NODEDC_1C/AGENTS.md

encoding_rule

• All source/code/config/docs files must be saved and edited in UTF-8 without BOM; never write mojibake placeholders or replacement characters.

commit_message_rule

• After applying fixes, always provide the user with a ready commit title in Russian.

graphify

This project has a graphify knowledge graph at graphify-out/.

Rules:

• Before answering architecture or codebase questions, read graphify-out/GRAPH_REPORT.md for god nodes and community structure
• If graphify-out/wiki/index.md exists, navigate it instead of reading raw files
• After modifying code files in this session, run python -c "from graphify.watch import _rebuild_code; from pathlib import Path; _rebuild_code(Path('.'))" to keep the graph current

codex_domain_loop

• Project-scoped Codex orchestration lives under .codex/.
• Use .codex/skills/domain-case-loop for repeatable domain hardening loops on one concrete case.
• Prefer docs/orchestration/active_domain_contract.json as the single mutable source of truth for the current domain/scenario pack; keep the agent canon stable and swap only this file when the active domain changes.
• The same skill/launcher also supports multi-step domain scenarios with shared assistant session state under artifacts/domain_runs/<scenario_id>/steps/.
• For full domain question pools, use pack mode and aggregate artifacts under artifacts/domain_runs/<pack_id>/scenarios/.
• Preserve current architecture: domain loop may automate capture, review, rerun, and artifact storage, but must not rewrite runtime foundations.
• Prefer machine-readable case artifacts in artifacts/domain_runs/<case_id>/, especially baseline_turn.json / rerun_turn.json, over ad hoc prose-only summaries.
• For cascading user questions in one domain, prefer scenario artifacts (scenario_manifest.json, scenario_state.json, per-step turn.json) over separate unlinked case folders.
• For follow-up-heavy domains, treat acceptance as scenario-tree coverage: root node, critical child nodes, critical edges, and the primary user path must be validated explicitly.
• Do not accept a domain when only the root snapshot works but selected-object or drilldown follow-up edges still fail.
• For critical branches, validate at least canonical wording, colloquial wording, and UI-generated selected-object wording when that UX exists.
• Treat temporal carryover, selected-object carryover, answer-shape match, and ordering semantics as first-class acceptance invariants rather than optional polish.
• Treat direct-answer-first behavior, business usefulness, selected-object memory, and field truthfulness as first-class analyst criteria rather than optional presentation polish.
• Treat stable focus_object, reusable bundles such as provenance_bundle, and pronoun-style follow-up resolution (по ней, по этой позиции) as first-class analyst criteria in follow-up-heavy domains.
• Treat action-first selected-object follow-ups, layered answer shape, stable answer_object, and temporal honesty about out-of-window evidence as first-class analyst criteria rather than optional polish.
• If a case falls outside the current routed contour because the route/intent/capability is not wired yet, treat it as domain enablement work for this project, not as automatic out-of-scope rejection.
• For new unmarked domains, needs_exact_capability means "bootstrap or extend the contour" rather than "close the case as unsupported".
• A case can be marked accepted only when analyst verdict is at least 80/100, no unresolved P0 remains, and the rerun does not mask heuristic output as confirmed.

agent_semantic_runs

• АГЕНТНЫЙ ПРОГОН is a targeted full semantic replay for the current architecture fix, not a generic smoke test.
• Use it to validate human user questions, human model answers, technical chats, business logic, and system routing together.
• Build question lists around the active fix: mix direct domain questions with contextual chains, meta interruptions, cross-domain pivots, and follow-up edges that specifically hit the architecture change under validation.
• Save agent-built question packs into autoruns under Пользовательские сессии with title prefix AGENT | ....
• Preferred repo-native save path: python scripts/save_agent_semantic_run.py --spec <truth_harness_or_question_spec.json>.
• Agent semantic runs must remain runnable by the user from the autoruns UI like any other saved user session.
• Do not run or save an АГЕНТНЫЙ ПРОГОН on every turn by default.
• Run it when the user explicitly asks for it, or when a substantial architecture/domain fix needs critical semantic proof beyond unit tests and narrow synthetic checks.