Shared memory and context tools for agentic work.
Code Rooms
# Bug-Hunt Audit Lane: audit-04
Round: `bughunt-click-mc1-20260518T000000Z`
Repo: `click-python-cli`
Instruction mode: `direct`
Workspace: `/Users/kle1nz/m1nd/.m1nd-field-workspaces/bughunt-click-mc1-20260518T000000Z/audit-04/click-python-cli`
Work as if this is a real production-minded dependency audit.
Do not guess the benchmark hypothesis, bug count, or comparison arm.
Find real behavioral defects, edge-case regressions, missing tests, or contract mismatches.
Do not patch files. Do not read `operator-only/` artifacts.
## Direct Mode
Do not use m1nd tools or m1nd helper scripts for this audit.
Use normal local repo tools such as file reads, rg, git, tests, and compiler/runtime output.
## Required Output
Write your final JSON result to `/Users/kle1nz/m1nd/docs/benchmarks/bug-hunt-rounds/bughunt-click-mc1-20260518T000000Z/lane-results/audit-04.json`.
Append investigation events to `/Users/kle1nz/m1nd/docs/benchmarks/bug-hunt-rounds/bughunt-click-mc1-20260518T000000Z/event-streams/audit-04.jsonl` using `event_source="agent"`.
Every event must include `schema`, `round_id`, `lane_id`, `event_source`, `event_type`, and `created_at`.
Record at least `audit_started`, one first-discovery event such as `findings_identified`, `focused_probes`, or `runtime_probe`, and `result_written`.
Use ISO timestamps; do not use `ts` or `event` as substitutes in new rounds.
Use the schema in `lane-result-template.json`.
Findings should include title, severity, file, symbol, cause, impact, evidence, reproduction_or_test, and confidence.
Extra findings are welcome, but they must be concrete and source-backed.