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Read Zulip stream/topic history for project context, summarize decisions, and recover requirements or action items. Use when task context may depend on prior Zulip discussion rather than only repository files.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | read-zulip |
| description | Read Zulip stream/topic history for project context, summarize decisions, and recover requirements or action items. Use when task context may depend on prior Zulip discussion rather than only repository files. |
Read Zulip history with shared credentials, then turn the result into project context for the current task.
Use scripts/read_zulip.py. It resolves credentials in this order:
ZULIPRC~/.zuliprc~/.config/zulip/zuliprcIf a collaborator keeps credentials elsewhere, pass --config /path/to/zuliprc
explicitly.
Never commit Zulip credentials into this repository.
For this repository, start with:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--url "https://quantum-info.zulipchat.com/#channels/591576/VibeYoga-Hackathon-QEC/general" \
--limit 20
If general returns no relevant messages, widen to the whole stream:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--channel 591576 \
--limit 20
If you still need the active thread referenced by repo docs, check:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--channel 591576 \
--topic "channel events" \
--limit 20
--limit 20.Recent messages from a stream/topic:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--channel "VibeYoga-Hackathon-QEC" \
--topic "channel events" \
--limit 20
Local substring filter over the fetched window:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--channel 591576 \
--limit 100 \
--contains benchmark
Machine-readable output:
python .claude/skills/read-zulip/scripts/read_zulip.py \
--channel 591576 \
--limit 20 \
--format json
--format json only when another tool/script will consume the result.Use when preparing an AutoQEC demo walkthrough, advisor presentation, hackathon pitch, recorded narration, or evidence-backed explanation of why the demos matter and why their outputs are correct.
Read the artifacts of a completed AutoQEC run and propose improvements to the framework code itself — DSL gaps, weak baselines, miscalibrated safety thresholds, prompt drift, env limitations, orchestration friction. Advisory only; never edits framework files. Use after a run completes when the user asks "what should we change before the next run?" or feels the system is plateauing.
Run the AutoQEC research loop on a given env YAML. Orchestrates the autoqec-ideator / autoqec-coder / autoqec-analyst subagents via the Agent tool, invokes the Runner CLI for training + evaluation, and writes history.jsonl + pareto.json. Use when the user asks "run AutoQEC on <env>", "start a research round", or provides an EnvSpec YAML.
Inspect a stalled or failed run, identify root cause (bad hyperparameter / NaN pattern / OOM / env misconfig), and recommend a fix. Does NOT apply fixes autonomously.
Read an entire runs/<id>/log.md and assess research narrative coherence, identify stuck hypotheses, detect overfitting signs, and write a review markdown. Use after a full run completes or when a loop has been stuck for many rounds.
Audit a predecoder checkpoint against holdout seeds. Runs independent_eval (3 fair-baseline guards) and interprets borderline cases with LLM reasoning. Use when a round produces a promising Δ_LER and the user wants to confirm it is not a reward-hacking artifact.