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Removed the "disabled" framing from docs/done/validator-test-script- narrative-output-issue.md (moved todo/ -> done/, root cause identified, structural fix landed, spot-check clean) -- the mechanism it described (_CANONICAL_DOC_CHAIN, e2e_pipeline._VALIDATOR_MANIFEST) no longer exists in production code, superseded by the 2026-08-08 self-planning rewrite and Org Graph unification Phase 2. Planner's and Validator's self-planning catalogs already carry test_script as a suggested (not required) option; _CODER_NODE_CATALOG was the one gap -- added a matching entry there (mechanical check_script_compiles judgment, same as Validator's). All three org agents now decide per-goal whether this node is worth planning, with no remaining "this node type is globally off" switch anywhere. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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New skills/work-graph-node-review/SKILL.md documents the methodology for judging a self-planned Work Graph node's output (real structured content vs. narrative prose standing in for it) -- distilled from the real narrative-output incident (docs/todo/validator-test-script-narrative- output-issue.md §6) and the conditional-not-assertive phrasing lesson already applied in _NARRATION_RETRY_HINT. Scoped explicitly against planner-output-review (Planner's fixed doc chain, task-level gate), qa-task-validation (overall task acceptance), and skill-defect-remediation (rewriting a Skill file itself) -- this one judges a single self-planned node's output, nothing broader. Wired into roles/planner_reviewer, roles/coder, roles/validator role.json skills lists. .claude/agents/*.md left untouched -- that's a deploy-time artifact compiled from role.json by agent_profile.deploy_agent_definitions(), not hand-synced (confirmed stale already: coder.md is missing an even earlier Phase 2a skill addition). This completes Phase 2c (§2.1/§2.2/§6/§7.1 all implemented; §7.2's analysis was completed earlier without needing a code change). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Implements org-graph-unification-phase2-universal-self-planning-design.md §4 + §5, the engine-extension sub-phase (Phase 2a) -- no org-flow callers changed yet, this is the underlying capability. - _run_one_node() now resolves subagent_type/skill_ref per-node (node.get with the run-level org_node/skill_id as fallback), threaded through _ensure_node_row/_make_run_fn/_resolve_node_verify_fn -- a node's own judgment.kind="llm" call runs under its own declared identity, not always the graph-level default. Found and fixed a real gap surfaced by writing this: run_graph() only ensures the run-level default skill_id exists as a placeholder skill (work_node_execution.skill_ref's FK target) -- a node declaring its own skill_ref needs the same guarantee or the first INSERT for that skill_id fails FOREIGN KEY constraint. - New on_fail.action="dynamic_loop_back": Reflection-review (_judge_root_cause_node) runs three real parallel perspectives (content/ connectivity/history) under the Validator identity, each picking a target_node_id from the failing node's real ancestors plus a defect_kind (content_error vs skill_defect), majority-voted by _tally_reflection (own small Counter-based implementation, not imported from root_cause_trace.py -- that module already imports this one). A runtime ancestor check in _run_one_node backs up _tally_reflection's own degradation guarantee. - skill_defect triggers Fix-Skill (_fix_skill_for_node) before the loop back fires: reads the target node's declared skill_ref, builds a rewrite prompt from what was asked/produced/why it failed/prior loop history, runs it under the Validator identity (user-confirmed via AskUserQuestion), then calls the existing but -- until now -- never actually invoked by any production path bug_record.create_bug_record() + skill_update.update_skill(), against skill_query._REPO_ROOT (never target_folder_path). Logs a real 'skill_iterated' execution_event (a CHECK-enum value that has existed since the original U-001 schema but was never written before). Rate-limited to _MAX_SKILL_FIXES_PER_RUN_PER_SKILL rewrites of the same Skill per run. - New total-attempts-per-source-node loop_limit guard alongside the existing per-(target,source) one -- dynamic_loop_back can pick a different target each round, which would otherwise dodge the per-pair cap indefinitely. New settings_config key shape "{org_node}:{source_node_id}:total", no interface change needed there. - New skills/skill-defect-remediation/SKILL.md (Validator-only), wired into roles/validator/role.json. python3 -m unittest discover -s src (741 tests) + discover -s supervisor -p "test_*.py" (126 tests) both green, zero regressions. Deferred to Phase 2b (per design doc's own sequencing note): §2.1/§2.2 (work_graph_run.org_node removal + ux_work_graph_run_active index narrowing) -- narrowing that index now, before the append-to-existing-run mechanism lands, would break the current production flow, since Planner's and Coder's work_graph_run rows both stay non-terminal indefinitely on the happy path today (only Validator's own graph ever reaches 'done'). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Inserts Planner -> planner_reviewer -> Coder -> Validator into the fixed Org Graph flow (was Planner -> Coder -> Validator), per docs/todo/org-graph-unification-phase1-review-gate-design.md. A new planner_reviewer role independently judges whether Planner's BRD/PRD/SDD/ Benchmark output is real structured content (not narrative prose) before Coder is allowed to start, with a 3-attempt retry loop and a narration heuristic informed by the real narrative-output incident (docs/todo/validator-test-script-narrative-output-issue.md). Also fixes, in the same code path: - The P0 bug in task-execution-resume-assumes-planner-artifacts-exist.md: resuming a task no longer assumes sdd/prd/benchmark artifacts exist -- falls through to real replanning when they don't. - A fresh-run KeyError (not resume-specific) when a self-planned graph omits the prd/benchmark node types. - agent_profile.migrated_from_profile was NOT NULL, which broke as soon as a role with no legacy Hermes profile (planner_reviewer) was recorded. org_node_lifecycle._REQUIRED_ARTIFACTS["coder"] is narrowed from (brd,prd,sdd,benchmark) to (sdd,) -- the old 4-artifact gate never actually blocked anything since artifact_write.py sets validation_status='passed' unconditionally; planner_reviewer is the first real semantic gate. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Per CLAUDE.md's docs/ role split (todo = pending, done = shipped into the SDD/code): all seven Graph Engineering series items with a real implementation (B, D, E, F, G, H -- A had no separate doc, resolved directly in graphlemon_architecture.md; C is explicitly won't-do) now have their requirements+design docs moved from docs/todo/ to docs/done/, git mv'd to preserve history. Every cross-reference to the 12 moved files -- across the other moved docs themselves, graph-engineering-open-items.md, 2 Skill files, and 9 src/*.py docstrings/comments -- updated from docs/todo/<file> to docs/done/<file>. Verified no stale docs/todo/ references to any of the 12 filenames remain anywhere in the repo. graph-engineering-open-items.md itself stays in docs/todo/ (not moved) -- it's a living index that keeps gaining new entries from later comparison-note/gap-analysis passes (H itself was added this way, and a new item already appeared while this cleanup was in progress), not a single finished conclusion. Its own header now reflects that all of A/B/D/E/F/G/H are done and explains why it wasn't moved. Also fixed two pre-existing stray path references (missing todo/done/ prefix entirely, predating this cleanup) in its G section. Full src suite (625 tests) passes -- this is a pure documentation/comment change, no behavior touched. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Implements docs/todo/validator-loop-until-dry-skill-design.md. Pure Skill + Agent-definition wiring, no execution-engine changes -- the convergence loop runs inside a single Work Node's one claude -p session (multi-turn tool use), not a graph_manifest-level cycle, so topological_layers()/ run_graph() are untouched. New Skill skills/unknown-scope-defect-sweep/SKILL.md: K=2 consecutive no-new-finding rounds to stop, 20-round hard cap, dedup key must be a structural identifier (file path + line, route path, package name) not a natural-language description (the same finding gets reworded call to call, so text-keyed dedup never converges), dedup set is "everything ever seen" not "everything confirmed" (the common bug the 14-step reference names: a rejected candidate reappearing as a false "new finding" every round). Each candidate is verified via qa-task-validation's existing PASS/FAIL/INCONCLUSIVE framework -- deliberately NOT root_cause_trace's three-perspective jury (F), since that answers a different question (root cause AFTER a failure) from this one (is this candidate real at all) -- documented in the design doc's own tradeoff note. Wired into agent_profile.py's FRONTMATTER["validator"]["skills"] and agents/validator/AGENTS.md's "必须加载" section with a concrete trigger signal (task description can't state an exact expected count/boundary up front). Only FR-4 (Skill wired into the rendered .claude/agents/validator.md) has deterministic, mockable behavior -- new test test_validator_references_unknown_scope_defect_sweep_skill. Acceptance criteria 1-3 (actually finds everything, actually dedups correctly, actually stops at the hard cap) need real multi-turn claude -p behavior, out of scope for mocked tests (RUN_REAL_AGENT_E2E=1 territory), same category of limitation as F's own real-concurrency-timing note. Full src suite (587 tests) passes with zero regressions. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Implements docs/todo/dynamic-work-graph-design-skill-design.md. G already answered FR-2 (how to mark a parallel-eligible node group): no new field needed -- topological_layers() infers independence purely from depends_on/edges, so the new Skill's job is just "express real dependencies honestly, don't add fake ones." New Skill skills/design-dynamic-work-graph/SKILL.md: the node-boundary / zero_token-vs-needs_judgment / per-node self-contained task_prompt methodology, wired into agent_profile.py's FRONTMATTER for coder and validator (Planner's own doc-chain path is untouched -- FR-4 only names Coder/Validator). work_graph_plan.py: new _GENERIC_PROMPT_TEMPLATE + generic_node_prompt_builder(), used whenever org_node != 'planner'. Planner keeps its existing fixed brd/prd/sdd/benchmark/... chain (_PROMPT_TEMPLATE) completely unchanged -- zero regression risk to the one real production planning path. Scoped per the requirements doc's non-goal #1 ("prove the mechanism works, don't cover every real scenario yet"): does NOT wire into e2e_pipeline.py::implement_code()'s existing single-node production path. New tests prove the mechanism itself: a Coder scenario that naturally splits into 3 independent modules produces a correctly-shaped graph_manifest, topological_layers() puts all three in one concurrent layer (ties E directly to G), and generic_node_prompt_builder drives it through run_graph() to completion. Full src suite (580 tests) passes with zero regressions. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> -
Real incident (2026-08-06): the skill-content migration task and the skill detail page bug fix were two separate tasks. Neither was asked to verify that migrated content is actually reachable through the DB-backed lookup the detail page uses. Both passed their own tests cleanly -- because both only ever exercised the mechanism against seeded/mocked fixture data, never checked whether the real producer's real output actually exists in the real system. The result: the skill detail page returned "not found" for all 12 real migrated skills, and nobody caught it until a human clicked through the real console. qa-task-validation (§8): passing unit tests against seeded fixtures proves the mechanism is correct given valid input -- it does not prove that input exists for real. When a feature reads data another task/process was supposed to have already written, Validator must independently query the real running system against a real (not newly-created) object. project-sdd-planning (§10): when a task's acceptance depends on another task's real output, the Benchmark must name a real, specific object as the acceptance anchor, not just describe the mechanism. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
