topostream_development — for Claude Code topostream_development, topostream_stage0_specs, community, for Claude Code, ide skills, schemas, wrap(Δθ) = arctan2(sin(Δθ), cos(Δθ)), scipy.optimize.linear_sum_assignment, token_type="sweep_delta", @numba.njit

v1.0.0

关于此技能

适用场景: Ideal for AI agents that need topostream development skill. 本地化技能摘要: # topostream Development Skill Project Identity topostream is a physics research artifact: a topology event stream toolkit for 2D XY and q=6 clock spin models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

功能特性

topostream Development Skill
Tech stack: Python 3.10+, NumPy, SciPy, Numba (jitted MC loops), jsonschema, pytest.
OS: Windows (PowerShell). All commands in this repo are run from PowerShell.
topostream stage0 specs/
├── agents/ # Agent handoff contracts (00–06). LOCKED — never edit.

# 核心主题

ItsReallyDanii ItsReallyDanii
[0]
[0]
更新于: 3/10/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
55
Canonical Locale
en
Detected Body Locale
en

适用场景: Ideal for AI agents that need topostream development skill. 本地化技能摘要: # topostream Development Skill Project Identity topostream is a physics research artifact: a topology event stream toolkit for 2D XY and q=6 clock spin models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

核心价值

推荐说明: topostream_development helps agents topostream development skill. topostream Development Skill Project Identity topostream is a physics research artifact: a topology event stream toolkit for 2D XY and q=6 clock

适用 Agent 类型

适用场景: Ideal for AI agents that need topostream development skill.

赋予的主要能力 · topostream_development

适用任务: Applying topostream Development Skill
适用任务: Applying Tech stack: Python 3.10+, NumPy, SciPy, Numba (jitted MC loops), jsonschema, pytest
适用任务: Applying OS: Windows (PowerShell). All commands in this repo are run from PowerShell

! 使用限制与门槛

  • 限制说明: ├── schemas/ # topology event stream.schema.json. Edit ONLY for proven gaps (e.g., missing conditionals).
  • 限制说明: These rules are codified in agents/00 repo rules.md. Violating ANY of them requires explicit human approval.
  • 限制说明: schemas/ Edit ONLY if a test proves a real gap (e.g., missing conditionals). Requires version bump.

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作,再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”,而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核,以及是否已经进入工作流落地阶段。

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

topostream_development 是什么?

适用场景: Ideal for AI agents that need topostream development skill. 本地化技能摘要: # topostream Development Skill Project Identity topostream is a physics research artifact: a topology event stream toolkit for 2D XY and q=6 clock spin models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

如何安装 topostream_development?

运行命令:npx killer-skills add ItsReallyDanii/topostream_stage0_specs/topostream_development。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

topostream_development 适用于哪些场景?

典型场景包括:适用任务: Applying topostream Development Skill、适用任务: Applying Tech stack: Python 3.10+, NumPy, SciPy, Numba (jitted MC loops), jsonschema, pytest、适用任务: Applying OS: Windows (PowerShell). All commands in this repo are run from PowerShell。

topostream_development 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

topostream_development 有哪些限制?

限制说明: ├── schemas/ # topology event stream.schema.json. Edit ONLY for proven gaps (e.g., missing conditionals).;限制说明: These rules are codified in agents/00 repo rules.md. Violating ANY of them requires explicit human approval.;限制说明: schemas/ Edit ONLY if a test proves a real gap (e.g., missing conditionals). Requires version bump.。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add ItsReallyDanii/topostream_stage0_specs/topostream_development。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    topostream_development 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

topostream_development

安装 topostream_development,这是一款面向AI agent workflows and automation的 AI Agent Skill。查看评审结论、使用场景与安装路径。

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

topostream Development Skill

1. Project Identity

topostream is a physics research artifact: a topology event stream toolkit for 2D XY and q=6 clock spin models. It extracts vortex / pair / sweep_delta tokens from simulated (and later, adapter-based map-mode) spin fields, with schema validation and reproducibility gates.

Tech stack: Python 3.10+, NumPy, SciPy, Numba (jitted MC loops), jsonschema, pytest.

OS: Windows (PowerShell). All commands in this repo are run from PowerShell.


2. Repo Layout

topostream_stage0_specs/
├── agents/            # Agent handoff contracts (00–06). LOCKED — never edit.
├── docs/              # Normative specs (SPEC_*.md). LOCKED — never edit.
├── schemas/           # topology_event_stream.schema.json. Edit ONLY for proven gaps (e.g., missing conditionals).
├── configs/           # default.yaml — runtime config for CLI reproduce.
├── src/topostream/
│   ├── simulate/      # xy_numba.py, clock6_numba.py — Numba-jitted Metropolis MC.
│   ├── extract/       # vortices.py, pairing.py — vortex extraction + Hungarian pairing.
│   ├── metrics/       # helicity.py, clock.py — Υ, ψ₆, clock6_order, histograms.
│   ├── map/           # forward_models.py, adapters.py — Stage 3 map-mode groundwork.
│   ├── io/            # schema_validate.py — jsonschema validation helper.
│   └── cli.py         # CLI entrypoint (reproduce, sweep, validate, plot).
├── tests/             # Gate tests — one test file per module + cross-cutting suites.
├── scripts/           # physics_sanity_audit.py — diagnostic runner.
├── results/           # Run outputs (gitignored).
├── Makefile           # reproduce, validate, test, clean targets.
└── pyproject.toml     # Build config, deps, pytest config.

3. Hard Rules (Non-Negotiable)

These rules are codified in agents/00_repo_rules.md. Violating ANY of them requires explicit human approval.

3.1 Locked Zones

PathRule
docs/NEVER edit. Normative specs are frozen at Stage 0.
agents/NEVER edit. Agent contracts are locked.
schemas/Edit ONLY if a test proves a real gap (e.g., missing conditionals). Requires version bump.

3.2 Physics Rules

  • The q=6 clock model has THREE phases and TWO BKT transitions (T₂ > T₁). Never conflate QLRO with clock-ordered.
  • Helicity modulus Υ(L,T) is a required metric in every simulation run. Not optional.
  • All angle differences use wrap(Δθ) = arctan2(sin(Δθ), cos(Δθ)). No other wrapping is permitted.
  • Vortex pairing uses Hungarian min-cost matching (scipy.optimize.linear_sum_assignment) only.
  • "Events" are temperature-sweep snapshot deltas, NOT physical time dynamics. Use token_type="sweep_delta".

3.3 CPU Rules

  • All inner MC loops MUST be Numba-jitted (@numba.njit). Pure-Python per-spin update loops are forbidden in src/topostream/simulate/.
  • Job-level parallelism is allowed (one subprocess per seed/temperature).
  • Target: L=64 sweep in < 5 minutes on a 4-core laptop.

3.4 Schema Rules

  • Every output token MUST validate against schemas/topology_event_stream.schema.json.
  • All provenance fields (seed, L, T, sweep_index, schema_version) must be populated.
  • Schema version bumps require updating ALL emitted token versions, config files, and tests.

3.5 Reproducibility Rules

  • All seeds must be explicit integers from the list [42, 43, 44, 45, 46, 47, 48, 49].
  • One-command reproduce: python -m topostream.cli reproduce --config configs/default.yaml
  • No hardcoded paths — all paths from config file.
  • No uuid4() in token IDs — IDs must be deterministic (e.g., v_p_r004_c004).

3.6 Code Quality Rules

  • No print() in library code under src/ — use logging module.
  • Type hints required on all public functions.
  • Every module under src/topostream/ has a corresponding test file in tests/.

4. Owner's Working Style

4.1 Task Structure

The owner gives highly structured, single-objective task prompts with:

  • A HARD RULES section listing what NOT to touch.
  • A TASK section with exact scope (files to create/modify, function signatures, behavior).
  • A DELIVERABLES section ending with STOP — meaning: deliver exactly what's listed, then stop. Don't add unsolicited extras.

4.2 Expectations

  • Read before writing. The owner expects you to read agents/00_repo_rules.md and relevant spec docs BEFORE generating code.
  • Prove, don't claim. Every deliverable includes runnable proof: python -m pytest -q output, git identity, diagnostic snippets.
  • No phantom edits. Don't modify files the task doesn't authorize. If a test reveals a bug in locked code, REPORT it — don't fix it without explicit approval.
  • Commit atomically. Each task = one commit with a descriptive message. The owner does git add . + git commit -m "..." + git push after verifying outputs.
  • Baseline tracking. The owner tracks a baseline test count (e.g., "227 passing"). New tests must ADD to the count, never reduce it. Always report the new total.

4.3 Commit Conventions

  • Prefix: chore:, feat:, or descriptive short phrase.
  • Branch: feature/clock6 (or feature branches per major feature).
  • Tags: v0.1-xy-mvp marks frozen milestones — never touch tagged commits.

4.4 Council-Ready Audit Format

The owner periodically requests "re-audit packets" — structured proof bundles intended to be copy/pasted to other LLMs or reviewers. These always include:

  1. Git identity (rev-parse HEAD, branch, status).
  2. Module existence checks (ls / Test-Path each source file).
  3. Determinism proofs (no uuid4, fixed seeds).
  4. Full pytest -q output.
  5. Diagnostic snippets from scripts/physics_sanity_audit.py.

5. Development Patterns

5.1 Adding a New Module

  1. Create src/topostream/<subpackage>/<module>.py with full docstrings.
  2. Add __init__.py if new subpackage.
  3. Create tests/test_<module>.py with gate tests.
  4. Run python -m pytest -q — full suite must pass.
  5. If the module emits tokens, ensure they validate against the schema.

5.2 Adding a New Metric

  1. Add the function to the appropriate src/topostream/metrics/*.py file.
  2. Do NOT change existing function signatures or behavior.
  3. Create dedicated tests in tests/test_metrics_<name>.py.
  4. Wire the metric into scripts/physics_sanity_audit.py as a new column.
  5. Verify the metric discriminates temperature (shows different values at T=0.3 vs T=2.0).

5.3 Adding a New Simulator

  1. Create src/topostream/simulate/<model>_numba.py.
  2. Public API pattern: init_config_<model>(L, seed), run_<model>(L, T, J, N_equil, N_meas, N_thin, seed).
  3. All inner loops must be @numba.njit.
  4. Return dict with configs, energy_per_spin, helicity, helicity_err.
  5. Create tests/test_sim_<model>.py with physical sanity tests (energy variance, determinism).
  6. Wire into scripts/physics_sanity_audit.py.

5.4 Schema Changes

  1. Write a test in tests/test_schema_conditionals.py (or new file) that proves the gap.
  2. Run the test — confirm it fails.
  3. Patch schemas/topology_event_stream.schema.json.
  4. Bump the "version" field in the schema.
  5. Update ALL "schema_version" strings in: src/, tests/, scripts/, configs/.
  6. Run full suite — all must pass.

5.5 Diagnostic / Audit Scripts

  • Scripts live in scripts/ — they are READ-ONLY consumers of src/ code.
  • They must NEVER modify core simulation code.
  • Output format: console table + JSON in results/diagnostics/.
  • Use logging.ERROR level to suppress simulator thermalization warnings.

6. Testing Conventions

6.1 General

  • Framework: pytest (configured in pyproject.toml, testpaths = ["tests"]).
  • Run: python -m pytest -q (always from repo root).
  • Naming: tests/test_<module>.py, classes Test<Feature>, methods test_<behavior>.

6.2 Fast Parameters

  • Tests use SHORT MC parameters for speed: N_equil=200, N_meas=500, N_thin=50.
  • Never use production-scale parameters in tests (those go in configs/default.yaml).

6.3 Determinism

  • All tests use explicit seeds (typically seed=42).
  • Determinism tests: run the same function twice and assert bitwise equality (use np.array_equal(a, b, equal_nan=True) for arrays that may contain NaN).

6.4 Physical Assertions

  • Use weak, robust assertions for physics tests — tolerances, not exact values.
  • Issue warnings (not failures) for known model behaviors (e.g., Clock6 trapping at low T).
  • Use pytest.warns(UserWarning) for expected warning paths.

6.5 Schema Validation in Tests

  • Use topostream.io.schema_validate.validate_token(token) — it raises on invalid tokens.
  • Positive controls: valid tokens must pass without error.
  • Negative controls: invalid tokens must raise with pytest.raises(Exception).

7. Key Commands

powershell
1# Run all tests 2python -m pytest -q 3 4# Run single test file 5python -m pytest -q tests/test_sim_xy.py 6 7# Run diagnostics 8python scripts/physics_sanity_audit.py 9 10# Full reproduce pipeline 11python -m topostream.cli reproduce --config configs/default.yaml 12 13# Git identity audit 14git rev-parse HEAD; git branch --show-current; git status --short 15 16# Search for version strings 17Get-ChildItem -Recurse -Include *.py src,tests,scripts | Select-String -Pattern '"1.1.0"'

8. Known Gotchas

IssueImpactWorkaround
Clock6 metastability at low TRandom init can trap in antiferromagnetic states → positive energyUse energy variance / config diversity tests, not raw energy ordering
|ψ₆| ≡ 1.0 for Clock6The sixfold order parameter is always 1.0 for discrete clock configsUse compute_clock6_order() (max population fraction) instead
Metropolis sign conventionBoth XY and Clock6 appear to accept uphill moves — existing tests pass anywayDo NOT "fix" without explicit owner approval + new test proving the bug
PowerShell stderr handlingPython logging warnings on stderr cause PowerShell to report exit code 1Set logging to ERROR in scripts, or redirect with 2>$null
NaN propagation in map-modeA single NaN site affects up to 4 vortex plaquettesDocument, don't suppress. Use nanmean in downsampling, weight-normalization in blur
np.array_equal with NaNNaN != NaN by IEEE → determinism tests failUse np.array_equal(a, b, equal_nan=True)

9. Architecture Diagram

mermaid
1graph TD 2 subgraph Simulation 3 XY["simulate/xy_numba.py<br/>run_xy()"] 4 C6["simulate/clock6_numba.py<br/>run_clock6()"] 5 end 6 7 subgraph Extraction 8 VX["extract/vortices.py<br/>extract_vortices()"] 9 PR["extract/pairing.py<br/>pair_vortices()"] 10 end 11 12 subgraph Metrics 13 HE["metrics/helicity.py<br/>compute_helicity()"] 14 CL["metrics/clock.py<br/>compute_psi6()<br/>compute_clock6_order()"] 15 end 16 17 subgraph MapMode["Map Mode (Stage 3)"] 18 FM["map/forward_models.py<br/>to_vector_map()<br/>apply_blur() / add_noise()"] 19 AD["map/adapters.py<br/>vector_map_to_theta()"] 20 end 21 22 subgraph Validation 23 SV["io/schema_validate.py"] 24 SC["schemas/<br/>topology_event_stream<br/>.schema.json"] 25 end 26 27 XY --> VX 28 C6 --> VX 29 VX --> PR 30 XY --> HE 31 C6 --> HE 32 XY --> CL 33 C6 --> CL 34 VX --> SV 35 PR --> SV 36 SV --> SC 37 38 FM --> AD 39 AD --> VX

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