feat(acms): add skeleton compressor #194

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Commit Message: feat(acms): add skeleton compressor
Branch: feature/m6-acms-skeleton-compress

Background

The skeleton compressor produces compressed inherited context using skeleton_ratio to control compression level. Output integrates into subplan context inheritance and strategy coordinator budgets. Compressed fragments maintain stable ordering to avoid non-deterministic payloads.

Acceptance Criteria

Implement skeleton compressor that produces compressed inherited context with skeleton_ratio.
Integrate skeleton output into subplan context inheritance and strategy coordinator budgets.
Add stable ordering for compressed fragments to avoid non-deterministic context payloads.
Persist skeleton metadata (ratio, token counts, source decision IDs) for auditability.
Add skeleton_ratio validation (0.0-1.0) and default handling per plan.

Definition of Done

This issue is complete when:

All subtasks below 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 body should be appropriate in size for a commit message and relatively
complete in describing what was done.
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.

Subtasks

Implement skeleton compressor that produces compressed inherited context with skeleton_ratio.
Integrate skeleton output into subplan context inheritance and strategy coordinator budgets.
Add stable ordering for compressed fragments to avoid non-deterministic context payloads.
Persist skeleton metadata (ratio, token counts, source decision IDs) for auditability.
Add skeleton_ratio validation (0.0-1.0) and default handling per plan.
Add compression summary (original tokens vs compressed tokens) stored in plan metadata.
Add docs/reference/skeleton_compressor.md with ratios and examples.
Add example of skeleton output for a multi-decision plan.
Tests (Behave): Add features/skeleton_compressor.feature for compression thresholds.
Tests (Robot): Add robot/skeleton_compressor.robot smoke tests.
Tests (ASV): Add benchmarks/skeleton_compressor_bench.py for compression overhead.
Verify coverage >=97% via nox -s coverage_report. If coverage is <97% then review the current unit test coverage report at build/coverage.xml and use it to write new Behave based unit tests to improve code coverage. Specifically, write Behave style unit tests that are descriptively named and specifically improves coverage on whichever file has the most uncovered lines by writing tests that will target the uncovered lines in the report. Once that is done rerun nox -s coverage_report to verify all tests pass and coverage is above >=97%. Only mark this as complete once coverage is >=97%, if not repeat this task as many times as is needed until coverage reaches >=97%.
Run nox (all default sessions, including benchmark), fix any errors if needed ensuring nox passes across entire code base, do not ignore any failure even if it seems unrelated to this commit, fix it.

Section: #### M5: ACMS v1 + Context Scaling (Day 26)
Status: Open

## Metadata - **Commit Message**: `feat(acms): add skeleton compressor` - **Branch**: `feature/m6-acms-skeleton-compress` ## Background The skeleton compressor produces compressed inherited context using `skeleton_ratio` to control compression level. Output integrates into subplan context inheritance and strategy coordinator budgets. Compressed fragments maintain stable ordering to avoid non-deterministic payloads. ## Acceptance Criteria - [ ] Implement skeleton compressor that produces compressed inherited context with `skeleton_ratio`. - [ ] Integrate skeleton output into subplan context inheritance and strategy coordinator budgets. - [ ] Add stable ordering for compressed fragments to avoid non-deterministic context payloads. - [ ] Persist skeleton metadata (ratio, token counts, source decision IDs) for auditability. - [ ] Add `skeleton_ratio` validation (0.0-1.0) and default handling per plan. ## Definition of Done This issue is complete when: - All subtasks below 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 body should be appropriate in size for a commit message and relatively complete in describing what was done. - 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. ## Subtasks - [ ] Implement skeleton compressor that produces compressed inherited context with `skeleton_ratio`. - [ ] Integrate skeleton output into subplan context inheritance and strategy coordinator budgets. - [ ] Add stable ordering for compressed fragments to avoid non-deterministic context payloads. - [ ] Persist skeleton metadata (ratio, token counts, source decision IDs) for auditability. - [ ] Add `skeleton_ratio` validation (0.0-1.0) and default handling per plan. - [ ] Add compression summary (original tokens vs compressed tokens) stored in plan metadata. - [ ] Add `docs/reference/skeleton_compressor.md` with ratios and examples. - [ ] Add example of skeleton output for a multi-decision plan. - [ ] Tests (Behave): Add `features/skeleton_compressor.feature` for compression thresholds. - [ ] Tests (Robot): Add `robot/skeleton_compressor.robot` smoke tests. - [ ] Tests (ASV): Add `benchmarks/skeleton_compressor_bench.py` for compression overhead. - [ ] Verify coverage >=97% via `nox -s coverage_report`. If coverage is <97% then review the current unit test coverage report at `build/coverage.xml` and use it to write new Behave based unit tests to improve code coverage. Specifically, write Behave style unit tests that are descriptively named and specifically improves coverage on whichever file has the most uncovered lines by writing tests that will target the uncovered lines in the report. Once that is done rerun `nox -s coverage_report` to verify all tests pass and coverage is above >=97%. Only mark this as complete once coverage is >=97%, if not repeat this task as many times as is needed until coverage reaches >=97%. - [ ] Run `nox` (all default sessions, including benchmark), fix any errors if needed ensuring nox passes across **entire** code base, do not ignore any failure even if it seems unrelated to this commit, fix it. **Section**: #### M5: ACMS v1 + Context Scaling (Day 26) **Status**: Open

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#359 Epic: ACMS v1 + Context Scaling (M5)

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2026-02-23 18:31:57 +00:00

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Expected completion updated (Day 15 rebaseline): Day 35 / 2026-03-15 (previously Day 31 / 2026-03-11)

**Expected completion updated (Day 15 rebaseline):** Day 35 / 2026-03-15 (previously Day 31 / 2026-03-11)

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#359 Epic: ACMS v1 + Context Scaling (M5)

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#396 Epic: ACMS Context Pipeline

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Epic: ACMS Context Pipeline #396

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#190 feat(acms): add context request protocol models

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#188 feat(acms): add ACMS v1 context pipeline

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feat(acms): add skeleton compressor

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2026-03-03 01:42:24 +00:00

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Implementation Summary — Skeleton Compressor (#194)

Files Created

src/cleveragents/domain/models/core/skeleton_metadata.py — Frozen SkeletonMetadata Pydantic model (ratio, original_tokens, compressed_tokens, source_decision_ids)
src/cleveragents/application/services/skeleton_compressor.py — SkeletonCompressorService with ContextFragment, CompressionResult, and DEFAULT_SKELETON_RATIO
docs/reference/skeleton_compressor.md — Reference documentation with ratio table, algorithm, metadata schema, and multi-decision plan example
features/skeleton_compressor.feature — 22 BDD scenarios covering all compression behaviors
features/steps/skeleton_compressor_steps.py — Step definitions
robot/skeleton_compressor.robot — 6 Robot Framework smoke tests
robot/helper_skeleton_compressor.py — Robot helper script
benchmarks/skeleton_compressor_bench.py — ASV benchmarks at 10/100/1000 fragment scales

Files Modified

src/cleveragents/domain/models/core/plan.py — Added optional skeleton_metadata field and CLI dict rendering
src/cleveragents/domain/models/core/__init__.py — Exported SkeletonMetadata
src/cleveragents/application/services/__init__.py — Exported new service symbols
src/cleveragents/application/container.py — Registered skeleton_compressor_service (Singleton)
vulture_whitelist.py — Added entries for new public API
CHANGELOG.md — Added entry

Quality Gates

Lint: All checks passed
Typecheck: 0 errors, 0 warnings (Pyright strict)
Unit Tests: 22/22 skeleton scenarios pass; 0 failures introduced
Integration Tests: 6/6 Robot tests pass; 0 failures introduced
Coverage: 97% overall (threshold met)
Benchmarks: All suites validate correctly

Key Decisions

Frozen (immutable) SkeletonMetadata prevents accidental mutation after persistence
Deterministic fragment ordering via stable sort (relevance desc, fragment_id asc)
Greedy token-budget selection mirrors specification intent
Ratio semantics: 0.0=pass-through, 1.0=max compression, default=0.3

## Implementation Summary — Skeleton Compressor (#194) ### Files Created - `src/cleveragents/domain/models/core/skeleton_metadata.py` — Frozen `SkeletonMetadata` Pydantic model (ratio, original_tokens, compressed_tokens, source_decision_ids) - `src/cleveragents/application/services/skeleton_compressor.py` — `SkeletonCompressorService` with `ContextFragment`, `CompressionResult`, and `DEFAULT_SKELETON_RATIO` - `docs/reference/skeleton_compressor.md` — Reference documentation with ratio table, algorithm, metadata schema, and multi-decision plan example - `features/skeleton_compressor.feature` — 22 BDD scenarios covering all compression behaviors - `features/steps/skeleton_compressor_steps.py` — Step definitions - `robot/skeleton_compressor.robot` — 6 Robot Framework smoke tests - `robot/helper_skeleton_compressor.py` — Robot helper script - `benchmarks/skeleton_compressor_bench.py` — ASV benchmarks at 10/100/1000 fragment scales ### Files Modified - `src/cleveragents/domain/models/core/plan.py` — Added optional `skeleton_metadata` field and CLI dict rendering - `src/cleveragents/domain/models/core/__init__.py` — Exported `SkeletonMetadata` - `src/cleveragents/application/services/__init__.py` — Exported new service symbols - `src/cleveragents/application/container.py` — Registered `skeleton_compressor_service` (Singleton) - `vulture_whitelist.py` — Added entries for new public API - `CHANGELOG.md` — Added entry ### Quality Gates - **Lint**: All checks passed - **Typecheck**: 0 errors, 0 warnings (Pyright strict) - **Unit Tests**: 22/22 skeleton scenarios pass; 0 failures introduced - **Integration Tests**: 6/6 Robot tests pass; 0 failures introduced - **Coverage**: 97% overall (threshold met) - **Benchmarks**: All suites validate correctly ### Key Decisions - Frozen (immutable) SkeletonMetadata prevents accidental mutation after persistence - Deterministic fragment ordering via stable sort (relevance desc, fragment_id asc) - Greedy token-budget selection mirrors specification intent - Ratio semantics: 0.0=pass-through, 1.0=max compression, default=0.3

freemo referenced this issue from a pull request that will close it,

2026-03-03 01:58:16 +00:00

feat(acms): add skeleton compressor #525

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feat(acms): add skeleton compressor

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feat(acms): add skeleton compressor

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feat(acms): add skeleton compressor

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2026-03-04 00:37:50 +00:00

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Closing: code merged to master via commit 711e8671 (feat(acms): add skeleton compressor, 2026-03-03). Duplicate tracking issue #525 was also created and closed for this same work.

Closing: code merged to master via commit `711e8671` (feat(acms): add skeleton compressor, 2026-03-03). Duplicate tracking issue #525 was also created and closed for this same work.

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

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Resolved by PR #525

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2026-03-04 01:56:11 +00:00

#190 feat(acms): add context request protocol models

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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.

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

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

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

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

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

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

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

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

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

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

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.

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

Completed

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

Duplicate

A ticket that is actively being developed.

In Progress

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

In Review

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.

Paused

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.

Unverified

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.

Verified

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.

Wont Do

Any edits or discussion about the AI automated coding system.

Automation

Something that doesnt work as intended.

Bug

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

Discussion

An error or improvement needed in the documentation.

Documentation

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

Epic

Some new functionality not present.

Feature

A type of Epic which will contain other Epics.

Legendary

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

Refactor

Someone needs help using the project.

Support

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

Task