Agentic DMX Master Plan
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agentic-dmx
- Dominant language
- Jupyter Notebook
- Stars
- 10
- Forks
- 1
- Avg merge
- 1m
- Merged PRs (30d)
- 34
Description
Goal
Build the repo-local agentic DMX skill system in small, reviewable merge requests.
Ordered Sub-Issues
- #72 Scaffold repo-local
dmx-expert-orchestratorskill - #73 Define intake workflow for the orchestrator skill
- #74 Add default lightweight EDA guidance for user-supplied data paths
- #75 Write structure-first hierarchy and data-shape routing reference
- #76 Encode the “joint model first” routing policy
- #77 Add
keysand parameter-sharing reference - #78 Add posterior reweighting and conditional reuse reference
- #79 Add initialization, sufficient-stats, and pseudo-count reference
- #80 Distill
dmx_basics_conditional_vs_composite_mixture.ipynb - #81 Distill
dmx_example_process_sequences.ipynb - #82 Distill
dmx_example_reduced_search_space.ipynb - #83 Distill
dmx_variable_sequence_length_search_depth.ipynb - #84 Distill
dmx_basics_mixture_models.ipynb - #85 Distill
dmx_advanced_plsi.ipynb - #86 Distill
dmx_advanced_geotweet.ipynb - #87 Refactor
dmx-local-modelingto rely on the new references - #88 Add compute and scaling reference, including
torch_statsguidance - #89 Create a small benchmark prompt suite for agentic DMX tasks
- #90 Define an evaluation rubric for “DMX expert” behavior
- #91 Audit
src/dmx/statsdocstrings forkeys - #92 Improve highest-priority
src/dmx/statsdocstrings forkeys - #93 Audit
src/dmx/statsdocstrings for sufficient stats and pseudo-counts - #94 Improve
src/dmx/statsdocstrings for initialization semantics - #95 Add repo-curated canonical examples reference
- #96 Run benchmark review for orchestrator routing behavior
- #97 Run benchmark review for post-fit and downstream-task behavior
Notes
- One MR per child issue.
- Land work in the listed order unless a dependency changes.
- Open follow-up issues instead of broadening an existing child issue.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the ordered child issues and their completion status, especially the remaining benchmark reviews #96 and #97. Use the completed orchestrator, modeling, reference, and evaluation work as context. The plan is complete when the benchmark reviews for routing behavior and post-fit/downstream-task behavior are finished or have produced clearly scoped follow-up issues.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100