一键导入
diagnose-aria
Use to diagnose ARIA-NBV bugs, regressions, failing metrics, Streamlit issues, docs builds, KG failures, or suspicious outputs.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Use to diagnose ARIA-NBV bugs, regressions, failing metrics, Streamlit issues, docs builds, KG failures, or suspicious outputs.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use for ARIA-NBV Typst proposal/thesis authoring, shared notation, scientific prose, citations, scientific/geometric figures, tables, Mermaid inclusion, and compile/render QA.
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.
Use to localize unknown ARIA-NBV files, symbols, docs, or source families through deterministic local discovery before handoff.
Use when reviewing ARIA-NBV working-tree or PR diffs, following up external/model review findings, or supplying ARIA-NBV domain context to the oh-my-codex code-review harness with severity-ranked file and line findings.
Use when ARIA-NBV work touches pose, camera, coordinate-frame, CW90, PyTorch3D projection, depth backprojection, candidate frusta, or geometry diagnostics contracts.
Stress-test vague, high-impact, research-facing, advisor-facing, or cross-surface ARIA-NBV decisions before implementation, including theory-rich or elaborate Plan Mode option analysis when requested.
| name | diagnose-aria |
| description | Use to diagnose ARIA-NBV bugs, regressions, failing metrics, Streamlit issues, docs builds, KG failures, or suspicious outputs. |
| metadata | {"mode":"diagnostic","not_when":["broad planning without a concrete symptom","pure source localization with no failure","reviewing concrete diffs rather than reproducing a symptom"],"handoff_to":["external analysis workflow capability for domain-agnostic read-only causal ranking before mutation","plan-grill for broad planning without a concrete symptom","aria-nbv-context for localizing an unknown failure surface","code-review-aria-nbv for diff review","specialized contract skills after the failing surface is known"],"evidence_required":["smallest reproducible failing loop or explicit reason none exists","exact command, traceback, metric, or bad output","passing loop after the fix"],"applies_to":["**"],"triggers":["bug","regression","failing test","suspicious metric"],"must_read":["AGENTS.md",".agents/memory/state/GOTCHAS.md",".agents/references/verification_matrix.md"],"canonical_sources":["AGENTS.md",".agents/references/source_order.md#role-split",".agents/references/verification_matrix.md",".agents/memory/state/GOTCHAS.md"],"context7_refs":["/websites/streamlit_io","/pytorch/pytorch"],"tool_refs":["mcp__code_index.search_code_advanced","mcp__MCP_DOCKER.browser_run_code","mcp__MCP_DOCKER.analyze_python_file","mcp__MCP_DOCKER.get_package_metrics"],"verification":["the narrowest reproducer for the failing surface","focused regression test after fixes"]} |
OMX owns orchestration, autonomy, goals, loops, and handoffs. Use external read-only causal ranking only when no concrete command, artifact, metric, or runtime symptom is known yet.
diagnose-aria is the ARIA-NBV sidecar for existing symptoms: it picks the
local reproducer, inspection command, domain verification loop, expected signal,
and passing loop. Use references/upstream-mattpocock.md only as optional
generic debugging inspiration; ARIA repro and verification loops remain
authoritative.
Use this skill for hard bugs or regressions in:
PoseTW / CameraTW, rendering, RRI, VIN, or rollout behaviorUse the smallest tool that can reproduce or inspect the symptom.
cd aria_nbv && uv run nbv-st --server.port <port>
The wrapper disables Streamlit file watching by default; pass
--server.fileWatcherType=<mode> before -- only when watcher behavior is
the suspected issue.cd aria_nbv && uv run pytest tests/test_streamlit_entry.py tests/app
Start with entrypoint or panel-specific tests before live UI inspection.make offline-info, make offline-tree,
make offline-samples, and make offline-sample-rerun-random.make rollouts-info, make rollouts-stats, and
make rollouts-rerun-random.cd aria_nbv && uv run nbv-rerun-inspect ....
Hand off to rerun-nbv-inspector for visual, frame-coordinate, depth/RGB,
OBB, frustum, or .rrd entity-tree issues.make kg-status, make kg-route KG_TASK="<task>",
make kg-claim-check KG_CLAIM="<claim>", make qmd-frontmatter-check,
and focused Quarto or Typst renders for the touched page.cd aria_nbv && uv run pytest <focused-test>, then targeted
cd aria_nbv && uv run ruff check <path> only for touched Python surfaces.Build the smallest deterministic loop that reproduces the user-visible symptom:
cd aria_nbv && uv run pytest <focused-test>cd aria_nbv && uv run nbv-summary --config-path <config>tests/data_handling/test_vin_offline_store.pycd docs && quarto render <page> or
typst compile typst/seminar_slides/<file>.typ --root .make kg-* command that owns the failing artifactDo not proceed on code guesses until the loop fails in the same way the user reported, or until you can state exactly why a loop cannot be built.
If no reproducible loop can be built, do not patch by guesswork. State the
missing artifact, access, fixture, command, or metric needed next. If the
blocker is durable repo debt, record a blocked issue in .agents/issues.toml
through agents-db.
[DEBUG-...] prefix.If no good test seam exists, record that as architecture debt in
.agents/issues.toml or .agents/refactors.toml through agents-db.
After the failing surface is known, include the relevant contract skill named by root routing or nested package guidance in the repro and verification loop.
Report: