[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D33ZX0ZDBCFP4G7FV7CWJB":3,"skill-same:01M6D33ZX0ZDBCFP4G7FV7CWJB":80},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":46,"commitSha":47,"skillDirectory":48,"forksCount":49,"repositoryHtmlUrl":50,"repositoryHomepageUrl":51,"ownerHtmlUrl":52,"ownerBlogUrl":53,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M6D33ZX0ZDBCFP4G7FV7CWJB","benchmark-agent-review",null,"Review persisted benchmark run outputs with one or more agent graders and report subjective ergonomic quality separately from deterministic benchmark scores","GeorgeQLe\u002Fagentic-skills","GeorgeQLe","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F21134126?v=4","01M6D2JP418S0VGJGF8M93EC3H","George Le","01M6D2JPBAKYD82TA5FS6HKQ3D",1,"MIT","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fagentic-skills-bench\u002Fcodex\u002Fbenchmark-agent-review\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36],"review","benchmark","benchmark agent review","codex","run","report","analysis","skill name","page","quality","v0","alignment","deterministic","2026-11-10 10:12:30",false,"---\nname: benchmark-agent-review\ndescription: Review persisted benchmark run outputs with one or more agent graders and report subjective ergonomic quality separately from deterministic benchmark scores\ntype: analysis\nversion: v0.4\nrequired_conventions: [alignment-page]\nargument-hint: \"\u003Cskill name or run path> [--reviewers codex,claude] [--runs N]\"\n---\n\n# Benchmark Agent Review\n\nInvoke as `$benchmark-agent-review \u003Cskill-or-run-path>`.\n\nUse this skill after `$benchmark-test-skill \u003Cskill>` when the deterministic benchmark in `agentic-skills-benchmarks` passed but the user wants agent judgment on whether the generated artifacts are actually excellent, ergonomic, and useful for the next caller.\n\nAct as a follow-up review workflow. It does not replace hard benchmark assertions, deterministic output-quality rubrics, or verify\u002Fbench commands.\n\nThe primary object of review is the generated skill output, not the benchmark harness. Treat hard assertions and deterministic output-quality scores as context and triage signals only. Lead with whether each retained output is excellent, good, usable, weak, or failing under the agent-review rubric; discuss deterministic rubric tightening only after output-quality findings, and only when it would help future triage surface the same output-quality issue.\n\n## Input\n\n- Required: a benchmark target skill name such as `run`, or a raw run directory in `agentic-skills-benchmarks`, such as `tests\u002Fbenchmarks\u002Fruns\u002Frun-codex-47e0dd54\u002F`.\n- Optional: `--reviewers codex,claude` to request named reviewer families when both outputs are available.\n- Optional: `--runs N` to request multiple independent review passes. Default to 3 when practical; use 1 when only one reviewer pass is available in the active environment.\n\n## Process\n\n1. Resolve benchmark evidence:\n   - Work from `\u002FUsers\u002Fgeorgele\u002Fprojects\u002Ftools\u002Fagentic-skills-benchmarks` (or the user's local benchmark repo checkout). Do not look for benchmark runs in the `agentic-skills` source repo.\n   - If the input is a run directory, inspect that directory.\n   - If the input is a skill name, find the newest matching directories under `tests\u002Fbenchmarks\u002Fruns\u002F\u003Cskill>-*\u002F`.\n   - Prefer the latest Claude and Codex run directories when both exist.\n   - Read `report.md`, `report.json`, each `run-*.json`, and any persisted generated artifact content visible in stdout\u002Fstderr or file snapshots.\n   - If generated artifact content is not fully available, state that limitation and grade only the retained evidence.\n\n2. Extract outputs under review:\n   - Identify the artifact path the benchmark expected, such as `run-plan.md` or `benchmark\u002Ftest-*.md`.\n   - Extract the generated artifact text when available.\n   - Preserve runner identity, run index, hard assertions, deterministic quality score, and infrastructure-blocked status.\n   - Exclude infrastructure-blocked runs from subjective scoring.\n\n3. Build the review packet:\n   - Include the original benchmark prompt.\n   - Include the benchmark fixture facts.\n   - Include the output artifact text or retained summary.\n   - Include hard assertions and deterministic quality scores for context.\n   - Include the target skill contract only when needed to judge ergonomics.\n\n4. Grade each evaluated output with this rubric:\n   - **Task selection clarity**: the selected work is unambiguous and traceable to fixture evidence.\n   - **Implementation specificity**: the output gives a next caller concrete enough steps to act without redoing basic discovery.\n   - **Validation strength**: proposed checks prove behavior or artifact quality, not just file existence or generic completion.\n   - **Scope control**: the output respects the fixture and user constraints without becoming timid or incomplete.\n   - **Next-route ergonomics**: the next command is correct for the runner mode and explains what it will do.\n   - **No invented facts**: the output avoids unsupported services, files, metrics, commands, deploys, or repository claims.\n   - **Residual-risk awareness**: the output names meaningful uncertainty, missing evidence, or follow-up risk when relevant.\n\n5. Score:\n   - Use a 0-100 integer score per reviewed output.\n   - Treat 90-100 as excellent, 80-89 as good, 70-79 as usable but meaningfully incomplete, 60-69 as weak, and below 60 as failing human review.\n   - When multiple review passes are available, report median score, score range, and common findings.\n   - Do not blend subjective scores into hard assertion pass rate or deterministic quality score.\n\n6. Optional multi-reviewer handling:\n   - Use subagents only when the active Codex tool instructions permit them and the user explicitly requested multiple agent review passes.\n   - Assign each reviewer one independent grading pass over the same review packet.\n   - Do not let reviewers edit repository files.\n   - Synthesize reviewer findings into a normalized score table.\n\n7. Write the report:\n   - Create `benchmark\u002Freview-\u003CSKILL>-\u003CYYYY-MM-DD>.md` in `agentic-skills-benchmarks` when the input resolves to a skill.\n   - Create `benchmark\u002Freview-\u003CRUN-DIR-NAME>-\u003CYYYY-MM-DD>.md` in `agentic-skills-benchmarks` when the input is one run directory.\n   - If the review is exploratory and the user asks for chat-only output, do not write a file.\n\n8. Build the remediation handoff:\n   - Convert every material weakness into a remediation target instead of stopping at broad advice.\n   - Classify each target as target-skill contract, benchmark rubric, retained-evidence gap, harness\u002Fsetup issue, or one-off run behavior.\n   - Name the exact owner file, skill contract, benchmark setup, or report artifact when known; when the exact file is not proven, name the narrowest known owner surface and state the lookup needed to confirm it.\n   - Propose the exact contract, rubric, fixture, or evidence-capture behavior to add or tighten; avoid vague changes such as \"update the skill\" without naming the behavior that changes.\n   - Include the validation command or contract-lint assertion that would prove the issue is fixed; a focused fixture rerun is acceptable only when it names the expected assertion or artifact-quality behavior.\n   - When retained artifact text contains placeholder risk, monitoring, validation, or known-unknown sections such as `Not captured`, `Not specified`, `TBD`, `None`, or `N\u002FA`, the remediation must identify the owner target that should reject or repair that placeholder and the validation check that would fail before the fix.\n   - Choose one definitive next route from the highest-impact verified remediation; do not leave the next caller to choose among generic options.\n\n## Output\n\nReport:\n\n- Source benchmark report paths.\n- Reviewed run directories and run indexes.\n- Hard assertion pass rate and deterministic output-quality score from the benchmark report.\n- Output-quality verdict against the agent-review rubric, explicitly focused on the generated skill artifacts rather than the benchmark's ease or strictness.\n- Agent-review score table with reviewer, runner, run index, score, and grade band.\n- Median subjective score and score range when multiple scores exist.\n- Common strengths.\n- Common weaknesses.\n- Remediation table with finding, classification, owner target, proposed change, validation check, and route.\n- Remediation rows must be implementation-ready: each material finding needs a concrete owner target, a proposed behavior change, and a validation check or command. Broad rows like \"tighten the rubric\" or \"update the skill\" are incomplete unless they also name the owning file\u002Fsurface, exact behavior, and proof.\n- Optional deterministic-rubric notes only when the retained output-quality findings show the deterministic rubric failed to surface a meaningful issue or produced misleading context.\n- **Next work:** the one definitive remediation selected from the remediation table, or no follow-up when all evaluated outputs are excellent and no meaningful issue remains.\n- **Recommended next command:** one command derived from that remediation, usually `$session-triage \u003Cskill> \u003Cspecific output-quality gap>`, `$session-triage \u003Cbenchmark setup or reviewed skill> \u003Cspecific rubric gap>`, `$session-triage \u003Cskill> benchmark review`, or `$ship` only when no remediation is needed.\n\n## Alignment Page\n\nFollow the shared alignment-page convention via the packaged convention resolver; output path is `alignment\u002Fbenchmark-agent-review-{topic}.html`. By default, report results inline and write only this skill's normal durable artifacts; create an alignment page only when explicitly requested or when a concrete clarification\u002Freview need cannot be handled cleanly inline.\n\n## Constraints\n\n- Do not re-run `$benchmark-test-skill` unless the requested benchmark artifacts are missing or stale and the user explicitly asks for a fresh benchmark.\n- Do not present subjective agent-review scores as statistically definitive.\n- Do not merge subjective scores into deterministic output-quality scores.\n- Do not frame benchmark pass\u002Ffail laxness as the primary problem when the task is to judge skill output quality. If the benchmark intentionally passes weak-but-compliant outputs, grade the output quality directly and use deterministic-rubric notes only as supporting context.\n- Do not grade infrastructure-blocked runs as skill outputs.\n- Do not fabricate missing artifact content. State when only stdout summaries, assertions, or quality results are available.\n- Do not collapse multiple material weaknesses into a vague handoff such as \"tighten the rubric\"; the remediation table must preserve the responsible target, exact behavior change, and validation check for each issue.\n- Do not create or modify GitHub Actions workflows.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n","# Benchmark Agent Review\n\nInvoke as `$benchmark-agent-review \u003Cskill-or-run-path>`.\n\nUse this skill after `$benchmark-test-skill \u003Cskill>` when the deterministic benchmark in `agentic-skills-benchmarks` passed but the user wants agent judgment on whether the generated artifacts are actually excellent, ergonomic, and useful for the next caller.\n\nAct as a follow-up review workflow. It does not replace hard benchmark assertions, deterministic output-quality rubrics, or verify\u002Fbench commands.\n\nThe primary object of review is the generated skill output, not the benchmark harness. Treat hard assertions and deterministic output-quality scores as context and triage signals only. Lead with whether each retained output is excellent, good, usable, weak, or failing under the agent-review rubric; discuss deterministic rubric tightening only after output-quality findings, and only when it would help future triage surface the same output-quality issue.\n\n## Input\n\n- Required: a benchmark target skill name such as `run`, or a raw run directory in `agentic-skills-benchmarks`, such as `tests\u002Fbenchmarks\u002Fruns\u002Frun-codex-47e0dd54\u002F`.\n- Optional: `--reviewers codex,claude` to request named reviewer families when both outputs are available.\n- Optional: `--runs N` to request multiple independent review passes. Default to 3 when practical; use 1 when only one reviewer pass is available in the active environment.\n\n## Process\n\n1. Resolve benchmark evidence:\n   - Work from `\u002FUsers\u002Fgeorgele\u002Fprojects\u002Ftools\u002Fagentic-skills-benchmarks` (or the user's local benchmark repo checkout). Do not look for benchmark runs in the `agentic-skills` source repo.\n   - If the input is a run directory, inspect that directory.\n   - If the input is a skill name, find the newest matching directories under `tests\u002Fbenchmarks\u002Fruns\u002F\u003Cskill>-*\u002F`.\n   - Prefer the latest Claude and Codex run directories when both exist.\n   - Read `report.md`, `report.json`, each `run-*.json`, and any persisted generated artifact content visible in stdout\u002Fstderr or file snapshots.\n   - If generated artifact content is not fully available, state that limitation and grade only the retained evidence.\n\n2. Extract outputs under review:\n   - Identify the artifact path the benchmark expected, such as `run-plan.md` or `benchmark\u002Ftest-*.md`.\n   - Extract the generated artifact text when available.\n   - Preserve runner identity, run index, hard assertions, deterministic quality score, and infrastructure-blocked status.\n   - Exclude infrastructure-blocked runs from subjective scoring.\n\n3. Build the review packet:\n   - Include the original benchmark prompt.\n   - Include the benchmark fixture facts.\n   - Include the output artifact text or retained summary.\n   - Include hard assertions and deterministic quality scores for context.\n   - Include the target skill contract only when needed to judge ergonomics.\n\n4. Grade each evaluated output with this rubric:\n   - **Task selection clarity**: the selected work is unambiguous and traceable to fixture evidence.\n   - **Implementation specificity**: the output gives a next caller concrete enough steps to act without redoing basic discovery.\n   - **Validation strength**: proposed checks prove behavior or artifact quality, not just file existence or generic completion.\n   - **Scope control**: the output respects the fixture and user constraints without becoming timid or incomplete.\n   - **Next-route ergonomics**: the next command is correct for the runner mode and explains what it will do.\n   - **No invented facts**: the output avoids unsupported services, files, metrics, commands, deploys, or repository claims.\n   - **Residual-risk awareness**: the output names meaningful uncertainty, missing evidence, or follow-up risk when relevant.\n\n5. Score:\n   - Use a 0-100 integer score per reviewed output.\n   - Treat 90-100 as excellent, 80-89 as good, 70-79 as usable but meaningfully incomplete, 60-69 as weak, and below 60 as failing human review.\n   - When multiple review passes are available, report median score, score range, and common findings.\n   - Do not blend subjective scores into hard assertion pass rate or deterministic quality score.\n\n6. Optional multi-reviewer handling:\n   - Use subagents only when the active Codex tool instructions permit them and the user explicitly requested multiple agent review passes.\n   - Assign each reviewer one independent grading pass over the same review packet.\n   - Do not let reviewers edit repository files.\n   - Synthesize reviewer findings into a normalized score table.\n\n7. Write the report:\n   - Create `benchmark\u002Freview-\u003CSKILL>-\u003CYYYY-MM-DD>.md` in `agentic-skills-benchmarks` when the input resolves to a skill.\n   - Create `benchmark\u002Freview-\u003CRUN-DIR-NAME>-\u003CYYYY-MM-DD>.md` in `agentic-skills-benchmarks` when the input is one run directory.\n   - If the review is exploratory and the user asks for chat-only output, do not write a file.\n\n8. Build the remediation handoff:\n   - Convert every material weakness into a remediation target instead of stopping at broad advice.\n   - Classify each target as target-skill contract, benchmark rubric, retained-evidence gap, harness\u002Fsetup issue, or one-off run behavior.\n   - Name the exact owner file, skill contract, benchmark setup, or report artifact when known; when the exact file is not proven, name the narrowest known owner surface and state the lookup needed to confirm it.\n   - Propose the exact contract, rubric, fixture, or evidence-capture behavior to add or tighten; avoid vague changes such as \"update the skill\" without naming the behavior that changes.\n   - Include the validation command or contract-lint assertion that would prove the issue is fixed; a focused fixture rerun is acceptable only when it names the expected assertion or artifact-quality behavior.\n   - When retained artifact text contains placeholder risk, monitoring, validation, or known-unknown sections such as `Not captured`, `Not specified`, `TBD`, `None`, or `N\u002FA`, the remediation must identify the owner target that should reject or repair that placeholder and the validation check that would fail before the fix.\n   - Choose one definitive next route from the highest-impact verified remediation; do not leave the next caller to choose among generic options.\n\n## Output\n\nReport:\n\n- Source benchmark report paths.\n- Reviewed run directories and run indexes.\n- Hard assertion pass rate and deterministic output-quality score from the benchmark report.\n- Output-quality verdict against the agent-review rubric, explicitly focused on the generated skill artifacts rather than the benchmark's ease or strictness.\n- Agent-review score table with reviewer, runner, run index, score, and grade band.\n- Median subjective score and score range when multiple scores exist.\n- Common strengths.\n- Common weaknesses.\n- Remediation table with finding, classification, owner target, proposed change, validation check, and route.\n- Remediation rows must be implementation-ready: each material finding needs a concrete owner target, a proposed behavior change, and a validation check or command. Broad rows like \"tighten the rubric\" or \"update the skill\" are incomplete unless they also name the owning file\u002Fsurface, exact behavior, and proof.\n- Optional deterministic-rubric notes only when the retained output-quality findings show the deterministic rubric failed to surface a meaningful issue or produced misleading context.\n- **Next work:** the one definitive remediation selected from the remediation table, or no follow-up when all evaluated outputs are excellent and no meaningful issue remains.\n- **Recommended next command:** one command derived from that remediation, usually `$session-triage \u003Cskill> \u003Cspecific output-quality gap>`, `$session-triage \u003Cbenchmark setup or reviewed skill> \u003Cspecific rubric gap>`, `$session-triage \u003Cskill> benchmark review`, or `$ship` only when no remediation is needed.\n\n## Alignment Page\n\nFollow the shared alignment-page convention via the packaged convention resolver; output path is `alignment\u002Fbenchmark-agent-review-{topic}.html`. By default, report results inline and write only this skill's normal durable artifacts; create an alignment page only when explicitly requested or when a concrete clarification\u002Freview need cannot be handled cleanly inline.\n\n## Constraints\n\n- Do not re-run `$benchmark-test-skill` unless the requested benchmark artifacts are missing or stale and the user explicitly asks for a fresh benchmark.\n- Do not present subjective agent-review scores as statistically definitive.\n- Do not merge subjective scores into deterministic output-quality scores.\n- Do not frame benchmark pass\u002Ffail laxness as the primary problem when the task is to judge skill output quality. If the benchmark intentionally passes weak-but-compliant outputs, grade the output quality directly and use deterministic-rubric notes only as supporting context.\n- Do not grade infrastructure-blocked runs as skill outputs.\n- Do not fabricate missing artifact content. State when only stdout summaries, assertions, or quality results are available.\n- Do not collapse multiple material weaknesses into a vague handoff such as \"tighten the rubric\"; the remediation table must preserve the responsible target, exact behavior change, and validation check for each issue.\n- Do not create or modify GitHub Actions workflows.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n",{"name":5,"type":30,"version":42,"description":7,"argument-hint":43,"required_conventions":44},"v0.4","\u003Cskill name or run path> [--reviewers codex,claude] [--runs N]",[45],"alignment-page","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fagentic-skills-bench\u002Fcodex\u002Fbenchmark-agent-review",0,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills","https:\u002F\u002Fagentic-skills-blush.vercel.app","https:\u002F\u002Fgithub.com\u002FGeorgeQLe","georgeqle.com","George Le is a futurist and serial tech entrepreneur who wants to work toward a world where humanity is free from robotic tasks.","2026-11-10 04:07:24",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill benchmark-agent-review",{"tool":62,"command":63},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill benchmark-agent-review",{"tool":65,"command":66},"pnpm","pnpm dlx skills add GeorgeQLe\u002Fagentic-skills --skill benchmark-agent-review","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fagentic-skills-bench\u002Fcodex\u002Fbenchmark-agent-review\u002FSKILL.md",true,[70,76],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"ALIGNMENT-PAGE.md","REFERENCE","参考文档",53638,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fagentic-skills-bench\u002Fcodex\u002Fbenchmark-agent-review\u002FALIGNMENT-PAGE.md",{"path":77,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":78,"sourceHtmlUrl":79},"CHANGELOG.md",817,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fagentic-skills-bench\u002Fcodex\u002Fbenchmark-agent-review\u002FCHANGELOG.md",[81,93,103,114,125,136],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":37},"01M6G0NJES15RJKZE6YZ0TSYGF","source-checkout-allowed","Valid source-checkout-only fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fsource-checkout-allowed\u002FSKILL.md",[],[88,89,90,91,34,92],"source checkout allowed","checkout","fixture","only","valid",{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":37},"01M6G0NFZ3R1MNB1E3DVTM0WB7","deck-install-valid","Valid deck install fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fdeck-install\u002FSKILL.md",[],[100,101,102,92,90,34],"deck install valid","deck","install",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":109,"publishedAt":37},"01M6G0ND3QZQC4MDZ9NVB97PT2","codex-pack-guard-valid","Valid Codex Pack Availability Guard fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-pack-guard\u002FSKILL.md",[],[110,111,112,92,27,113,90,34],"codex pack guard valid","pack","guard","availability",{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":118,"categories":119,"keywords":121,"publishedAt":37},"01M6G0NA9YB3NKGZKD3S96JMNB","codex-missing-skill-valid","Valid Codex missing skill fallback fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-missing-skill-fallback\u002FSKILL.md",[120],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[122,123,92,27,34,124,90],"codex missing skill valid","missing","fallback",{"skillNo":126,"name":127,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":129,"categories":130,"keywords":132,"publishedAt":37},"01M6G0N7PC0EKFD40ZWQAXSAQ9","codex-base-skill-fallback-valid","Valid Codex base skill fallback fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-base-skill-fallback\u002FSKILL.md",[131],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[92,27,124,133,134,135,34,90],"base skill","codex base skill fallback valid","base",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":142,"publishedAt":37},"01M6G0N4VRR2YKZQ6N3Y6S2BQA","claude-pack-guard-valid","Valid Claude Pack Availability Guard fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fclaude-pack-guard\u002FSKILL.md",[],[92,112,111,143,113,34,90],"claude pack guard valid"]