{"results":[{"id":"beliefs-cli-vs-reasons-cli","text":"Two CLIs at different levels: beliefs CLI is a structured markdown KB with provenance and manual maintenance (simple, flat). reasons CLI (ftl-reasons) is a full TMS with automatic propagation, cascades, backtracking, and LLM-driven operations (powerful, dependency-aware). Use beliefs for independent facts, reasons for justified conclusions with dependency chains","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"ftl-reasons-implementation","text":"ftl-reasons implements: SL justifications with antecedents and outlists, BFS propagation cascades with restoration, entrenchment-scored dependency-directed backtracking, challenge/defend dialectical argumentation (challenge→OUT, defend neutralizes, multi-level chains), LLM-driven derive, review-beliefs, and contradiction detection. SQLite-backed, Python CLI.","truth_value":"IN","justification_count":0,"dependent_count":2,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"ftl-reasons-install","text":"ftl-reasons installs via pip or uv. Three options: (1) pip install ftl-reasons, (2) uv tool install ftl-reasons, (3) uvx ftl-reasons <command> to run without installing. Requires Python. Initialize a new database with: reasons init","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"ftl-reasons-is-tms","text":"ftl-reasons implements actual Doyle-style TMS architecture: SL justifications with antecedents and outlists, BFS propagation cascades with restoration, entrenchment-scored dependency-directed backtracking. LLMs fill the problem-solver role Doyle left open","truth_value":"IN","justification_count":2,"dependent_count":6,"challenges":[],"last_reviewed":"2026-05-30T07:02:40","review_result":"pass","source_type":""},{"id":"ftl-reasons-quick-start","text":"Quick start: (1) pip install ftl-reasons, (2) reasons init, (3) reasons add my-belief 'Text of the belief' --source 'where I learned this', (4) reasons add derived-belief 'Conclusion' --sl my-belief to create a justified derivation, (5) reasons retract my-belief to see cascades propagate, (6) reasons assert my-belief to see restoration, (7) reasons explain derived-belief to trace the justification chain.","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":"2026-05-30T07:02:40","review_result":"invalid","source_type":""},{"id":"ftl-reasons-repo","text":"ftl-reasons source code and issue tracker: https://github.com/benthomasson/ftl-reasons — open source, 211 tests covering propagation, cascades, restoration, nogoods, backtracking, challenge/defend, import/export, staleness detection. Issues and feature requests go here.","truth_value":"IN","justification_count":0,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"http-endpoint-access","text":"EEM is accessible via a single HTTP GET at https://expert.ftl2.com/public/eem-expert/beliefs — no Python library, no CLI installation, no database copy, no setup. Three formats available: HTML (human-browsable), Markdown (agent-readable), JSON (machine-readable). Any agent that can fetch a URL can consume justified beliefs immediately.","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"hybrid-tms","text":"ftl-reasons is a hybrid TMS: symbolic TMS handles structure (justifications, propagation, cascades, backtracking, challenge/defend) while LLMs handle semantic operations (derive generates beliefs, review-beliefs critiques them, contradiction detection finds nogoods)","truth_value":"IN","justification_count":1,"dependent_count":5,"challenges":[],"last_reviewed":"2026-05-29T17:30:21","review_result":"pass","source_type":""},{"id":"import-agent-implementation","text":"import-agent command imports another agent's beliefs with SL justifications including agent:active as antecedent. Node is IN iff agent is active AND original belief is justified. Implemented in ftl-reasons CLI.","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"no-code-adoption","text":"Three levels of EEM integration: (1) HTTP GET — just a URL, read beliefs as context, no installation. (2) CLI (ftl-reasons) — search, show, explain, pip install. (3) Full pipeline (expert-build) — build, derive, review, maintain. The HTTP level is the on-ramp: try EEM in 30 seconds, see if it helps, no commitment.","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"staleness-implementation","text":"check-stale implementation: each belief records a source path and SHA-256 hash at creation time. check-stale compares stored hashes against current file content and flags any IN belief whose source has changed. Implemented in ftl-reasons CLI.","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""},{"id":"structure-not-truth-applies-to-site","text":"The expert.ftl2.com belief explorer demonstrates that TMS mechanics work (justification chains, IN/OUT propagation, retraction cascades) but does not prove the underlying claims are correct. A belief can be IN and fully justified within the system while being wrong, because all antecedents trace back to the same author's observations. Structure proves the tooling; external evidence proves the claims.","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null,"source_type":""}],"count":12,"limit":20,"offset":0}