{"id":"3cdb1a3c-62fd-4bfb-bbe5-5ba96950fb59","slug":"clawhub-psyb0t-predictalot","name":"predictalot","description":"Self-hosted forecasting/prediction service. Foundation time-series endpoints under /v1/timeseries/<type>/{forecast,forecast/ensemble} + GET .../models — univariate, past/future/both covariates, multivariate, samples — over 5 zero-shot models (chronos-2, timesfm-2.5, moirai-2, toto-1, sundial-base-128m). Plus supervised tabular ML under /v1/tabular/ (9 backends — lightgbm, xgboost, hist-gbt, random-forest, logistic, mlp, svm-rbf, knn, naive-bayes — over direction/value/quantile modes) with train+persist, weighted ensembles, and calibrated/stacking/diversified meta-learners. Unified REST + MCP (streamable-HTTP at /mcp, one tool per (type, model) cell + per-type ensemble + listing) + optional bearer auth. Use when the user wants to forecast a numeric time series (quantile bands or raw sample paths), condition a forecast on known/future covariates, ensemble several forecasters, or train a tabular model on engineered features and predict direction/value/quantiles on the latest snapshot.","canonicalUrl":"https://www.xpersona.co/agent/clawhub-psyb0t-predictalot","sourceUrl":"https://clawhub.ai/psyb0t/predictalot","homepage":"https://clawhub.ai/psyb0t/skills/predictalot","source":"CLAWHUB","vendor":{"slug":"clawhub","label":"Clawhub","url":"https://clawhub.ai/psyb0t/skills/predictalot"},"protocols":["OPENCLEW"],"capabilities":[],"trustScore":null,"trustConfidence":"unknown","artifactCount":0,"benchmarkCount":0,"lastRelease":"1.2.2","freshnessAt":"2026-10-10T23:45:17.774Z","freshnessLabel":"Oct 10, 2026","securityReviewed":true,"openapiReady":false,"stats":[{"label":"Trust score","value":"Unknown"},{"label":"Compatibility","value":"OpenClaw"},{"label":"Freshness","value":"Oct 10, 2026"},{"label":"Vendor","value":"Clawhub"},{"label":"Artifacts","value":"0"},{"label":"Benchmarks","value":"0"},{"label":"Last release","value":"1.2.2"}],"factsPreview":[{"factKey":"vendor","category":"vendor","label":"Vendor","value":"Clawhub","href":"https://clawhub.ai/psyb0t/skills/predictalot","sourceUrl":"https://clawhub.ai/psyb0t/skills/predictalot","sourceType":"profile","confidence":"medium","observedAt":"2026-10-10T23:45:17.789Z","isPublic":true},{"factKey":"protocols","category":"compatibility","label":"Protocol compatibility","value":"OpenClaw","href":"https://www.xpersona.co/api/v1/agents/clawhub-psyb0t-predictalot/contract","sourceUrl":"https://www.xpersona.co/api/v1/agents/clawhub-psyb0t-predictalot/contract","sourceType":"contract","confidence":"medium","observedAt":"2026-10-10T23:45:17.789Z","isPublic":true},{"factKey":"traction","category":"adoption","label":"Adoption signal","value":"1.2K downloads","href":"https://clawhub.ai/psyb0t/predictalot","sourceUrl":"https://clawhub.ai/psyb0t/predictalot","sourceType":"profile","confidence":"medium","observedAt":"2026-10-10T23:45:17.789Z","isPublic":true},{"factKey":"latest_release","category":"release","label":"Latest release","value":"1.2.2","href":"https://clawhub.ai/psyb0t/predictalot","sourceUrl":"https://clawhub.ai/psyb0t/predictalot","sourceType":"release","confidence":"medium","observedAt":"2026-10-10T15:00:46.805Z","isPublic":true},{"factKey":"handshake_status","category":"security","label":"Handshake status","value":"UNKNOWN","href":"https://www.xpersona.co/api/v1/agents/clawhub-psyb0t-predictalot/trust","sourceUrl":"https://www.xpersona.co/api/v1/agents/clawhub-psyb0t-predictalot/trust","sourceType":"trust","confidence":"medium","observedAt":null,"isPublic":true}],"highlights":["1.2K downloads","Trust evidence available"],"agentCard":{"name":"predictalot","description":"Self-hosted forecasting/prediction service. Foundation time-series endpoints under /v1/timeseries/<type>/{forecast,forecast/ensemble} + GET .../models — univariate, past/future/both covariates, multivariate, samples — over 5 zero-shot models (chronos-2, timesfm-2.5, moirai-2, toto-1, sundial-base-128m). Plus supervised tabular ML under /v1/tabular/ (9 backends — lightgbm, xgboost, hist-gbt, random-forest, logistic, mlp, svm-rbf, knn, naive-bayes — over direction/value/quantile modes) with train+persist, weighted ensembles, and calibrated/stacking/diversified meta-learners. Unified REST + MCP (streamable-HTTP at /mcp, one tool per (type, model) cell + per-type ensemble + listing) + optional bearer auth. Use when the user wants to forecast a numeric time series (quantile bands or raw sample paths), condition a forecast on known/future covariates, ensemble several forecasters, or train a tabular model on engineered features and predict direction/value/quantiles on the latest snapshot.","source":"CLAWHUB","sourceId":"clawhub:s17fq93tmpky791n7516jcn08n83sfn2:predictalot","homepage":"https://clawhub.ai/psyb0t/skills/predictalot","repository":"https://clawhub.ai/psyb0t/predictalot","documentation":"https://www.xpersona.co/agent/clawhub-psyb0t-predictalot","protocols":["OPENCLEW"],"examples":[{"kind":"example","language":"bash","snippet":"export PREDICTALOT_URL=http://localhost:8080"},{"kind":"example","language":"bash","snippet":"export PREDICTALOT_AUTH_TOKEN=<your-token>\n# every /v1/* and /mcp request below needs: -H \"Authorization: Bearer $PREDICTALOT_AUTH_TOKEN\""}]}}