New brief_echo stage before the planner in role_pipeline: the model restates
the analyst brief as a structured artifact, and a deterministic gate
(checkBriefEcho, opt-in via brief_echo=true) diffs the restatement against the
original brief. On divergence — dropped requirements (Jaccard coverage < 0.34)
or hallucinated files — it emits BriefEchoMismatchEvent and fails the stage
retryably, so a misread brief never reaches plan generation.
The diff (BriefEchoDiff) is a pure function of two recorded artifacts, so it is
replay-safe and records no observation; the event fires only on mismatch, for
audit. Symbols are recorded but non-blocking in v1. Mirrors the groundBrief-
References gate. role_pipeline only; freestyle_planning wiring is a follow-up.
Runtime install (like research): copy brief_echo.json + brief_echo.md and the
[[artifacts]] block into ~/.config/correx.
Replace the inline "Q:"-prefixed-summary convention with a structured
`questions` array of {prompt, options?, multiSelect?, header?} objects that
rides in the analysis artifact (allowed by additionalProperties:true, skipped
by JsonSchemaValidator). The kernel parses it to drive the producer-exit
clarification loop; the TUI renders it as an interactive form.
The schema declared sources as an array of objects, which correx's flat
JsonSchema model can't represent (JsonSchemaProperty has no nested
properties). The strict config loader rejected it at startup, silently
disabling the source_dossier artifact kind. Flatten sources to an array
of strings (URL-prefixed per-source notes), update the gather prompt to
match, and add ResearchSchemaLoadTest to guard every shipped research
schema against the strict loader.
Makes the research feature runnable end-to-end, off by default.
- config: [tools.research] (enabled, searxng_url, max_results, max_fetch_bytes).
- registration: web_search/web_fetch are built into BOTH the default and per-workspace
tool registries when research.enabled, sharing one HTTP client threaded from Main
(none built on the static path). Egress stays harness-enforced: web_fetch is T2
(operator-approved) and the existing NetworkHostRule still applies.
- workflow: examples/workflows/research.toml — decompose → gather → report, with the
three artifact schemas and prompts. Fan-out (search per sub-question, fetch per source)
runs as repeated tool calls inside the gather stage (Correx has no parallel agents);
per-source synthesis into the dossier is the compression step, so the report stage
consumes summaries, never raw pages. ResearchWorkflowTest validates the graph contract.
To run: set [tools.research].enabled, register the 3 [[artifacts]], copy research.toml +
prompts + schemas into the workflows dir, start SearXNG. Launch like any workflow (the
T2 fetch approval surfaces as an approval card; the report opens in the artifact viewer).
Follow-ups (noted, not blocking): batch fetch-approval at the source-list level (§3),
a dedicated SourceFetched/LowQualityExtraction event (quality + content hash are already
in tool-result metadata), dynamic per-session egress allowlist, and the web approval client (§6).
The reviewer prompt told the model to judge "the analysis requirements," but
the reviewer stage only needed [patch, impl_plan] — it never actually received
the analysis artifact, so the acceptance criteria it was meant to check against
were never in its context. A reliability gate checking against criteria it
can't see is theater.
- reviewer now needs `analysis`, so the diff is judged against concrete,
pre-stated acceptance criteria (§5 narrow question) rather than whole files
against taste; the §3 minItems enforcement guarantees those criteria are
non-empty.
- reviewer.md operationalizes §5's two principles: evaluate the diff against
each requirement (findings must map to a requirement/plan-step/defect), and
don't re-report what deterministic tools already catch (compiler/detekt/tests
— trust verification, point at failures, don't re-derive them).
This is the workflow-level realization of §5. The full static-first
infrastructure (running static tools as a pipeline step and mechanically
excluding their findings from reviewer context) needs a static-findings event
representation and is deferred. §6 critic calibration needs runtime history
before it can say anything (spec ordering #5).
Local analysts hallucinate file paths the same as planners. A stage can now
opt in with `ground_references = true`: after it produces its brief, every
workspace-relative file path the brief named is checked for existence, and a
path that doesn't exist fails the stage (retryable) with the misses fed back
("Reference only files you have read") so the model re-grounds.
Grounding probes the filesystem directly rather than the repo map — the map
is recency-ranked and depth/extension-limited, not a complete existence
oracle, so "absent from the map" can't be a hard failure. Existence is a
nondeterministic observation, so the result is recorded as a
BriefGroundingCheckedEvent (invariant #9); replay reads it back and never
re-probes.
- BriefGroundingCheckedEvent + GroundingReference, registered in eventModule
- BriefReferenceExtractor: pure, deterministic pull of relative file-path
references from a brief artifact JSON (needs a '/' and a dotted extension;
skips modules, bare names, URLs, absolute/parent paths — so coarse
"subsystem" mentions the brief is allowed to make aren't false-flagged)
- SessionOrchestrator.groundBriefReferences on the post-verifyProduces path,
gated by stage metadata; uses the existing worldProbe
- TomlWorkflowLoader `ground_references` → metadata; role_pipeline analyst
opts in
Scoped to file references with a '/' + extension (not bare basenames, which
a depth-limited probe can't resolve), so a flagged miss is high-confidence.
The symbol-grounding half of §3 is left for a real symbol index.
Scope creep — an implementer writing files it never declared — is the
dominant local-model failure that compiler/tests don't catch. A stage can
now declare a `writes` manifest (workspace-relative globs); a FILE_WRITE
that resolves inside the workspace but outside the declared set is raised
as PATH_OUTSIDE_MANIFEST → BLOCK, so the model gets the violation as tool
feedback and retries within scope (the §2 bounded-retry signal).
Implemented as a plane-2 rule beside PathContainmentRule (same effect-based
dispatch on FILE_WRITE, same symlink-safe WorldProbe resolution, same
recorded observations so replay reads them back — invariant #9). An empty
manifest is unrestricted; out-of-workspace targets stay PathContainmentRule's
concern, so the two rules don't double-flag.
- StageConfig.writeManifest + TomlWorkflowLoader `writes` parsing
- ToolCallAssessmentInput.writeManifest, threaded from the active stage via
SessionOrchestrator.runPlane2Assessment
- new ManifestContainmentRule, registered in the server assessor
- shared candidatePathStrings extracted so both path rules judge the same
target set
- role_pipeline.toml documents the option on the implementer stage
The dedicated ManifestViolationEvent the spec names is not added: the
violation is already recorded replayably in ToolCallAssessedEvent (issue +
observations + BLOCK) and surfaced in the TUI rationale band. A first-class
event is worth adding only once reconciliation consumes it.
Live repro: architect emitted a verify stage with kind=analysis and a
verdict-equals edge. The kind schema doubles as the LLM response format,
so 'verdict' was never emitted and the workflow failed at its final hop
at runtime. The compiler now requires artifact_field_equals fields to be
declared by the producing stage's kind schema, failing the plan at lock
time with a pointer at review_report. Architect prompt rule added;
reachability check extracted alongside the new validation.
Live repro: the architect wired all three stages straight to 'done'
instead of chaining them, so phase 2 legitimately completed after
stage 1 of 3 — a silently truncated plan reported as success. The
compiler now walks the edge graph from start and fails compilation
when any declared stage is unreachable, surfacing the broken topology
as ExecutionPlanRejected at lock time instead. Architect prompt edge
rules rewritten to demand explicit chaining (the old wording was
garbled).
ExecutionPlanCompiler treated the plan's single 'produces' string as a
registry kind id, while the architect prompt described it as a unique
artifact id referenced by needs/edges — the model followed the prompt,
invented descriptive ids (files_created), and every freestyle plan
failed to compile. Collapsing both onto one string is also unsound:
two stages producing the same kind would collide on slot name and make
artifact_validated edge conditions ambiguous.
Plan stages now carry an optional 'kind' selecting the registered kind
(mirroring TOML's produces = { name, kind }); 'produces' stays the
unique slot name. Missing 'kind' falls back to the old produces-as-kind
reading so existing plans still compile. Vocabulary entry, architect
prompt, and execution_plan schemas updated to match.
qa_ping is a minimal single-stage file_write workflow used for live QA smoke
runs (writes 'pong' into the qa/ scratch repo). The qa/ workspace itself is a
nested git repo and stays untracked; the compiled tui-go binary is ignored.
Add docs/schemas/execution_plan.json (goal/stages/edges), the
architect_freestyle prompt that instructs emitting the execution pipeline as
JSON, and register the execution_plan llm-emitted kind in both
artifacts.config.toml and sample-config.toml. Validated via
ExecutionPlanSchemaValidationTest (minimal plan passes; missing stages rejected).
- LlamaCppInferenceProvider: check HTTP status and surface the real error body instead of masking it as a ChatCompletionResponse deserialization failure
- PromptRenderer: render the live conversation layer (L1) last so the user turn is the final message (fixes Qwen 'No user query found' 500 when L3 recall is present)
- TomlWorkflowLoader: resolve stage prompts relative to the workflow file's own dir (bundle), CWD-independent; config-dir fallback for globals
- SessionOrchestrator: hard-fail a stage whose declared prompt can't resolve (was a silent user-less request)
- move healthcheck prompts next to the example workflow (examples/workflows/prompts/)
kami