
unit-executor
Execute exactly one runnable unit from `UNITS.csv` (first TODO whose dependencies are DONE), then up
Unit Executor
The leading principle is atomicity: one invocation owns one Unit Attempt and either commits one accepted Completion or records one diagnosable block. It never starts a second Unit.
Inputs
UNITS.csvand the selected Unit row.- Files declared by that row's
inputsfield. DECISIONS.mdwhen the Unit is checkpoint-gated.
Outputs
- Files declared by the Unit's
outputsfield. - Updated
UNITS.csv, Run Evidence, and optionalSTATUS.mdprojection. output/QUALITY_GATE.mdwhen strict quality checks block Completion.
Steps
1. Reconcile and select one Unit
Inspect the Workspace through the Pipeline adapter. Select the requested Unit,
or the first TODO Unit whose dependencies are DONE. Stop when a HUMAN
checkpoint, unresolved Decision, open Attempt, or integrity failure prevents
selection.
Completion criterion: exactly one eligible Unit is selected, or one blocking condition is recorded with a concrete next action.
2. Open the Attempt
Start semantic work through the adapter, never by editing a status cell:
uv run python scripts/pipeline.py mark \
--workspace workspaces/<name> \
--unit-id <U###> \
--status DOING \
--note "starting semantic execution"
Completion criterion: the Unit is DOING and one matching open Attempt owns
the execution.
3. Execute the declared Skill
Read the selected Unit's Skill and only the context pointers required by this branch. Produce the declared outputs without changing unrelated Workspace artifacts.
Completion criterion: every required output exists or the failure is specific
enough to commit as BLOCKED.
4. Verify and commit Completion
Evaluate the Unit acceptance rule and strict quality contract when requested. Commit through the adapter:
uv run python scripts/pipeline.py mark \
--workspace workspaces/<name> \
--unit-id <U###> \
--status DONE \
--note "acceptance checked"
Use BLOCKED with a concrete reason when acceptance fails. Do not directly
edit UNITS.csv; the adapter aligns Attempt, Artifact, Manifest, Decision, and
status projections.
Completion criterion: Completion is DONE with acceptance and provenance
evidence, or BLOCKED with a diagnosable Failure.
5. Stop after one Unit
Refresh the Workspace projection and report the completed or blocked Unit. Do not claim end-to-end completion and do not start the next eligible Unit.
Completion criterion: exactly one Unit changed execution state during this invocation and the next operator can resume from Workspace files.
Context Pointers
- The selected row in
UNITS.csvowns dependencies, inputs, outputs, acceptance, checkpoint, and Skill identity. - The selected Skill owns semantic behavior.
- The locked Pipeline owns cross-Unit gates and target Artifacts.
- Use
research-pipeline-runnerfor automatic continuation across Units.
Script
Quick Start
uv run python .codex/skills/unit-executor/scripts/run.py \
--workspace workspaces/<name>
All Options
--workspace <path>: existing Workspace.--unit-id <U###>: execute a specific eligible Unit.--inputs,--outputs,--checkpoint: Pipeline-runner compatibility arguments.--strict: block scaffold-like outputs and write the quality-gate report.
Examples
Run exactly one strict Unit:
uv run python .codex/skills/unit-executor/scripts/run.py \
--workspace workspaces/<name> \
--strict
Equivalent adapter command:
uv run python scripts/pipeline.py run-one \
--workspace workspaces/<name> \
--strict
The helper returns 0 for DONE or IDLE, and 2 for BLOCKED or ERROR.
Troubleshooting
- When no Unit is runnable, inspect dependencies, checkpoint approvals, and open Attempts before changing status.
- When a
DONEUnit has missing outputs, reopen it through the adapter with an explanatory note; never repair the CSV projection alone.