feat(acms): implement depth/breadth projection system and skeleton context propagation #544

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opened 2026-03-04 01:01:02 +00:00 by freemo · 1 comment

freemo commented 2026-03-04 01:01:02 +00:00

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• Commit Message: feat(acms): implement depth/breadth projection system
• Branch: feature/m5-depth-breadth-projection

Field	Value
Type	Feature
Priority	High
MoSCoW	Should Have
Points	8
Milestone	v3.4.0
Assignee	freemo
Parent Epic	#396 (Epic: ACMS Context Pipeline)
Depends On	#538 (ContextFragment model), #189 (UKO ontology scaffolding), #194 (skeleton compressor)

Background

This issue covers two related spec features:

Depth/Breadth Projection System (§ Core Concepts > Depth/Breadth Projection, lines 25265-25300)

The spec defines a formal projection system over the UKO graph:

• Breadth (0-N hops): how many relationship hops from the focal entity to include.
• Depth (integer or named level): how much detail to include per entity.
• DetailLevelMap: maps named depth levels to domain-specific semantics.
  • Code domain: MODULE_LISTING → CLASS_SIGNATURES → METHOD_BODIES → FULL_SOURCE
  • Docs domain: TABLE_OF_CONTENTS → SECTION_SUMMARIES → FULL_CONTENT
  • Database domain: TABLE_LISTING → SCHEMA_DETAILS → FULL_PROCEDURES

No implementation of the projection system or DetailLevelMap exists in the codebase.

Skeleton Context Propagation (§ Core Concepts > Hierarchical Plan Context, lines 25235-25263; § Architecture > ACMS, lines 43057-43110)

The SkeletonCompressor (#194) is implemented (226 lines), but the propagation workflow is missing: when a child plan is spawned, the parent's assembled context should be compressed into a skeleton and injected into the child's context budget. This involves:

1. Calling the pipeline's SkeletonCompressor during subplan spawn
2. Injecting the skeleton as inherited context with a configurable skeleton_ratio budget allocation
3. Child plans start with parent context skeleton + their own fresh context

Acceptance Criteria

1. DetailLevelMap enum/class defines named depth levels per domain (code, docs, database).
2. ProjectionSpec dataclass captures (breadth: int, depth: int | str, domain: str).
3. Projection logic retrieves UKO entities at the specified breadth/depth, returning ContextFragment results at the requested detail level.
4. When a subplan is spawned, the parent plan's assembled context is compressed via SkeletonCompressor and injected into the child's initial context budget.
5. skeleton_ratio config parameter controls what fraction of child's budget is reserved for inherited skeleton (default: 0.2 per spec).
6. Child plan's context assembly starts with the skeleton as pre-populated fragments.

Subtasks

1. Design

• Design DetailLevelMap and ProjectionSpec data models
• Design integration point between subplan spawn and skeleton injection
• Define skeleton_ratio config schema

2. Implementation

• Implement DetailLevelMap with domain-specific depth semantics
• Implement ProjectionSpec and projection logic
• Wire projection into strategy implementations (strategies use ProjectionSpec to control retrieval depth)
• Implement skeleton propagation in subplan spawn workflow
• Honor skeleton_ratio budget parameter

3. Testing

• Unit tests for DetailLevelMap resolution
• Unit tests for projection at various breadth/depth combinations
• Unit test: skeleton injection during subplan spawn
• Test skeleton_ratio budget allocation
• Integration test: parent plan → skeleton → child plan context

4. Documentation

• Docstrings for projection system
• Config documentation for skeleton_ratio

5. Integration

• Wire projection into ACMS pipeline strategies
• Wire skeleton propagation into SubplanActor (#198)

6. Observability

• Log skeleton compression ratio and injected token count
• Log projection parameters per strategy invocation

7. Security

• Skeleton propagation must not leak context across plan isolation boundaries beyond what the parent explicitly shares

Definition of Done

• All acceptance criteria met
• All subtask checkboxes checked
• Tests pass in CI
• Code reviewed and approved

## Metadata - **Commit Message**: `feat(acms): implement depth/breadth projection system` - **Branch**: `feature/m5-depth-breadth-projection` | Field | Value | |-------|-------| | **Type** | Feature | | **Priority** | High | | **MoSCoW** | Should Have | | **Points** | 8 | | **Milestone** | v3.4.0 | | **Assignee** | freemo | | **Parent Epic** | #396 (Epic: ACMS Context Pipeline) | | **Depends On** | #538 (ContextFragment model), #189 (UKO ontology scaffolding), #194 (skeleton compressor) | ## Background This issue covers two related spec features: ### Depth/Breadth Projection System (§ Core Concepts > Depth/Breadth Projection, lines 25265-25300) The spec defines a formal projection system over the UKO graph: - **Breadth** (0-N hops): how many relationship hops from the focal entity to include. - **Depth** (integer or named level): how much detail to include per entity. - **DetailLevelMap**: maps named depth levels to domain-specific semantics. - Code domain: `MODULE_LISTING` → `CLASS_SIGNATURES` → `METHOD_BODIES` → `FULL_SOURCE` - Docs domain: `TABLE_OF_CONTENTS` → `SECTION_SUMMARIES` → `FULL_CONTENT` - Database domain: `TABLE_LISTING` → `SCHEMA_DETAILS` → `FULL_PROCEDURES` No implementation of the projection system or `DetailLevelMap` exists in the codebase. ### Skeleton Context Propagation (§ Core Concepts > Hierarchical Plan Context, lines 25235-25263; § Architecture > ACMS, lines 43057-43110) The SkeletonCompressor (#194) is implemented (226 lines), but the **propagation workflow** is missing: when a child plan is spawned, the parent's assembled context should be compressed into a skeleton and injected into the child's context budget. This involves: 1. Calling the pipeline's SkeletonCompressor during subplan spawn 2. Injecting the skeleton as inherited context with a configurable `skeleton_ratio` budget allocation 3. Child plans start with parent context skeleton + their own fresh context ## Acceptance Criteria 1. `DetailLevelMap` enum/class defines named depth levels per domain (code, docs, database). 2. `ProjectionSpec` dataclass captures `(breadth: int, depth: int | str, domain: str)`. 3. Projection logic retrieves UKO entities at the specified breadth/depth, returning `ContextFragment` results at the requested detail level. 4. When a subplan is spawned, the parent plan's assembled context is compressed via SkeletonCompressor and injected into the child's initial context budget. 5. `skeleton_ratio` config parameter controls what fraction of child's budget is reserved for inherited skeleton (default: 0.2 per spec). 6. Child plan's context assembly starts with the skeleton as pre-populated fragments. ## Subtasks ### 1. Design - [ ] Design `DetailLevelMap` and `ProjectionSpec` data models - [ ] Design integration point between subplan spawn and skeleton injection - [ ] Define `skeleton_ratio` config schema ### 2. Implementation - [ ] Implement `DetailLevelMap` with domain-specific depth semantics - [ ] Implement `ProjectionSpec` and projection logic - [ ] Wire projection into strategy implementations (strategies use ProjectionSpec to control retrieval depth) - [ ] Implement skeleton propagation in subplan spawn workflow - [ ] Honor `skeleton_ratio` budget parameter ### 3. Testing - [ ] Unit tests for DetailLevelMap resolution - [ ] Unit tests for projection at various breadth/depth combinations - [ ] Unit test: skeleton injection during subplan spawn - [ ] Test skeleton_ratio budget allocation - [ ] Integration test: parent plan → skeleton → child plan context ### 4. Documentation - [ ] Docstrings for projection system - [ ] Config documentation for skeleton_ratio ### 5. Integration - [ ] Wire projection into ACMS pipeline strategies - [ ] Wire skeleton propagation into SubplanActor (#198) ### 6. Observability - [ ] Log skeleton compression ratio and injected token count - [ ] Log projection parameters per strategy invocation ### 7. Security - [ ] Skeleton propagation must not leak context across plan isolation boundaries beyond what the parent explicitly shares ## Definition of Done - [ ] All acceptance criteria met - [ ] All subtask checkboxes checked - [ ] Tests pass in CI - [ ] Code reviewed and approved

freemo added the

Points

8

Priority

High

State

In Progress

Type

Feature

labels 2026-03-04 01:01:15 +00:00

freemo added this to the v3.2.0 milestone 2026-03-04 01:01:15 +00:00

freemo modified the milestone from v3.2.0 to v3.4.0 2026-03-04 01:09:35 +00:00

freemo added

State

Verified

and removed

State

In Progress

labels 2026-03-04 01:09:37 +00:00

freemo self-assigned this 2026-03-04 01:41:12 +00:00

freemo added a new dependency 2026-03-05 00:34:01 +00:00

#396 Epic: ACMS Context Pipeline

freemo referenced this issue from a commit 2026-03-05 11:34:44 +00:00

feat(acms): implement depth/breadth projection system

freemo referenced this issue 2026-03-05 11:35:00 +00:00

feat(acms): implement depth/breadth projection system #603

freemo added

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labels 2026-03-05 11:35:18 +00:00

freemo commented 2026-03-05 11:35:52 +00:00

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Implementation Notes

PR: #603
Branch: feature/m5-depth-breadth-projection
Commit: 6a4529ea — feat(acms): implement depth/breadth projection system

Source: src/cleveragents/application/services/depth_breadth_projection.py (530 lines)

Seven components implemented per spec §25265-25340 and §43057-43128:

1. ProjectionSpec — Frozen Pydantic model capturing a projection request. Fields: focus (tuple of URIs, min 1), breadth (int ≥ 0, default 2), depth (int or named string, default 3), depth_gradient (bool, default True), domain (str, default "uko-code:"). Validates non-negative depth.

2. ProjectedNode — Frozen Pydantic model for a materialized UKO node with uri, distance from focus, resolved_depth after gradient, and label.

3. DepthBreadthProjector — Stateless BFS projector. Maintains a registry of DetailLevelMap instances per domain. project() does BFS from focus URIs over an adjacency list, computing resolved_depth = base - floor(base * distance / breadth) for each node. project_to_fragments() converts to ContextFragment with relevance inversely proportional to distance. Handles multiple focus items.

4. PlanContextInheritance — Service implementing compute_child_context(). Computes child detail = parent avg + delta * max_detail_increase (capped at 9), child breadth = max(1, parent - delta), skeleton budget = child_budget * skeleton_ratio. Injects skeleton via duck-typed compressor. Returns ChildContextResult.

5. ChildContextResult — Frozen model with request: ContextRequest, skeleton_fragments: tuple[ContextFragment, ...], parent_context_hash, skeleton_budget, depth_delta. Separates the request from skeleton data since ContextRequest has no metadata field.

6. InheritanceConfig — Frozen config: skeleton_ratio=0.2, min_skeleton_tokens=32, max_detail_increase=3.

7. Built-in presets: code_detail_map() (MODULE_LISTING=0 through FULL_SOURCE=9), docs_detail_map() (TITLE_ONLY=0 through FULL_CONTENT=10), database_detail_map() (TABLE_LISTING=0 through FULL_CATALOG=11).

Design Decisions

• Used duck-typing (_SkeletonCompressorLike = Any) for the skeleton compressor to avoid circular imports between this module and acms_service.py
• ChildContextResult wraps both request and skeleton data — the spec shows metadata being passed on ContextRequest but the model doesn't have a metadata field, so we return a richer result instead
• Gradient formula: base - floor(base * distance / breadth) — at distance 0 gives full depth, at max distance gives 0, matching spec examples exactly
• Relevance score: 1.0 - distance / (breadth + 1) — smooth decay from 1.0 at focus to near-0 at edge
• Existing DetailLevelMap in crp.py is reused (not duplicated)

Test Coverage

• 27 Behave scenarios (features/depth_breadth_projection.feature): model creation/validation, BFS traversal at breadth 0/1/2, gradient vs uniform depth, named depth resolution, multi-focus, fragment conversion, preset maps, inheritance computation, skeleton injection/skip, error cases
• 9 Robot Framework tests (robot/depth_breadth_projection.robot): end-to-end component verification
• ASV benchmarks (benchmarks/depth_breadth_projection_bench.py): latency for spec creation, node creation, small/medium graph projection, fragment conversion, inheritance

Verification

Check	Result
nox -s lint	✅ 0 issues
nox -s typecheck	✅ 0 errors (pyright strict)
nox -s unit_tests	✅ 8551 scenarios, 0 failures
nox -s integration_tests	✅ 1212 tests, 0 failures
nox -s coverage_report	✅ 97.0% (≥97% threshold)

## Implementation Notes **PR**: #603 **Branch**: `feature/m5-depth-breadth-projection` **Commit**: `6a4529ea` — `feat(acms): implement depth/breadth projection system` ### Source: `src/cleveragents/application/services/depth_breadth_projection.py` (530 lines) Seven components implemented per spec §25265-25340 and §43057-43128: 1. **`ProjectionSpec`** — Frozen Pydantic model capturing a projection request. Fields: `focus` (tuple of URIs, min 1), `breadth` (int ≥ 0, default 2), `depth` (int or named string, default 3), `depth_gradient` (bool, default True), `domain` (str, default "uko-code:"). Validates non-negative depth. 2. **`ProjectedNode`** — Frozen Pydantic model for a materialized UKO node with `uri`, `distance` from focus, `resolved_depth` after gradient, and `label`. 3. **`DepthBreadthProjector`** — Stateless BFS projector. Maintains a registry of `DetailLevelMap` instances per domain. `project()` does BFS from focus URIs over an adjacency list, computing `resolved_depth = base - floor(base * distance / breadth)` for each node. `project_to_fragments()` converts to `ContextFragment` with relevance inversely proportional to distance. Handles multiple focus items. 4. **`PlanContextInheritance`** — Service implementing `compute_child_context()`. Computes child detail = parent avg + delta * max_detail_increase (capped at 9), child breadth = max(1, parent - delta), skeleton budget = child_budget * skeleton_ratio. Injects skeleton via duck-typed compressor. Returns `ChildContextResult`. 5. **`ChildContextResult`** — Frozen model with `request: ContextRequest`, `skeleton_fragments: tuple[ContextFragment, ...]`, `parent_context_hash`, `skeleton_budget`, `depth_delta`. Separates the request from skeleton data since `ContextRequest` has no `metadata` field. 6. **`InheritanceConfig`** — Frozen config: `skeleton_ratio=0.2`, `min_skeleton_tokens=32`, `max_detail_increase=3`. 7. **Built-in presets**: `code_detail_map()` (MODULE_LISTING=0 through FULL_SOURCE=9), `docs_detail_map()` (TITLE_ONLY=0 through FULL_CONTENT=10), `database_detail_map()` (TABLE_LISTING=0 through FULL_CATALOG=11). ### Design Decisions - Used duck-typing (`_SkeletonCompressorLike = Any`) for the skeleton compressor to avoid circular imports between this module and `acms_service.py` - `ChildContextResult` wraps both request and skeleton data — the spec shows metadata being passed on `ContextRequest` but the model doesn't have a metadata field, so we return a richer result instead - Gradient formula: `base - floor(base * distance / breadth)` — at distance 0 gives full depth, at max distance gives 0, matching spec examples exactly - Relevance score: `1.0 - distance / (breadth + 1)` — smooth decay from 1.0 at focus to near-0 at edge - Existing `DetailLevelMap` in `crp.py` is reused (not duplicated) ### Test Coverage - **27 Behave scenarios** (`features/depth_breadth_projection.feature`): model creation/validation, BFS traversal at breadth 0/1/2, gradient vs uniform depth, named depth resolution, multi-focus, fragment conversion, preset maps, inheritance computation, skeleton injection/skip, error cases - **9 Robot Framework tests** (`robot/depth_breadth_projection.robot`): end-to-end component verification - **ASV benchmarks** (`benchmarks/depth_breadth_projection_bench.py`): latency for spec creation, node creation, small/medium graph projection, fragment conversion, inheritance ### Verification | Check | Result | |-------|--------| | `nox -s lint` | ✅ 0 issues | | `nox -s typecheck` | ✅ 0 errors (pyright strict) | | `nox -s unit_tests` | ✅ 8551 scenarios, 0 failures | | `nox -s integration_tests` | ✅ 1212 tests, 0 failures | | `nox -s coverage_report` | ✅ 97.0% (≥97% threshold) |

freemo referenced this issue from a commit 2026-03-05 15:25:48 +00:00

feat(acms): implement depth/breadth projection system

freemo referenced this issue from a commit 2026-03-05 15:42:22 +00:00

feat(acms): implement depth/breadth projection system

freemo closed this issue 2026-03-05 15:47:37 +00:00

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Currently being processed by the merge driver.

  

auto/claimed-reviewer

Currently being processed by a reviewer worker.

  

auto/driver-down

Merge driver heartbeat stale; pipeline halted. Closed automatically on next clean tick.

  

auto/invariant-violation

Detected master commit violating the strict merge invariant. Tracked as an issue (not a PR label); kept here for label completeness.

  

auto/last-attempt-tier-0

In-cycle escalation: most recent attempt ran at the Tier 0 slot (`tier-0`). Slot's model defined in .opencode/models/tiers.yaml.

  

auto/last-attempt-tier-1

In-cycle escalation: most recent attempt ran at the Tier 1 slot (`tier-1`). Slot's model defined in .opencode/models/tiers.yaml.

  

auto/last-attempt-tier-2

In-cycle escalation: most recent attempt ran at the Tier 2 slot (`tier-2`). Slot's model defined in .opencode/models/tiers.yaml. Gated behind IMPLEMENTER_ESCALATION_TIER2_ENABLED.

  

auto/last-attempt-tier-min

In-cycle escalation: most recent attempt ran at the Tier -1 slot (`tier-min`). Slot's model defined in .opencode/models/tiers.yaml. Suffix is ``-min`` (not ``--1``) so the Forgejo UI reads naturally.

  

Automation Tracking

Tracking issues used by the AI Automation system for agents to communicate and report.

  

auto/needs-conflict-resolution

Rebase conflict needs LLM conflict-resolver.

  

auto/needs-implementer

Failing CI needs implementer attention.

  

auto/postmortem

Documenting a driver incident or rollback.

  

auto/ready-to-merge

Reviewer has APPROVED this PR and no later REQUEST_CHANGES is outstanding. The merge driver requires this label to even consider a PR for merging. Set by the reviewer worker on APPROVE; cleared on REQUEST_CHANGES.

  

auto/restart-throttled

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.

  

auto/sentinel

Sentinel PR duplicated from upstream into a personal fork by tools/duplicate_prs_to_fork.py for pipeline testing. Lives only in the fork; the canonical pipeline never sees it.

  

auto/stale-inactivity

No implementer activity for N days. Flagged for human review. Auto-cleared on next push to head branch.

  

auto/unstable

Repeatedly fails on current master (>= 3 ci-fail-on-rebased-sha releases in 12 h). Excluded from driver until human triage.

  

Blocked

A ticket in a blocked state and unable to complete until some other task is completed first.

  

Bounty

$100

A bounty of $100 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$1000

A bounty of $1000 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$10000

A bounty of $10000 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$20

A bounty of $20 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$2000

A bounty of $2000 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$250

A bounty of $250 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$50

A bounty of $50 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$500

A bounty of $500 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$5000

A bounty of $5000 for any open-source contributor who provides a MR that solves this issue

  

Bounty

$750

A bounty of $750 for any open-source contributor who provides a MR that solves this issue

  

MoSCoW

Could have

Could have feature in order to satisfy the epic/legendary.

  

MoSCoW

Must have

Must have feature in order to satisfy the epic/legendary.

  

MoSCoW

Should have

Should have feature in order to satisfy the epic/legendary.

  

Needs Feedback

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.

  

Points

2

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

  

Points

21

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

  

Points

3

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

  

Points

34

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

  

Points

5

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

  

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

Backlog

This ticket has backlogged priority and is not to be worked on yet

  

Priority

CI Blocker

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

  

Priority

Critical

The priority is critical

  

Priority

High

The priority is high

  

Priority

Low

The priority is low

  

Priority

Medium

The priority is medium

  

Signed-off: Owner

When an epic or legendary is in review it must be signed off by owner, tech lead, and scrum master before being marked as completed.

  

Signed-off: Scrum Master

When an epic or legendary is in review it must be signed off by owner, tech lead, and scrum master before being marked as completed.

  

Signed-off: Tech Lead

When an epic or legendary is in review it must be signed off by owner, tech lead, and scrum master before being marked as completed.

  

Spike

A ticket for learning a tool or technology that is needed to be able to do future planning and design.

  

State

Completed

The ticket has been fully implemented, completed, and merged with the source code. This label should only be applied once a ticket is closed.

  

State

Duplicate

A ticket that represents the same content as an existing ticket.

  

State

In Progress

A ticket that is actively being developed.

  

State

In Review

A ticket that has had some code completed to implement but is waiting to pass peer review and is not yet merged in.

  

State

Paused

This ticket's work started but wasn't finished. It's on hold (likely in a feature branch) and will be resumed later, either due to a blocker or a delay.

  

State

Unverified

All new tickets start in this state. A developer may set it to show the ticket is unverified. This means we haven't agreed to work on it. It will either move to a verified state or be closed as wontdo.

  

State

Verified

The issue has been verified by a developer as legitimate. It will be worked on and verified tickets are now considered part of the backlog.

  

State

Wont Do

This ticket has been decided it wont be done. This may mean the bug has been determined to not be real (cant verify) or the feature is one we have decided we dont want to adopt.

  

Type

Automation

Any edits or discussion about the AI automated coding system.

  

Type

Bug

Something that doesnt work as intended.

  

Type

Discussion

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

  

Type

Documentation

An error or improvement needed in the documentation.

  

Type

Epic

Any first tier epic. That is, an epic which contains only issues as children and will not have sub-epics.

  

Type

Feature

Some new functionality not present.

  

Type

Legendary

A type of Epic which will contain other Epics.

  

Type

Refactor

A code change that restructures existing code without changing its external behavior.

  

Type

Support

Someone needs help using the project.

  

Type

Task

A generic task that doesnt fit into the other type categories.

  

Type

Testing

Work exclusively focusing on fixing or expanding testing.

No labels

auto/needs-reevaluation

controller-managed

auto/blocked-by-deps

auto/ci-timeout

auto/claimed-implementer

auto/claimed-merge

auto/claimed-reviewer

auto/driver-down

auto/invariant-violation

auto/last-attempt-tier-0

auto/last-attempt-tier-1

auto/last-attempt-tier-2

auto/last-attempt-tier-min

Automation Tracking

auto/needs-conflict-resolution

auto/needs-implementer

auto/postmortem

auto/ready-to-merge

auto/restart-throttled

auto/revert

auto/sentinel

auto/stale-inactivity

auto/unstable

Blocked

Bounty

$100

Bounty

$1000

Bounty

$10000

Bounty

$20

Bounty

$2000

Bounty

$250

Bounty

$50

Bounty

$500

Bounty

$5000

Bounty

$750

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

Type

Task

Type

Testing

Milestone

Clear milestone

No items

No milestone

v3.4.0

Projects

Clear projects

No items

No project

Assignees

Clear assignees

No assignees

freemo

1 participant

Notifications

Subscribe

Due date

The due date is invalid or out of range. Please use the format "yyyy-mm-dd".

No due date set.

Blocks

#396 Epic: ACMS Context Pipeline

cleveragents/cleveragents-core

Reference

cleveragents/cleveragents-core#544

No description provided.