering by region, language, or release format (vinyl vs. digital) — returns global results only","Search latency depends on database size and query complexity; no caching of popular searches","Similarity scoring is opaque to end users — no explainability for why Track A ranks higher than Track B","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":"2026-05-24T12:16:33.096Z","last_scraped_at":"2026-04-05T13:23:42.559Z","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=songs-like-x","compare_url":"https://unfragile.ai/compare?artifact=songs-like-x"}},"signature":"t000aLu1Q82UiCaW1G7o5F3b35xJ4pFDk2eu1OUrkIudTfSshdFGdU5hhldOZhwxSNAUkJBCXTO7qRTB83W9AQ==","signedAt":"2026-06-21T01:35:34.357Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/songs-like-x","artifact":"https://unfragile.ai/songs-like-x","verify":"https://unfragile.ai/api/v1/verify?slug=songs-like-x","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"}}