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fix(skill_manage): batch success rows carry the linter findings and org-sharing note

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Since operations[] became the only call shape (#97295) the batch's success
path rebuilt each row as {name, action, file_path, success} and dropped every
advisory key the per-op handler attached — lint_warnings/lint_hint from the
create linter and the org_sharing note. The model never saw a finding.
Carry those keys onto the row, mirroring what the failure path already does
for teaching payloads.
This commit is contained in:
kshitijk4poor
2026-09-22 12:20:13 +05:30
committed by kshitij
parent 405975a7c0
commit 54a867a6e9
2 changed files with 20 additions and 2 deletions
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11
tests/tools/test_skill_manage_batch.py
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@@ -54,6 +54,17 @@ class TestSkillManageBatch(unittest.TestCase):
for rel in ("SKILL.md", "references/a.md", "scripts/r.py"):
self.assertTrue(os.path.exists(os.path.join(base, rel)), rel)
def test_advisory_findings_ride_on_the_op_result(self):
# operations[] is the only call shape, so a finding the per-op handler attaches must
# survive into the batch row or the linter is silent for every model call.
from tools.skill_linter import _BODY_SOFT_BUDGET_CHARS
self._call("probe", [{"action": "create", "content": SK.format(n="probe")}])
r = self._call("probe", [{"action": "patch", "old_string": "Step 1.",
"new_string": "- rule; why.\n" * (_BODY_SOFT_BUDGET_CHARS // 12 + 1)}])
self.assertTrue(r["success"], r)
rules = {w["rule"] for w in r["results"][0]["lint_warnings"]}
self.assertIn("oversized-body", rules)
def test_midbatch_failure_rolls_back_existing_skill(self):
self._call("probe", [{"action": "create", "content": SK.format(n="probe")}])
r = self._call("probe", [

11
tools/skill_manager_batch.py
View File

@@ -181,6 +181,9 @@ def _rollback(snapshots, find_skill):
return ("; ".join(notes) if notes else "all touched skills rolled back"), bool(notes)
_ADVISORY_KEYS = ("lint_warnings", "lint_hint", "org_sharing")
def _skill_manage_batch(operations, default_name: str = None, task_id: str = None,
session_id: str = None) -> str:
"""Apply operations atomically: every touched skill is snapshotted first and any
@@ -249,8 +252,12 @@ def _skill_manage_batch(operations, default_name: str = None, task_id: str = Non
if k not in ("success", "error") and v is not None:
fail.setdefault(k, v)
return json.dumps(fail, ensure_ascii=False)
results.append({"name": names[i], "action": op["action"],
"file_path": op.get("file_path"), "success": True})
entry = {"name": names[i], "action": op["action"],
"file_path": op.get("file_path"), "success": True}
# Advisory payloads (linter findings, org-sharing note) ride on the op result; the
# compact success row otherwise hides them and the model never sees a finding.
entry.update({k: parsed[k] for k in _ADVISORY_KEYS if parsed.get(k) is not None})
results.append(entry)
finally:
_smt._skill_gate_bypass.reset(token)
if rollback_failed: