360 Secure SkillHub
360 安全技能中心

exo-suite-linkage

该技能是科研工具链集成指南:串联hfpclawer文献与公式登记、expflow-pde实验与超参优化、omega-architect的Lean 4证明。核心是定义跨工具的文件/CLI契约(公式注册表、试验记录、Lean项目与编译结果),并提供端到端命令、低中高成本分层及缺层降级。典型场景:从论文提炼命题,先实验验证,再将少数关键陈述机器证明,输出带溯源工件。适合需可复现、可验证科研流程者。

diamond2nv
diamond2nv
热度 19.83
最近更新 2026-09-22 11:36:40
分类:自动化依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:研究 / 工作流 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add exo-suite-linkage
Metadata
name
exo-suite-linkage
description
Link the AI-for-Science toolchain — hfpclawer (literature + formula registry), expflow (experiments + HPO), omega-architect (Lean 4 proofs) — through file and CLI contracts, with per-layer cost tiers and a degradation ladder.
category
research
tags
["ai-for-science","formal-verification","literature","hpo","workflow"]
author
Li Shen
version
1.0.3
permissions
["shell","file_read","file_write","network"]
metadata
{"hermes":{"homepage":"https://github.com/diamond2nv/omega-architect","tags":["ai-for-science","integration","workflow","papers","hpo","formal-verification"],"related_skills":["omega-architect-formal-proof"]}}

Exo Suite Linkage — literature → experiments → machine-checked proof

Part of the Exo suite — literature (hfpclawer) → experiments (expflow-pde) → proofs (omega-architect). Three independent CLIs that meet through files and CLI calls, never imports. Entry skill: exo-suite-linkage (wiring, cost tiers low → medium → high, degradation ladder). Install: uv tool install hfpclawer · uv tool install expflow-pde · uv tool install "omega-architect @ git+https://github.com/diamond2nv/omega-architect@v0.2.3"

Three independent tools, one chain. Each keeps its own license and release cycle; they meet through files and CLI calls, never through imports.

Layer Tool Job Cost tier
Knowledge hfpclawer (PyPI hfpclawer) discover/dedup papers, extract formulas into a registry, verify citations low
Experiment expflow-pde run trials, HPO, record metrics for reproducibility medium
Proof omega-architect (omega) turn a statement into a compiler-checked Lean 4 proof high

Tiers are design targets, not guarantees: even the low tier spends bandwidth, disk and CPU, and rate-limited sources can throttle. Describe the chain as low → medium → high with the LLM steps named — never as "zero-token".

The contracts (files are the interface)

Producer Artifact Consumer
hfpclawer formula registry (JSONL: fid, latex, source id) + paper store expflow, omega, humans
hfpclawer citation audit report (per-reference status) humans, reviewers
expflow-pde trial records (JSONL: trial id, params, metric, seed) + best-parameter export omega, humans
omega-architect Lean project (statement + proof) + compile result + run metadata humans, reports

Design rules: ① every artifact is self-describing (identity + provenance), ② no cross-tool imports, ③ every hand-off is a command someone can paste, ④ the proof layer only ever receives statements that survived the earlier gates.

Minimal end-to-end run

# 1) Knowledge — collect the material and pin the statement
hfpclawer search --max-pages 3 && hfpclawer download && hfpclawer convert --to-wiki
#    → formula-registry entry: fid + latex + source id

# 2) Experiment — produce a number worth making a claim about
expflow pipeline submit --trials 20 --parallel 4
#    → trial records: params + metric + seed

# 3) Proof — formalize only the statement that carries the claim
omega prove 'theorem my_bound (x : ℝ) (h : 0 ≤ x) : 0 ≤ x^2 := by' --samples 4 --rounds 2
#    → compiler-accepted proof, or an honest "unverified"

Installing the three tools (every form below was run and verified)

# knowledge layer
uv tool install hfpclawer                     # or: pipx install hfpclawer · pip install hfpclawer
# pin the version — `uvx`/`uv tool run` reuse an installed tool env (may run an older
# release), and an unpinned launch is a supply-chain (rug-pull) risk
uvx "hfpclawer==0.2.3" --help                          # run without installing

# experiment layer
uv tool install expflow-pde                   # or: pipx install expflow-pde
# pin the version — `uvx`/`uv tool run` reuse an installed tool env (may run an older
# release), and an unpinned launch is a supply-chain (rug-pull) risk
uvx --from "expflow-pde==0.2.3" expflow --help         # note: package name and entry point differ

# proof layer (not on PyPI — install from the released tag)
uv tool install "omega-architect @ git+https://github.com/diamond2nv/omega-architect@v0.2.3"
# pin the version — `uvx`/`uv tool run` reuse an installed tool env (may run an older
# release), and an unpinned launch is a supply-chain (rug-pull) risk
uvx --from "git+https://github.com/diamond2nv/omega-architect@v0.2.3" omega --help
pipx install "git+https://github.com/diamond2nv/omega-architect@v0.2.3"

Each layer installs independently — start with the one you need and add the next when the hand-off artifact matters. (pipx needs a recent version: 1.0.0 cannot parse git specs.)

Degradation ladder (run what you have installed)

Installed What still works
hfpclawer only literature review, formula registry, citation verification
+ expflow experiments with recorded provenance; the formalization step stays an explicit TODO
+ omega machine-checked proofs for the statements that deserve the cost

Missing layers must degrade loudly: mark the unverified statement as unverified in the hand-off artifact instead of describing it in prose.

Cost discipline

  • Formalize few statements — the expensive layer scales with the number of theorems, not pages.
  • Raise --samples / --rounds only after the plumbing works at 1 / 1.
  • Move the high tier from API tokens toward local compute where a GPU is available (local Ollama / vLLM backend in omega-architect). How large that saving is depends on model strength and workload — measure it (same theorem set, both backends) before quoting any figure.
  • Record model and budget next to each proof artifact so a reader can see what the claim cost.
  • Keep the low tier genuinely low: mechanical extraction and verification make no LLM call, but bandwidth, disk and upstream rate limits still apply.

Pitfalls

  1. Claiming a proof layer ran when it did not — unverified statements must be labelled as such.
  2. Letting the expensive layer absorb noise — filter first (dedup, citation status, metrics), then prove.
  3. Implicit coupling — importing one tool from another breaks version independence; use files.
  4. Cost anecdotes — quote recorded run metadata (model, samples, rounds), not an estimate.
  5. Version drift — pin each tool (tag or released version) in the artifact provenance.

Verification checklist

  • Each artifact carries identity + provenance (tool version, model, seeds)
  • Unverified steps are labelled unverified in the final artifact
  • Proof claims are backed by the compiler, not by an LLM's word
  • Cost stated as a tier (low / medium / high) with LLM steps named