cli-and-indexing
Operate the PaperQA pqa CLI and local full-text index workflows safely.
- License 许可
- Apache-2.0
- 最近更新
- 2026-09-03
- Stars
- ★ 351
- Forks
- 27
01 前言 Front Matter
- name
- cli-and-indexing
- license
- Apache 2.0
- metadata
- { "disco-role": "operating" }
- description
- Operate the PaperQA pqa CLI and local full-text index workflows safely.
- disable-model-invocation
- true
02 资源文件 5
- 参考文档references/cli-reference.md6.3 KB
- 参考文档references/indexing-workflows.md7.4 KB
- 参考文档references/troubleshooting.md7.4 KB
- 脚本scripts/inspect_cli.py6.0 KB
- 脚本scripts/validate_manifest.py9.1 KB
03 SKILL.md 正文
PaperQA CLI and Indexing
Use this sub-skill when the task is about the pqa command-line interface or
PaperQA's local search indexes: pqa ask, pqa search, pqa index, pqa view,
pqa save, --settings, --index, PQA_HOME, manifest CSVs, named indexes,
autogenerated indexes, answer history search, and index reuse or invalidation.
Do not use this sub-skill for Python Docs/ask/agent_query RAG code,
parser internals, metadata-provider APIs, or deep model/provider settings. Route
those to the sibling sub-skills for agentic RAG, docs/parsing, metadata/sources,
and settings/configuration.
Operating rules
- For CLI syntax and safe examples, read references/cli-reference.md.
- For index names, directories, manifests, reuse, answer indexes, recursive scanning, and invalidation, read references/indexing-workflows.md.
- For failures or surprising behavior, read references/troubleshooting.md.
- Use scripts/inspect_cli.py before relying on a
user's environment-specific
pqaentry point or parser behavior. It only inspects help text and does not run queries, embeddings, or metadata lookups. - Use scripts/validate_manifest.py before an index build that depends on a manifest CSV.
Safety boundary
pqa ask and pqa index can call LLM, embedding, and paper-metadata providers
while parsing, indexing, searching, or answering unless the user configured
local/fake/offline-compatible settings. Before running those commands, make the
provider, credential, network, cost, and rate-limit implications explicit.
Prefer pqa view, pqa search on an existing index, inspect_cli.py, and
validate_manifest.py for dry-run or diagnostic steps.
Quick routing map
- Need to view or save named CLI settings: use
pqa view/pqa save, then cross-route provider details to../settings-and-configuration/SKILL.md. - Need to build or reuse a local paper index: use this sub-skill's indexing workflows and keep document paths user-owned.
- Need full-text search over a prebuilt paper index or previous answers: use
pqa searchwith the correct--indexand--agent.index.index_directory. - Need generated answers with citations from local documents: this sub-skill
covers the CLI command shape; route answer behavior and Python API details to
../agentic-rag/SKILL.md. - Need file-format parsing or custom file filtering beyond CLI flags: route to
../docs-and-parsing/SKILL.md.
04 同仓库更多 Skills
passnet-triton-opt
Make a single PassNet Triton kernel fast AND numerically faithful: performance model (when a replacement can win at all), block/grid/warp tuning, autotune policy, launch overhead, and per-op numeric recipes to pass the dtype baseline tolerances. Use when a pass matches and is correct but speedup below expected, or when correctness fails by small numeric margins.
passnet-solve
END-TO-END playbook for solving one PassNet sample: analyze the computation graphs, decide the optimization strategy (what to fuse, what to replace, what to leave alone), drive the iteration loop, and maximize the sample score. This is the ENTRY skill — invoke it first for any PassNet optimization task; it tells you when to use passnet-pattern-fusion, passnet-triton-opt and passnet-feedback.
passnet-skill
PassNet GPU kernel optimization via compiler passes. Design and implement Triton-based optimization passes, create pass files under ./pass_dir/, self-evaluate with pass_evaluator, and iterate to maximize GPU speedup.
passnet-pattern-fusion
Author PassNet pass files: write patterns that actually MATCH the FX graph, pick fusion regions (which ops to absorb into one Triton kernel), and structure multi-pass submissions with the mandatory shared-dispatch architecture. Use when creating or fixing pattern()/replacement_args()/replacement_func() files, when a pass "failed to match", or when deciding how to fuse multiple kernels/ops.
passnet-orchestrate
Round/batch planning and decision support for PassNet graph optimization. Use for multi-sample triage, worker allocation, eval-budget policy, and post-eval keep/revert decisions. For solving one concrete sample end to end, use passnet-solve as the entry skill; consult this skill only when you need broader planning or a specific decision gate.
passnet-feedback
Fast, deterministic feedback for PassNet work: pre-flight pattern/match verification WITHOUT burning a GPU evaluation, per-node bottleneck analysis of a sample's graphs, and eval-log parsing into per-variant status + estimated score + failure classification. Use BEFORE every GPU evaluation (check_pattern), at the START of a sample (analyze_graph), and AFTER every evaluation (parse_eval_log).