with one click
with one click
Code Review Protocol
Coordinate Pairing-mode doer/reviewer sessions through a Markdown blackboard. Use when the user invokes /adversarial-pairing with role and blackboard-path arguments or asks multiple pairing agents to coordinate plan review, implementation, staged code review, and follow-up review rounds without Liza multi-agent mode.
Analyze Liza `.liza/agent-prompts/` and `.liza/agent-outputs/` from a context-engineering perspective: prompt payload shape, context budget use, cacheability, duplicated or missing context, instruction hierarchy, tool-output pressure, role-specific context fit, and prompt-output feedback loops. Use when diagnosing agent context bloat, prompt drift, poor agent handoffs, repeated misunderstandings, excessive tool output, or whether Liza agents received the right information at the right time.
Transform vision documents into structured epics that bound story-writing
Transform requirements into user stories for coding tasks
Context-efficient delegation to subagents (read-only default, READ-WRITE opt-in)
| name | liza-logs |
| description | Analyze Liza agents logs |
SCOPE:
The logs in .liza/agent-outputs/ and task state in .liza/state.yaml
(nowhere else unless told otherwise explicitly).
The prompt may filter more specifically, e.g. a specific role, task, status,
or time range.
OBJECTIVE: Find recurring task, review, integration, tool, context, and setup frictions; correlate state symptoms with log evidence; propose fixes.
PROTOCOL:
python3 ~/.liza/skills/liza-logs/scripts/analyze-log.py .liza/agent-outputs/coder-*.txt # all coder agents
python3 ~/.liza/skills/liza-logs/scripts/analyze-log.py .liza/agent-outputs/coder-1-*.txt # single agent
python3 ~/.liza/skills/liza-logs/scripts/analyze-log.py --summary-by-role .liza/agent-outputs/*.txt
By default, run the analyzer per role.
Use --summary-by-role when you need cross-role aggregate token, tool, MCP,
error, and skill-invocation totals.
.liza/state.yaml for task-level frictions before drawing conclusions:python3 ~/.liza/skills/liza-logs/scripts/analyze-state.py .liza/state.yaml
review_cycles_total >= 4INTEGRATION_FAILED, BLOCKED, SUPERSEDED, or ABANDONEDreview_cycles_total is missing, count task history events named
rejected or review_verdict_rejectedReport sections: session header, token summary, content breakdown, top items by size, tool usage, empty turns, skill invocations, secret-word/init breadcrumb detection, turn timeline, tool result breakdown, MCP usage, efficiency insights, and struggle sequences. Rich format adds per-turn context growth, top longest turns, cost breakdown with system-prompt replay cost, and MCP server status. Sparse logs have aggregate usage only; do not infer exact per-turn growth or cost.
query-log.py to extract trimmed evidence windows for
specific questions, for example:python3 ~/.liza/skills/liza-logs/scripts/query-log.py .liza/agent-outputs/coder-3-*.txt --around-errors 3 --task architecture-4-code-planning-0-b-repair-0-coding-1
coder-1-20260417-171454.txt) so the reader can trace the claim
back to the exact source log quickly.Before proposing a fix, check whether the fix is already implemented (e.g. an instruction already exists but agents ignore it):
.liza/agent-prompts/~/.liza/ (CORE.md, AGENT_TOOLS.md, MULTI_AGENT_MODE.md)Write the final report using skills/liza-logs/report-format.md.
Propose fixes whenever possible.
FALSE POSITIVES:
.liza/agent-outputs/*.txt files are not automatically agent reasoning bloat. Attribute volume to avoidable behavior before raising it: broad file reads, repeated large diffs, noisy failing tests, unbounded command output, or repeated tool loops.NOTE: The skill contains a web tool for humans to inspect logs: ~/.liza/skills/liza-logs/tools/liza-session-analyzer.html