ops-readonly gets kuma_alerts (host export kuma-export.py, one more read-only
mount). kuma-triage.py sorts the same data without a model. Flow H runs the
agent with skill alert-triage.md. Flow B: one open incident per monitor, an
UP closes all of them, titles name start and end and stay under Outline's
limit. B and D accept Kuma only with a header token. Monitoring notes: ntfy
rejects Kuma messages for monitors without a URL, resend for long outages.
ops-readonly gets two read-only questions, waf_blocked and waf_rule_info. The
rule ids per blocked request are in CrowdSec's alerts, not in its log, and
alerts need machine credentials that can also write, so waf-export.py runs on
the host and the container gets one more read-only mount.
Workflow G lets a local 3B model draft CRS route exclusions as a Forgejo issue.
The model never writes rule syntax, a code node checks every field against the
tool output, the only write permission is an issue in one repo, trusted sources
live in the workflow and the trigger needs a token.
waf-propose.py does the same without a model: 5 of 5 false positives, no
exclusion for an attack, 0.03 s. The model proposed an exclusion for nearly
every attack it saw. Numbers and the traps we hit are in HARDENING.md.
New: ops-readonly, the read-only twin of the episode 9 ops-actions runner
(fixed question list, three read-only mounts, no docker socket, read_only,
cap_drop ALL). Four role skills in agents/skills/, loaded at run time from
this repo's Forgejo. Two workflows: E (one agent, seven tools, one skill) and
F (three agents, one skill each, the workflow is the orchestrator).
Measured over 20 runs: no run of either variant produced all numbers and
lists correct. The solo agent confuses similar counts and skips a tool; the
crew calls every tool but drops fields at each role boundary. Sharpening the
skill files did not help the crew, it made it worse. Logs are attacker text:
an instruction in a request path is carried into the report as data, not
obeyed, but carried.
Claude-Session: https://claude.ai/code/session_017iP581CYtPfxdZYPPAyWZA
