thkt /ablate - one-sided harness ablation
Input
$ARGUMENTS is an element path narrowing the measurement to one element. Omitted, every element Phase 1 enumerates is measured.
Where the criteria and thresholds live
The arm list, the run count per arm, and the pass threshold are all constants in ${CLAUDE_SKILL_DIR}/scripts/arms.py. The classification criteria live in ${CLAUDE_SKILL_DIR}/scripts/verdict.py. The DR-gate criteria, the confirmed-unmet marker and where the records are read from, live in ${CLAUDE_SKILL_DIR}/scripts/dr_gate.py. The measurement window and the rare-by-design set live in ${CLAUDE_SKILL_DIR}/scripts/usage_counts.py. The per-rule trigger tasks and the fixed task set live in ${CLAUDE_SKILL_DIR}/references/measurement-criteria.md. Do not copy a number into this body (docs/wiki/deterministic-script-judgment.md).
Phase 1: Enumerate
Call enumerate_elements(root) in skills/_lib/harness_elements.py for the harness elements and each one's classification. When $ARGUMENTS names an element path, hand Phase 2 that one alone.
python3 -c 'import sys; sys.path.insert(0, "skills/_lib"); import harness_elements, json; print(json.dumps(harness_elements.enumerate_elements(".")))'
Phase 2: Run the arms
For each element Phase 1 returned, and each arm in arms.ARMS, assemble the command arms.arm_command(arm, element) returns and run it arms.RUN_COUNT times. Take that element's triggering task from ${CLAUDE_SKILL_DIR}/references/measurement-criteria.md. Build one observation for that element out of the run results.
| Situation | Treatment |
|---|---|
The run count falls short of arms.RUN_COUNT |
Proceed with arms.measurement_status(runs) still returning unmeasured |
The element wiped+1 restores is unsettled |
arm_command stops with ValueError, so settle the element before calling it |
| A run fails and its result cannot be read | Leave that run uncounted and put only the runs that landed in the observation |
Phase 3: Report
Call report.write_report(root, observations). Before a delete candidate reaches the report, dr_gate.gate reads docs/decisions/ and holds back any element a live record governs, so the Summary counts them apart. It also runs usage_counts.py and folds each element's fire count and last-used date into the same Harness Elements table, so there is one route to see them, not a second one running alongside it. It writes to docs/audit/ by default, naming the file <YYYY-MM-DD>-<HHMMSS>-ablate.md in UTC, in the section order ${CLAUDE_SKILL_DIR}/templates/report-template.md carries.
python3 -c 'import sys; sys.path.insert(0, "skills/ablate/scripts"); sys.path.insert(0, "skills/_lib"); import report, json, pathlib; print(report.write_report(pathlib.Path("."), json.load(sys.stdin)))' < <observations.json>
Output
Removing anything the report names is a separate run: hand the delete candidates to docs/wiki/retire-rename-procedure.md, which owns the detection layer a retirement loses and the trigger for reviving it. This skill stops at the verdict.
| Item | Content |
|---|---|
| Report path | The path write_report returned |
| Delete candidates | The report's Delete Candidates section, or that there are none |
| Measured count | Rows in Verdicts that are not unmeasured |
| Usage | Each element's fire count and last-used date, in Harness Elements |