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CLI plan correct never passes decision tree to CorrectionService, producing single-node impact analysis #606

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opened 2026-03-05 13:37:29 +00:00 by hurui200320 · 4 comments
hurui200320 commented 2026-03-05 13:37:29 +00:00
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  • Commit Message: fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler
  • Branch: fix/plan-correct-tree-wiring

Parent

Epic: #401 (E2E Integration Testing — bug discovered during #494 review)

Background and Context

During code review of PR #559 (#494 — M3 acceptance gate E2E verification), reviewer @CoreRasurae identified that the plan correct CLI handler in src/cleveragents/cli/commands/plan.py creates a bare CorrectionService() and calls analyze_impact() and execute_correction() without passing the decision_tree or influence_edges arguments.

Both parameters default to None, which causes CorrectionService._compute_affected_subtree() to perform BFS on an empty adjacency dict — returning only the single target decision, never its descendants or influence-DAG dependents.

Current Behavior

The CLI handler at plan.py:2409-2468:

svc = CorrectionService()

request = svc.request_correction(
    plan_id=resolved_plan_id,
    target_decision_id=decision_id,
    mode=correction_mode,
    guidance=guidance,
    dry_run=dry_run,
)

# Dry-run path (line 2422):
impact = svc.analyze_impact(request.correction_id)  # No tree, no edges

# Live execution path (line 2468):
result = svc.execute_correction(request.correction_id)  # No tree, no edges

CorrectionService.analyze_impact() defaults decision_tree=None → {} at line 145. _compute_affected_subtree() BFS on {} returns only [target_decision_id].

Consequence: In production, agents plan correct --dry-run always reports only 1 affected decision (the target), ignoring all descendants. agents plan correct --mode=revert only reverts the single target, never cascading to the subtree. This directly violates the spec's correction behavior.

Expected Behavior

The CLI handler should resolve the decision tree and influence edges from the DecisionService and pass them to CorrectionService:

  • analyze_impact(correction_id, decision_tree=structural_tree, influence_edges=influence_edges) should report the full affected subtree.
  • execute_correction(correction_id, decision_tree=structural_tree, influence_edges=influence_edges) should revert/append the full affected subtree.

The infrastructure already exists:

  • DecisionService.get_influence_edges(plan_id) returns dict[str, list[str]] — its docstring explicitly states: "This is the format expected by CorrectionService._compute_affected_subtree()."
  • DecisionService.list_decisions(plan_id) returns all decisions, from which the structural tree adjacency list can be built.
  • Every other command in plan.py resolves DecisionService via get_container().resolve(DecisionService).

Acceptance Criteria

  • correct_decision() in plan.py resolves DecisionService via the DI container
  • The structural tree (dict[str, list[str]]) is built from DecisionService.list_decisions(plan_id)
  • The influence edges are obtained from DecisionService.get_influence_edges(plan_id)
  • svc.analyze_impact() receives both decision_tree and influence_edges
  • svc.execute_correction() receives both decision_tree and influence_edges
  • The dry-run path reports the full affected subtree (target + all descendants)
  • The live execution path reverts/appends the full affected subtree
  • Existing tests in m3_e2e_verification.robot continue to pass (mock assertions updated if needed)

Supporting Information

  • Spec reference: docs/specification.md lines 14788-14802 (CLI signature), lines 28282-28478 (correction modes)
  • Discovered in: PR #559 review by @CoreRasurae (finding H1 in third review cycle)
  • Related: #494 (M3 acceptance gate — the E2E test mock assertions at helper_m3_e2e_verification.py:588 confirm the CLI passes only 1 arg)

Subtasks

  • Add get_structural_tree(plan_id) -> dict[str, list[str]] convenience method to DecisionService (optional — can also build inline)
  • Update correct_decision() in plan.py to resolve DecisionService via container and build/fetch tree + edges
  • Pass decision_tree and influence_edges to svc.analyze_impact() and svc.execute_correction()
  • Tests (Robot): Update or add integration test verifying CLI correction reports full subtree
  • Verify coverage >=97% via nox -s coverage_report
  • Run nox (all default sessions), fix any errors

Definition of Done

This issue is complete when:

  • All subtasks above are completed and checked off.
  • A Git commit is created where the first line of the commit message matches the Commit Message in Metadata exactly, followed by a blank line, then additional lines providing relevant details about the implementation.
  • The commit is pushed to the remote on the branch matching the Branch in Metadata exactly.
  • The commit is submitted as a pull request to master, reviewed, and merged before this issue is marked done.
## Metadata - **Commit Message**: `fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler` - **Branch**: `fix/plan-correct-tree-wiring` ## Parent Epic: #401 (E2E Integration Testing — bug discovered during #494 review) ## Background and Context During code review of PR #559 (#494 — M3 acceptance gate E2E verification), reviewer @CoreRasurae identified that the `plan correct` CLI handler in `src/cleveragents/cli/commands/plan.py` creates a bare `CorrectionService()` and calls `analyze_impact()` and `execute_correction()` without passing the `decision_tree` or `influence_edges` arguments. Both parameters default to `None`, which causes `CorrectionService._compute_affected_subtree()` to perform BFS on an empty adjacency dict — returning only the single target decision, never its descendants or influence-DAG dependents. ## Current Behavior The CLI handler at `plan.py:2409-2468`: ```python svc = CorrectionService() request = svc.request_correction( plan_id=resolved_plan_id, target_decision_id=decision_id, mode=correction_mode, guidance=guidance, dry_run=dry_run, ) # Dry-run path (line 2422): impact = svc.analyze_impact(request.correction_id) # No tree, no edges # Live execution path (line 2468): result = svc.execute_correction(request.correction_id) # No tree, no edges ``` `CorrectionService.analyze_impact()` defaults `decision_tree=None` → `{}` at line 145. `_compute_affected_subtree()` BFS on `{}` returns only `[target_decision_id]`. **Consequence:** In production, `agents plan correct --dry-run` always reports only 1 affected decision (the target), ignoring all descendants. `agents plan correct --mode=revert` only reverts the single target, never cascading to the subtree. This directly violates the spec's correction behavior. ## Expected Behavior The CLI handler should resolve the decision tree and influence edges from the `DecisionService` and pass them to `CorrectionService`: - `analyze_impact(correction_id, decision_tree=structural_tree, influence_edges=influence_edges)` should report the full affected subtree. - `execute_correction(correction_id, decision_tree=structural_tree, influence_edges=influence_edges)` should revert/append the full affected subtree. The infrastructure already exists: - `DecisionService.get_influence_edges(plan_id)` returns `dict[str, list[str]]` — its docstring explicitly states: *"This is the format expected by `CorrectionService._compute_affected_subtree()`."* - `DecisionService.list_decisions(plan_id)` returns all decisions, from which the structural tree adjacency list can be built. - Every other command in `plan.py` resolves `DecisionService` via `get_container().resolve(DecisionService)`. ## Acceptance Criteria - [x] `correct_decision()` in `plan.py` resolves `DecisionService` via the DI container - [x] The structural tree (`dict[str, list[str]]`) is built from `DecisionService.list_decisions(plan_id)` - [x] The influence edges are obtained from `DecisionService.get_influence_edges(plan_id)` - [x] `svc.analyze_impact()` receives both `decision_tree` and `influence_edges` - [x] `svc.execute_correction()` receives both `decision_tree` and `influence_edges` - [x] The dry-run path reports the full affected subtree (target + all descendants) - [x] The live execution path reverts/appends the full affected subtree - [x] Existing tests in `m3_e2e_verification.robot` continue to pass (mock assertions updated if needed) ## Supporting Information - **Spec reference:** `docs/specification.md` lines 14788-14802 (CLI signature), lines 28282-28478 (correction modes) - **Discovered in:** PR #559 review by @CoreRasurae (finding H1 in third review cycle) - **Related:** #494 (M3 acceptance gate — the E2E test mock assertions at `helper_m3_e2e_verification.py:588` confirm the CLI passes only 1 arg) ## Subtasks - [x] Add `get_structural_tree(plan_id) -> dict[str, list[str]]` convenience method to `DecisionService` (optional — can also build inline) - [x] Update `correct_decision()` in `plan.py` to resolve `DecisionService` via container and build/fetch tree + edges - [x] Pass `decision_tree` and `influence_edges` to `svc.analyze_impact()` and `svc.execute_correction()` - [x] Tests (Robot): Update or add integration test verifying CLI correction reports full subtree - [x] Verify coverage >=97% via `nox -s coverage_report` - [x] Run `nox` (all default sessions), fix any errors ## Definition of Done This issue is complete when: - All subtasks above are completed and checked off. - A Git commit is created where the **first line** of the commit message matches the Commit Message in Metadata exactly, followed by a blank line, then additional lines providing relevant details about the implementation. - The commit is pushed to the remote on the branch matching the **Branch** in Metadata exactly. - The commit is submitted as a **pull request** to `master`, reviewed, and **merged** before this issue is marked done.
hurui200320 added this to the v3.3.0 milestone 2026-03-06 03:19:25 +00:00
freemo self-assigned this 2026-03-06 23:13:10 +00:00
freemo commented 2026-03-07 23:07:46 +00:00
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Triage — Day 27

Status: Confirmed bug. Labels corrected.

Actions Taken

  • Priority upgraded: Priority/High → Priority/Critical (all bugs get Critical per policy)
  • MoSCoW upgraded: MoSCoW/Should have → MoSCoW/Must have (all bugs are Must Have)
  • Created TDD counterpart: #636

Analysis

Well-documented issue with clear root cause identification by @hurui200320 and confirmed by @CoreRasurae during PR #559 review. The correct_decision() handler at plan.py:2409-2468 creates a bare CorrectionService() without passing decision_tree or influence_edges, causing single-node impact analysis instead of full subtree traversal.

The fix is straightforward — resolve DecisionService via DI container and pass the tree/edges. The infrastructure (get_influence_edges(), list_decisions()) already exists.

Dependencies

  • TDD tests (#636) should be written first per CONTRIBUTING.md Bug Fix Workflow
  • TDD infrastructure (#627, #628) blocks TDD test execution but not creation
  • This is blocking M4 acceptance — correction behavior violates the specification
## Triage — Day 27 **Status**: Confirmed bug. Labels corrected. ### Actions Taken - Priority upgraded: `Priority/High` → `Priority/Critical` (all bugs get Critical per policy) - MoSCoW upgraded: `MoSCoW/Should have` → `MoSCoW/Must have` (all bugs are Must Have) - Created TDD counterpart: #636 ### Analysis Well-documented issue with clear root cause identification by @hurui200320 and confirmed by @CoreRasurae during PR #559 review. The `correct_decision()` handler at `plan.py:2409-2468` creates a bare `CorrectionService()` without passing `decision_tree` or `influence_edges`, causing single-node impact analysis instead of full subtree traversal. The fix is straightforward — resolve `DecisionService` via DI container and pass the tree/edges. The infrastructure (`get_influence_edges()`, `list_decisions()`) already exists. ### Dependencies - TDD tests (#636) should be written first per CONTRIBUTING.md Bug Fix Workflow - TDD infrastructure (#627, #628) blocks TDD test execution but not creation - This is blocking M4 acceptance — correction behavior violates the specification
freemo commented 2026-03-08 00:27:23 +00:00
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Verification — Day 28

Status: Verified. Bug confirmed and root cause identified.

Root Cause

The correct_decision() handler in plan.py (line ~2409) creates a bare CorrectionService() without resolving DecisionService via the DI container. It never fetches the decision tree or influence edges, so both default to None → empty dicts. _compute_affected_subtree() BFS on empty data returns only the single target decision.

The fix infrastructure already exists:

  • DecisionService.list_decisions(plan_id) returns all decisions with parent_decision_id for building the structural tree
  • DecisionService.get_influence_edges(plan_id) returns the influence DAG in the exact format CorrectionService expects

Every other plan command correctly resolves DecisionService via get_container() — this handler is the only one that doesn't.

Actions Taken

  • Transitioned from State/Unverified → State/Verified
  • Issue already has proper CONTRIBUTING.md template

Fix Plan

  1. Resolve DecisionService via get_container() in correct_decision()
  2. Build structural tree adjacency list from list_decisions(plan_id)
  3. Fetch influence edges from get_influence_edges(plan_id)
  4. Pass both to analyze_impact() and execute_correction()
  5. Write Behave BDD + Robot + ASV tests
## Verification — Day 28 **Status**: Verified. Bug confirmed and root cause identified. ### Root Cause The `correct_decision()` handler in `plan.py` (line ~2409) creates a bare `CorrectionService()` without resolving `DecisionService` via the DI container. It never fetches the decision tree or influence edges, so both default to `None` → empty dicts. `_compute_affected_subtree()` BFS on empty data returns only the single target decision. The fix infrastructure already exists: - `DecisionService.list_decisions(plan_id)` returns all decisions with `parent_decision_id` for building the structural tree - `DecisionService.get_influence_edges(plan_id)` returns the influence DAG in the exact format `CorrectionService` expects Every other plan command correctly resolves `DecisionService` via `get_container()` — this handler is the only one that doesn't. ### Actions Taken - Transitioned from `State/Unverified` → `State/Verified` - Issue already has proper CONTRIBUTING.md template ### Fix Plan 1. Resolve `DecisionService` via `get_container()` in `correct_decision()` 2. Build structural tree adjacency list from `list_decisions(plan_id)` 3. Fetch influence edges from `get_influence_edges(plan_id)` 4. Pass both to `analyze_impact()` and `execute_correction()` 5. Write Behave BDD + Robot + ASV tests
freemo commented 2026-03-08 02:14:05 +00:00
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Implementation Complete — PR #639

Summary

Fixed the plan correct CLI handler to properly wire the decision tree and influence DAG edges through to CorrectionService, resolving the single-node impact analysis bug.

What Changed

Core fix in src/cleveragents/cli/commands/plan.py correct_decision():

  1. Resolved DecisionService via DI container — follows the same pattern used by plan explain, plan tree, and other plan commands (container = get_container(); decision_svc = container.resolve(DecisionService))

  2. Built structural tree adjacency list from decision_svc.list_decisions(resolved_plan_id):

    decision_tree: dict[str, list[str]] = {}
for d in decisions:
    if d.parent_decision_id is not None:
        decision_tree.setdefault(d.parent_decision_id, []).append(d.decision_id)

  3. Fetched influence DAG edges via decision_svc.get_influence_edges(resolved_plan_id)

  4. Passed both to CorrectionService calls:

    • svc.analyze_impact(correction_id, decision_tree=decision_tree, influence_edges=influence_edges)
    • svc.execute_correction(correction_id, decision_tree=decision_tree, influence_edges=influence_edges)

Test Coverage

Test Type File Scenarios/Cases Status
BDD (Behave) features/plan_correct_tree_wiring.feature 3 scenarios, 15 steps All pass
Integration (Robot) robot/plan_correct_tree_wiring.robot 3 test cases All pass
ASV Benchmark benchmarks/plan_correct_tree_wiring_bench.py 2 suites Added

Updated 4 existing step definition files to mock the DI container in their _invoke_correct() helpers, ensuring all existing correction tests continue to pass.

Quality Gates

  • nox -s lint — All checks passed
  • nox -s typecheck — 0 errors, 0 warnings, 0 informations (Pyright strict)
  • nox -s unit_tests — 9109 scenarios passed, 0 failed
  • nox -s integration_tests — New tests pass (3/3); 19 pre-existing failures unrelated
  • nox -s coverage_report — 97% coverage

Branch & Commit

  • Branch: fix/plan-correct-tree-wiring
  • Commit: ea8815e7 — fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler
## Implementation Complete — PR #639 ### Summary Fixed the `plan correct` CLI handler to properly wire the decision tree and influence DAG edges through to `CorrectionService`, resolving the single-node impact analysis bug. ### What Changed **Core fix** in `src/cleveragents/cli/commands/plan.py` `correct_decision()`: 1. **Resolved `DecisionService` via DI container** — follows the same pattern used by `plan explain`, `plan tree`, and other plan commands (`container = get_container(); decision_svc = container.resolve(DecisionService)`) 2. **Built structural tree adjacency list** from `decision_svc.list_decisions(resolved_plan_id)`: ```python decision_tree: dict[str, list[str]] = {} for d in decisions: if d.parent_decision_id is not None: decision_tree.setdefault(d.parent_decision_id, []).append(d.decision_id) ``` 3. **Fetched influence DAG edges** via `decision_svc.get_influence_edges(resolved_plan_id)` 4. **Passed both to CorrectionService** calls: - `svc.analyze_impact(correction_id, decision_tree=decision_tree, influence_edges=influence_edges)` - `svc.execute_correction(correction_id, decision_tree=decision_tree, influence_edges=influence_edges)` ### Test Coverage | Test Type | File | Scenarios/Cases | Status | |-----------|------|----------------|--------| | BDD (Behave) | `features/plan_correct_tree_wiring.feature` | 3 scenarios, 15 steps | All pass | | Integration (Robot) | `robot/plan_correct_tree_wiring.robot` | 3 test cases | All pass | | ASV Benchmark | `benchmarks/plan_correct_tree_wiring_bench.py` | 2 suites | Added | Updated 4 existing step definition files to mock the DI container in their `_invoke_correct()` helpers, ensuring all existing correction tests continue to pass. ### Quality Gates - `nox -s lint` — All checks passed - `nox -s typecheck` — 0 errors, 0 warnings, 0 informations (Pyright strict) - `nox -s unit_tests` — **9109 scenarios passed, 0 failed** - `nox -s integration_tests` — New tests pass (3/3); 19 pre-existing failures unrelated - `nox -s coverage_report` — **97% coverage** ### Branch & Commit - Branch: `fix/plan-correct-tree-wiring` - Commit: `ea8815e7` — `fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler`
freemo commented 2026-03-09 02:44:45 +00:00
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Day 29 Planning Review — Closing

PR #639 (fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler) was merged 2026-03-08. All acceptance criteria are marked complete. The fix resolves the root cause: correct_decision() now resolves DecisionService via get_container(), builds the structural tree adjacency list, and passes both decision_tree and influence_edges to CorrectionService.

TDD counterpart #636 was closed in this planning session (tests included in the fix PR via maintainer override).

Closing as fix is merged and verified.

**Day 29 Planning Review — Closing** PR #639 (`fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler`) was merged 2026-03-08. All acceptance criteria are marked complete. The fix resolves the root cause: `correct_decision()` now resolves `DecisionService` via `get_container()`, builds the structural tree adjacency list, and passes both `decision_tree` and `influence_edges` to `CorrectionService`. TDD counterpart #636 was closed in this planning session (tests included in the fix PR via maintainer override). Closing as fix is merged and verified.
freemo 2026-03-09 02:44:46 +00:00
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feature/m4-correction-flows
feature/m1-plan-execute-runtime
feature/m4-security-exceptions
feature/m4-definition-of-done
feature/m4-correction-model
feature/m1-apply-pipeline
feature/m5-automation-profiles
feature/m2-lsp-stubs
feature/m3-invariants
feature/m1-actor-runtime
feature/docs-v2-restore
feature/m6-perf-scale
feature/m6-validation-edge
feature/m3-session-cli
feature/m1-persistence-tests-robot
feature/m3-config-cli
feature/m1-cli-tests-robot
feature/m5-subplan-tests
feature/m6-review-playbook
feature/aditya-m3-actor-loader
feature/m3-skill-protocol
feature/m4-automation-legacy-cleanup
feature/m3-change-model
feature/m3-skill-git
feature/m3-skill-registry
feature/m4-security-eval
fix/robot-tests
feature/m3-actor-registry
feature/m3-tool-cli
feature/m4-automation-profiles-cli
feature/m2-resource-cli-extensions
feature/m3-actor-loader
feature/m3-tool-domain-robot
feature/m3-skill-domain-robot
feature/m3-skill-cli
feature/m1-resource-db-robot-tests
feature/m3-session-domain-robot
feature/m1-persistence-tests
feature/m1-cli-tests
ten-branches-backup
feature/m3-skill-schema
feature/m3-session-persistence
feature/automation-profiles-and-resource-dag
feature/m1-plan-repo
feature/m1-db-plan-phase-rebaseline
feat/B4-sandbox
feat/B2-cli-wiring
feat/B5-project-persistence
feat/B1-project-data-models
feat/b1-data-models
feat-repo-manager-and-sourcegraph-support
feat/actor-schema
fix/component-isolation-security-fix
feat/ontology-agent
fix/error-handling-security-fix
fix/concurrency-security-fix
fix/serialization-security-fix
fix/server-side-request-forgery-security-fix
fix/file-system-security
fix/template-injection-fix
fix/data-injection-fix
tests/unit-tests
latest/poetry-generator
poetry-generator
config/contract-metadata-extractor
docs/readme-yaml-syntax
config/memory-yaml
fix/double-response
brent-additions
intel_2_demo
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auto/needs-reevaluation
Controller deferred this PR; awaiting Phase 6+ scope-evaluator or operator re-enablement.

  
controller-managed
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auto/driver-down
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auto/invariant-violation
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auto/last-attempt-tier-1
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Train repeatedly lost master-tempo races. Driver excludes via merge_cycle until cooldown elapses; label persists as visible history.

  
auto/revert
Revert PR backing out an invariant violation. Fast-tracked through the merge driver.

  
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There are questions in the ticket that can not be completed until the project owner provides clarity.

  
Points
1
 1 man-hours worth of work for an expert with no learning curve.

  
Points
13
 13 man-hours worth of work for an expert with no learning curve.

  
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2
 2 man-hours worth of work for an expert with no learning curve.

  
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21
 21 man-hours worth of work for an expert with no learning curve.

  
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3
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Points
34
 34 man-hours worth of work for an expert with no learning curve.

  
Points
5
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Points
55
 55 man-hours worth of work for an expert with no learning curve.

  
Points
8
 8 man-hours worth of work for an expert with no learning curve.

  
Points
88
 88 man-hours worth of work for an expert with no learning curve.

  
Priority
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 Critical priority issue that blocks CI/CD pipeline and prevents PR merges

  
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State
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Type
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 Any edits or discussion about the AI automated coding system.

  
Type
Bug
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Type
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 Anytime a ticket represents a discussion about a subject and doesnt fall into one of the other categories.

  
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Documentation
 An error or improvement needed in the documentation.

  
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Epic
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Type
Feature
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Type
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Type
Refactor
 A code change that restructures existing code without changing its external behavior.

  
Type
Support
 Someone needs help using the project.

  
Type
Task
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Type
Testing
 Work exclusively focusing on fixing or expanding testing.

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auto/needs-reevaluation
controller-managed
auto/blocked-by-deps
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auto/claimed-implementer
auto/claimed-merge
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auto/driver-down
auto/invariant-violation
auto/last-attempt-tier-0
auto/last-attempt-tier-1
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Automation Tracking
auto/needs-conflict-resolution
auto/needs-implementer
auto/postmortem
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auto/restart-throttled
auto/revert
auto/sentinel
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Blocked
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$1000
Bounty
$10000
Bounty
$20
Bounty
$2000
Bounty
$250
Bounty
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Bounty
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Bounty
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Bounty
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MoSCoW
Could have
MoSCoW
Must have
MoSCoW
Should have
Needs Feedback
Points
1
Points
13
Points
2
Points
21
Points
3
Points
34
Points
5
Points
55
Points
8
Points
88
Priority
Backlog
Priority
CI Blocker
Priority
Critical
Priority
High
Priority
Low
Priority
Medium
Signed-off: Owner
Signed-off: Scrum Master
Signed-off: Tech Lead
Spike
State
Completed
State
Duplicate
State
In Progress
State
In Review
State
Paused
State
Unverified
State
Verified
State
Wont Do
Type
Automation
Type
Bug
Type
Discussion
Type
Documentation
Type
Epic
Type
Feature
Type
Legendary
Type
Refactor
Type
Support
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Task
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Testing
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v3.3.0
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freemo
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Blocks
#494 test(e2e): validate M3 acceptance criteria for v3.2.0 milestone closure
cleveragents/cleveragents-core
Depends on
#636 TDD: plan correct single-node impact analysis test
cleveragents/cleveragents-core
Reference
cleveragents/cleveragents-core#606
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