[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M78TSHDZVRFH4ZQ5SDRD3JBH":3,"skill-same:01M78TSHDZVRFH4ZQ5SDRD3JBH":67},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":18,"linkOnly":19,"markdownContent":20,"markdownBody":21,"frontMatter":22,"refName":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":33,"install":34,"resources":46},"01M78TSHDZVRFH4ZQ5SDRD3JBH","core-circuits-and-ops",null,"Build, inspect, mutate, serialize, and debug Cirq circuits and core operation objects.","VectorSpaceLab\u002FAREX-Skill","VectorSpaceLab","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F180637102?v=4","01M7538C5WPSJGWF7KHR4EFZ9F","01M7538C6R2GFP53NPXTCZNBRT",351,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: core-circuits-and-ops\ndescription: \"Build, inspect, mutate, serialize, and debug Cirq circuits and\n  core operation objects.\"\ndisable-model-invocation: true\nmetadata:\n  disco-role: operating\nlicense: Apache 2.0\n---\n\n# Core Circuits and Operations\n\nUse this sub-skill when the task is about Cirq's core object model: qubits\u002Fqids,\ngates, operations, moments, circuits, circuit diagrams, measurement keys, tags,\ncontrols, symbolic parameters, custom gates, and basic object serialization.\n\n## Stay in this sub-skill for\n\n- Choosing or constructing `LineQubit`, `GridQubit`, `NamedQubit`, `LineQid`, or\n  `GridQid` objects.\n- Building and mutating `Gate`, `Operation`, `Moment`, `Circuit`,\n  `FrozenCircuit`, and `CircuitOperation` objects.\n- Using `Circuit.append`, `Circuit.insert`, `InsertStrategy`, OP trees,\n  `findall_operations`, measurement keys, operation tags, controls, and\n  classically controlled operations.\n- Resolving symbolic parameters with `ParamResolver` and `resolve_parameters`.\n- Using core protocols such as `unitary`, `has_unitary`, `decompose`, `inverse`,\n  `qid_shape`, and `circuit_diagram_info` for debugging custom or built-in\n  objects.\n- Basic JSON, QASM, and Quirk interop at the circuit-object level.\n\n## Route away when\n\n- The user needs sampling, state vectors, density matrices, result histograms,\n  parameter sweeps as execution, or noise simulation: use\n  `simulation-study-and-noise`.\n- The user needs circuit transformers, optimization, decomposition pipelines,\n  routing, target gatesets, or placement: use `transformers-and-compilation`.\n- The user needs cloud\u002Fhardware provider serializers, live services, credentials,\n  or provider-specific package behavior: use `hardware-providers-and-serialization`.\n- The user needs algorithm recipes, Pauli observables, expectation values, or\n  textbook algorithm interpretation: use `algorithms-and-observables`.\n\n## Operating routine\n\n1. Identify whether the task is object construction, mutation, inspection,\n   parameters, protocols, or interop.\n2. For exact signatures and object-model facts, read\n   [references\u002Fapi-reference.md](references\u002Fapi-reference.md).\n3. For common build\u002Fdebug recipes, read\n   [references\u002Fworkflows.md](references\u002Fworkflows.md).\n4. For known failure modes, read\n   [references\u002Ftroubleshooting.md](references\u002Ftroubleshooting.md).\n5. For a safe local smoke helper, run\n   [scripts\u002Finspect_circuit.py](scripts\u002Finspect_circuit.py) with `--help`, then\n   run it with optional `--json` or `--qubits N`.\n\n## Bundled assets\n\n- [references\u002Fapi-reference.md](references\u002Fapi-reference.md) — verified public\n  API signatures and compact examples for core Cirq objects.\n- [references\u002Fworkflows.md](references\u002Fworkflows.md) — task-oriented recipes for\n  construction, mutation, parameter resolution, custom gates, and interop.\n- [references\u002Ftroubleshooting.md](references\u002Ftroubleshooting.md) — symptom-based\n  fixes for unresolved parameters, duplicate measurement keys, protocol failures,\n  qid-shape mismatches, JSON resolver issues, QASM limits, and insert strategy\n  surprises.\n- [scripts\u002Finspect_circuit.py](scripts\u002Finspect_circuit.py) — deterministic helper\n  that builds a small parameterized circuit, prints diagrams, validates\n  measurement-key uniqueness, and optionally performs a JSON roundtrip.\n","# Core Circuits and Operations\n\nUse this sub-skill when the task is about Cirq's core object model: qubits\u002Fqids,\ngates, operations, moments, circuits, circuit diagrams, measurement keys, tags,\ncontrols, symbolic parameters, custom gates, and basic object serialization.\n\n## Stay in this sub-skill for\n\n- Choosing or constructing `LineQubit`, `GridQubit`, `NamedQubit`, `LineQid`, or\n  `GridQid` objects.\n- Building and mutating `Gate`, `Operation`, `Moment`, `Circuit`,\n  `FrozenCircuit`, and `CircuitOperation` objects.\n- Using `Circuit.append`, `Circuit.insert`, `InsertStrategy`, OP trees,\n  `findall_operations`, measurement keys, operation tags, controls, and\n  classically controlled operations.\n- Resolving symbolic parameters with `ParamResolver` and `resolve_parameters`.\n- Using core protocols such as `unitary`, `has_unitary`, `decompose`, `inverse`,\n  `qid_shape`, and `circuit_diagram_info` for debugging custom or built-in\n  objects.\n- Basic JSON, QASM, and Quirk interop at the circuit-object level.\n\n## Route away when\n\n- The user needs sampling, state vectors, density matrices, result histograms,\n  parameter sweeps as execution, or noise simulation: use\n  `simulation-study-and-noise`.\n- The user needs circuit transformers, optimization, decomposition pipelines,\n  routing, target gatesets, or placement: use `transformers-and-compilation`.\n- The user needs cloud\u002Fhardware provider serializers, live services, credentials,\n  or provider-specific package behavior: use `hardware-providers-and-serialization`.\n- The user needs algorithm recipes, Pauli observables, expectation values, or\n  textbook algorithm interpretation: use `algorithms-and-observables`.\n\n## Operating routine\n\n1. Identify whether the task is object construction, mutation, inspection,\n   parameters, protocols, or interop.\n2. For exact signatures and object-model facts, read\n   [references\u002Fapi-reference.md](references\u002Fapi-reference.md).\n3. For common build\u002Fdebug recipes, read\n   [references\u002Fworkflows.md](references\u002Fworkflows.md).\n4. For known failure modes, read\n   [references\u002Ftroubleshooting.md](references\u002Ftroubleshooting.md).\n5. For a safe local smoke helper, run\n   [scripts\u002Finspect_circuit.py](scripts\u002Finspect_circuit.py) with `--help`, then\n   run it with optional `--json` or `--qubits N`.\n\n## Bundled assets\n\n- [references\u002Fapi-reference.md](references\u002Fapi-reference.md) — verified public\n  API signatures and compact examples for core Cirq objects.\n- [references\u002Fworkflows.md](references\u002Fworkflows.md) — task-oriented recipes for\n  construction, mutation, parameter resolution, custom gates, and interop.\n- [references\u002Ftroubleshooting.md](references\u002Ftroubleshooting.md) — symptom-based\n  fixes for unresolved parameters, duplicate measurement keys, protocol failures,\n  qid-shape mismatches, JSON resolver issues, QASM limits, and insert strategy\n  surprises.\n- [scripts\u002Finspect_circuit.py](scripts\u002Finspect_circuit.py) — deterministic helper\n  that builds a small parameterized circuit, prints diagrams, validates\n  measurement-key uniqueness, and optionally performs a JSON roundtrip.\n",{"name":5,"license":23,"metadata":24,"description":7,"disable-model-invocation":26},"Apache 2.0",{"disco-role":25},"operating",true,"main","ac3fe1afa80fb9a09775ecfb2b6cc3ba850a2db6","skills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops",27,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab","2026-09-03 10:25:21",{"source":8,"skillName":5,"commands":35,"prompt":45,"zipAvailable":26},[36,39,42],{"tool":37,"command":38},"npx","npx skills add VectorSpaceLab\u002FAREX-Skill --skill core-circuits-and-ops",{"tool":40,"command":41},"bunx","bunx skills add VectorSpaceLab\u002FAREX-Skill --skill core-circuits-and-ops",{"tool":43,"command":44},"pnpm","pnpm dlx skills add VectorSpaceLab\u002FAREX-Skill --skill core-circuits-and-ops","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002FSKILL.md",[47,53,57,61],{"path":48,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":51,"sourceHtmlUrl":52},"references\u002Fapi-reference.md","REFERENCE","参考文档",10597,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002Freferences\u002Fapi-reference.md",{"path":54,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":55,"sourceHtmlUrl":56},"references\u002Ftroubleshooting.md",6198,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002Freferences\u002Ftroubleshooting.md",{"path":58,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":59,"sourceHtmlUrl":60},"references\u002Fworkflows.md",6315,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002Freferences\u002Fworkflows.md",{"path":62,"resourceType":63,"resourceTypeDesc":64,"sizeBytes":65,"sourceHtmlUrl":66},"scripts\u002Finspect_circuit.py","SCRIPT","脚本",4547,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fcirq\u002Fsub-skills\u002Fcore-circuits-and-ops\u002Fscripts\u002Finspect_circuit.py",[68,75,82,89,96,103],{"skillNo":69,"name":70,"nameZh":6,"description":71,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":72,"categories":73,"keywords":74,"publishedAt":18},"01M799NYSH1R3RVAHSM2D88Y84","passnet-triton-opt","Make a single PassNet Triton kernel fast AND numerically faithful: performance model (when a replacement can win at all), block\u002Fgrid\u002Fwarp 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.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-triton-opt\u002FSKILL.md",[],[],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":81,"publishedAt":18},"01M799NS5APEC0N1FZ7XZVW6BN","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.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-solve\u002FSKILL.md",[],[],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":86,"categories":87,"keywords":88,"publishedAt":18},"01M799NNY9BKSM21V5R7QVTBJX","passnet-skill","PassNet GPU kernel optimization via compiler passes. Design and implement Triton-based optimization passes, create pass files under .\u002Fpass_dir\u002F, self-evaluate with pass_evaluator, and iterate to maximize GPU speedup.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-skill\u002FSKILL.md",[],[],{"skillNo":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":93,"categories":94,"keywords":95,"publishedAt":18},"01M799NHH6NP7Z1RK77KGXAN6S","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()\u002Freplacement_args()\u002Freplacement_func() files, when a pass \"failed to match\", or when deciding how to fuse multiple kernels\u002Fops.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-pattern-fusion\u002FSKILL.md",[],[],{"skillNo":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":102,"publishedAt":18},"01M799ND2J4WNC2PGAZ0A06NDF","passnet-orchestrate","Round\u002Fbatch planning and decision support for PassNet graph optimization. Use for multi-sample triage, worker allocation, eval-budget policy, and post-eval keep\u002Frevert 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.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-orchestrate\u002FSKILL.md",[],[],{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":109,"publishedAt":18},"01M799N8SBTMY02ZDG2AZF5ZWE","passnet-feedback","Fast, deterministic feedback for PassNet work: pre-flight pattern\u002Fmatch 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).","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-feedback\u002FSKILL.md",[],[]]