[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M74FTXEJG4CTVJSJQX132PBY":3,"skill-same:01M74FTXEJG4CTVJSJQX132PBY":71},{"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":41,"commitSha":42,"skillDirectory":43,"forksCount":13,"repositoryHtmlUrl":44,"repositoryHomepageUrl":6,"ownerHtmlUrl":45,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":46,"install":47,"resources":60},"01M74FTXEJG4CTVJSJQX132PBY","subagent-driven-development",null,"Execute plans via delegate_task subagents (2-stage review).","lzy18001500226\u002FMoSim","lzy18001500226","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F152623587?v=4","01M71ZMEX36NK05B642131DEEK","01M71ZMEXSMX72KPVNJ572G0CM",0,"MIT","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FPlatforms\u002Fhermes-agent\u002Fskills\u002Fsoftware-development\u002Fsubagent-driven-development\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: subagent-driven-development\ndescription: \"Execute plans via delegate_task subagents (2-stage review).\"\nversion: 1.1.0\nauthor: Hermes Agent (adapted from obra\u002Fsuperpowers)\nlicense: MIT\nplatforms: [linux, macos, windows]\nmetadata:\n  hermes:\n    tags: [delegation, subagent, implementation, workflow, parallel]\n    related_skills: [writing-plans, requesting-code-review, test-driven-development]\n---\n\n# Subagent-Driven Development\n\n## Overview\n\nExecute implementation plans by dispatching fresh subagents per task with systematic two-stage review.\n\n**Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.\n\n## When to Use\n\nUse this skill when:\n- You have an implementation plan (from writing-plans skill or user requirements)\n- Tasks are mostly independent\n- Quality and spec compliance are important\n- You want automated review between tasks\n\n**vs. manual execution:**\n- Fresh context per task (no confusion from accumulated state)\n- Automated review process catches issues early\n- Consistent quality checks across all tasks\n- Subagents can ask questions before starting work\n\n## The Process\n\n### 1. Read and Parse Plan\n\nRead the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:\n\n```python\n# Read the plan\nread_file(\"docs\u002Fplans\u002Ffeature-plan.md\")\n\n# Create todo list with all tasks\ntodo([\n    {\"id\": \"task-1\", \"content\": \"Create User model with email field\", \"status\": \"pending\"},\n    {\"id\": \"task-2\", \"content\": \"Add password hashing utility\", \"status\": \"pending\"},\n    {\"id\": \"task-3\", \"content\": \"Create login endpoint\", \"status\": \"pending\"},\n])\n```\n\n**Key:** Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.\n\n### 2. Per-Task Workflow\n\nFor EACH task in the plan:\n\n#### Step 1: Dispatch Implementer Subagent\n\nUse `delegate_task` with complete context:\n\n```python\ndelegate_task(\n    goal=\"Implement Task 1: Create User model with email and password_hash fields\",\n    context=\"\"\"\n    TASK FROM PLAN:\n    - Create: src\u002Fmodels\u002Fuser.py\n    - Add User class with email (str) and password_hash (str) fields\n    - Use bcrypt for password hashing\n    - Include __repr__ for debugging\n\n    FOLLOW TDD:\n    1. Write failing test in tests\u002Fmodels\u002Ftest_user.py\n    2. Run: pytest tests\u002Fmodels\u002Ftest_user.py -v (verify FAIL)\n    3. Write minimal implementation\n    4. Run: pytest tests\u002Fmodels\u002Ftest_user.py -v (verify PASS)\n    5. Run: pytest tests\u002F -q (verify no regressions)\n    6. Commit: git add -A && git commit -m \"feat: add User model with password hashing\"\n\n    PROJECT CONTEXT:\n    - Python 3.11, Flask app in src\u002Fapp.py\n    - Existing models in src\u002Fmodels\u002F\n    - Tests use pytest, run from project root\n    - bcrypt already in requirements.txt\n    \"\"\",\n    toolsets=['terminal', 'file']\n)\n```\n\n#### Step 2: Dispatch Spec Compliance Reviewer\n\nAfter the implementer completes, verify against the original spec:\n\n```python\ndelegate_task(\n    goal=\"Review if implementation matches the spec from the plan\",\n    context=\"\"\"\n    ORIGINAL TASK SPEC:\n    - Create src\u002Fmodels\u002Fuser.py with User class\n    - Fields: email (str), password_hash (str)\n    - Use bcrypt for password hashing\n    - Include __repr__\n\n    CHECK:\n    - [ ] All requirements from spec implemented?\n    - [ ] File paths match spec?\n    - [ ] Function signatures match spec?\n    - [ ] Behavior matches expected?\n    - [ ] Nothing extra added (no scope creep)?\n\n    OUTPUT: PASS or list of specific spec gaps to fix.\n    \"\"\",\n    toolsets=['file']\n)\n```\n\n**If spec issues found:** Fix gaps, then re-run spec review. Continue only when spec-compliant.\n\n#### Step 3: Dispatch Code Quality Reviewer\n\nAfter spec compliance passes:\n\n```python\ndelegate_task(\n    goal=\"Review code quality for Task 1 implementation\",\n    context=\"\"\"\n    FILES TO REVIEW:\n    - src\u002Fmodels\u002Fuser.py\n    - tests\u002Fmodels\u002Ftest_user.py\n\n    CHECK:\n    - [ ] Follows project conventions and style?\n    - [ ] Proper error handling?\n    - [ ] Clear variable\u002Ffunction names?\n    - [ ] Adequate test coverage?\n    - [ ] No obvious bugs or missed edge cases?\n    - [ ] No security issues?\n\n    OUTPUT FORMAT:\n    - Critical Issues: [must fix before proceeding]\n    - Important Issues: [should fix]\n    - Minor Issues: [optional]\n    - Verdict: APPROVED or REQUEST_CHANGES\n    \"\"\",\n    toolsets=['file']\n)\n```\n\n**If quality issues found:** Fix issues, re-review. Continue only when approved.\n\n#### Step 4: Mark Complete\n\n```python\ntodo([{\"id\": \"task-1\", \"content\": \"Create User model with email field\", \"status\": \"completed\"}], merge=True)\n```\n\n### 3. Final Review\n\nAfter ALL tasks are complete, dispatch a final integration reviewer:\n\n```python\ndelegate_task(\n    goal=\"Review the entire implementation for consistency and integration issues\",\n    context=\"\"\"\n    All tasks from the plan are complete. Review the full implementation:\n    - Do all components work together?\n    - Any inconsistencies between tasks?\n    - All tests passing?\n    - Ready for merge?\n    \"\"\",\n    toolsets=['terminal', 'file']\n)\n```\n\n### 4. Verify and Commit\n\n```bash\n# Run full test suite\npytest tests\u002F -q\n\n# Review all changes\ngit diff --stat\n\n# Final commit if needed\ngit add -A && git commit -m \"feat: complete [feature name] implementation\"\n```\n\n## Task Granularity\n\n**Each task = 2-5 minutes of focused work.**\n\n**Too big:**\n- \"Implement user authentication system\"\n\n**Right size:**\n- \"Create User model with email and password fields\"\n- \"Add password hashing function\"\n- \"Create login endpoint\"\n- \"Add JWT token generation\"\n- \"Create registration endpoint\"\n\n## Red Flags — Never Do These\n\n- Start implementation without a plan\n- Skip reviews (spec compliance OR code quality)\n- Proceed with unfixed critical\u002Fimportant issues\n- Dispatch multiple implementation subagents for tasks that touch the same files\n- Make subagent read the plan file (provide full text in context instead)\n- Skip scene-setting context (subagent needs to understand where the task fits)\n- Ignore subagent questions (answer before letting them proceed)\n- Accept \"close enough\" on spec compliance\n- Skip review loops (reviewer found issues → implementer fixes → review again)\n- Let implementer self-review replace actual review (both are needed)\n- **Start code quality review before spec compliance is PASS** (wrong order)\n- Move to next task while either review has open issues\n\n## Handling Issues\n\n### If Subagent Asks Questions\n\n- Answer clearly and completely\n- Provide additional context if needed\n- Don't rush them into implementation\n\n### If Reviewer Finds Issues\n\n- Implementer subagent (or a new one) fixes them\n- Reviewer reviews again\n- Repeat until approved\n- Don't skip the re-review\n\n### If Subagent Fails a Task\n\n- Dispatch a new fix subagent with specific instructions about what went wrong\n- Don't try to fix manually in the controller session (context pollution)\n\n## Efficiency Notes\n\n**Why fresh subagent per task:**\n- Prevents context pollution from accumulated state\n- Each subagent gets clean, focused context\n- No confusion from prior tasks' code or reasoning\n\n**Why two-stage review:**\n- Spec review catches under\u002Fover-building early\n- Quality review ensures the implementation is well-built\n- Catches issues before they compound across tasks\n\n**Cost trade-off:**\n- More subagent invocations (implementer + 2 reviewers per task)\n- But catches issues early (cheaper than debugging compounded problems later)\n\n## Integration with Other Skills\n\n### With writing-plans\n\nThis skill EXECUTES plans created by the writing-plans skill:\n1. User requirements → writing-plans → implementation plan\n2. Implementation plan → subagent-driven-development → working code\n\n### With test-driven-development\n\nImplementer subagents should follow TDD:\n1. Write failing test first\n2. Implement minimal code\n3. Verify test passes\n4. Commit\n\nInclude TDD instructions in every implementer context.\n\n### With requesting-code-review\n\nThe two-stage review process IS the code review. For final integration review, use the requesting-code-review skill's review dimensions.\n\n### With systematic-debugging\n\nIf a subagent encounters bugs during implementation:\n1. Follow systematic-debugging process\n2. Find root cause before fixing\n3. Write regression test\n4. Resume implementation\n\n## Example Workflow\n\n```\n[Read plan: docs\u002Fplans\u002Fauth-feature.md]\n[Create todo list with 5 tasks]\n\n--- Task 1: Create User model ---\n[Dispatch implementer subagent]\n  Implementer: \"Should email be unique?\"\n  You: \"Yes, email must be unique\"\n  Implementer: Implemented, 3\u002F3 tests passing, committed.\n\n[Dispatch spec reviewer]\n  Spec reviewer: ✅ PASS — all requirements met\n\n[Dispatch quality reviewer]\n  Quality reviewer: ✅ APPROVED — clean code, good tests\n\n[Mark Task 1 complete]\n\n--- Task 2: Password hashing ---\n[Dispatch implementer subagent]\n  Implementer: No questions, implemented, 5\u002F5 tests passing.\n\n[Dispatch spec reviewer]\n  Spec reviewer: ❌ Missing: password strength validation (spec says \"min 8 chars\")\n\n[Implementer fixes]\n  Implementer: Added validation, 7\u002F7 tests passing.\n\n[Dispatch spec reviewer again]\n  Spec reviewer: ✅ PASS\n\n[Dispatch quality reviewer]\n  Quality reviewer: Important: Magic number 8, extract to constant\n  Implementer: Extracted MIN_PASSWORD_LENGTH constant\n  Quality reviewer: ✅ APPROVED\n\n[Mark Task 2 complete]\n\n... (continue for all tasks)\n\n[After all tasks: dispatch final integration reviewer]\n[Run full test suite: all passing]\n[Done!]\n```\n\n## Remember\n\n```\nFresh subagent per task\nTwo-stage review every time\nSpec compliance FIRST\nCode quality SECOND\nNever skip reviews\nCatch issues early\n```\n\n**Quality is not an accident. It's the result of systematic process.**\n\n## Further reading (load when relevant)\n\nWhen the orchestration involves significant context usage, long review loops, or complex validation checkpoints, load these references for the specific discipline:\n\n- **`references\u002Fcontext-budget-discipline.md`** — Four-tier context degradation model (PEAK \u002F GOOD \u002F DEGRADING \u002F POOR), read-depth rules that scale with context window size, and early warning signs of silent degradation. Load when a run will clearly consume significant context (multi-phase plans, many subagents, large artifacts).\n- **`references\u002Fgates-taxonomy.md`** — The four canonical gate types (Pre-flight, Revision, Escalation, Abort) with behavior, recovery, and examples. Load when designing or reviewing any workflow that has validation checkpoints — use the vocabulary explicitly so each gate has defined entry, failure behavior, and resumption rules.\n\nBoth references adapted from gsd-build\u002Fget-shit-done (MIT © 2025 Lex Christopherson).\n","# Subagent-Driven Development\n\n## Overview\n\nExecute implementation plans by dispatching fresh subagents per task with systematic two-stage review.\n\n**Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.\n\n## When to Use\n\nUse this skill when:\n- You have an implementation plan (from writing-plans skill or user requirements)\n- Tasks are mostly independent\n- Quality and spec compliance are important\n- You want automated review between tasks\n\n**vs. manual execution:**\n- Fresh context per task (no confusion from accumulated state)\n- Automated review process catches issues early\n- Consistent quality checks across all tasks\n- Subagents can ask questions before starting work\n\n## The Process\n\n### 1. Read and Parse Plan\n\nRead the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:\n\n```python\n# Read the plan\nread_file(\"docs\u002Fplans\u002Ffeature-plan.md\")\n\n# Create todo list with all tasks\ntodo([\n    {\"id\": \"task-1\", \"content\": \"Create User model with email field\", \"status\": \"pending\"},\n    {\"id\": \"task-2\", \"content\": \"Add password hashing utility\", \"status\": \"pending\"},\n    {\"id\": \"task-3\", \"content\": \"Create login endpoint\", \"status\": \"pending\"},\n])\n```\n\n**Key:** Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.\n\n### 2. Per-Task Workflow\n\nFor EACH task in the plan:\n\n#### Step 1: Dispatch Implementer Subagent\n\nUse `delegate_task` with complete context:\n\n```python\ndelegate_task(\n    goal=\"Implement Task 1: Create User model with email and password_hash fields\",\n    context=\"\"\"\n    TASK FROM PLAN:\n    - Create: src\u002Fmodels\u002Fuser.py\n    - Add User class with email (str) and password_hash (str) fields\n    - Use bcrypt for password hashing\n    - Include __repr__ for debugging\n\n    FOLLOW TDD:\n    1. Write failing test in tests\u002Fmodels\u002Ftest_user.py\n    2. Run: pytest tests\u002Fmodels\u002Ftest_user.py -v (verify FAIL)\n    3. Write minimal implementation\n    4. Run: pytest tests\u002Fmodels\u002Ftest_user.py -v (verify PASS)\n    5. Run: pytest tests\u002F -q (verify no regressions)\n    6. Commit: git add -A && git commit -m \"feat: add User model with password hashing\"\n\n    PROJECT CONTEXT:\n    - Python 3.11, Flask app in src\u002Fapp.py\n    - Existing models in src\u002Fmodels\u002F\n    - Tests use pytest, run from project root\n    - bcrypt already in requirements.txt\n    \"\"\",\n    toolsets=['terminal', 'file']\n)\n```\n\n#### Step 2: Dispatch Spec Compliance Reviewer\n\nAfter the implementer completes, verify against the original spec:\n\n```python\ndelegate_task(\n    goal=\"Review if implementation matches the spec from the plan\",\n    context=\"\"\"\n    ORIGINAL TASK SPEC:\n    - Create src\u002Fmodels\u002Fuser.py with User class\n    - Fields: email (str), password_hash (str)\n    - Use bcrypt for password hashing\n    - Include __repr__\n\n    CHECK:\n    - [ ] All requirements from spec implemented?\n    - [ ] File paths match spec?\n    - [ ] Function signatures match spec?\n    - [ ] Behavior matches expected?\n    - [ ] Nothing extra added (no scope creep)?\n\n    OUTPUT: PASS or list of specific spec gaps to fix.\n    \"\"\",\n    toolsets=['file']\n)\n```\n\n**If spec issues found:** Fix gaps, then re-run spec review. Continue only when spec-compliant.\n\n#### Step 3: Dispatch Code Quality Reviewer\n\nAfter spec compliance passes:\n\n```python\ndelegate_task(\n    goal=\"Review code quality for Task 1 implementation\",\n    context=\"\"\"\n    FILES TO REVIEW:\n    - src\u002Fmodels\u002Fuser.py\n    - tests\u002Fmodels\u002Ftest_user.py\n\n    CHECK:\n    - [ ] Follows project conventions and style?\n    - [ ] Proper error handling?\n    - [ ] Clear variable\u002Ffunction names?\n    - [ ] Adequate test coverage?\n    - [ ] No obvious bugs or missed edge cases?\n    - [ ] No security issues?\n\n    OUTPUT FORMAT:\n    - Critical Issues: [must fix before proceeding]\n    - Important Issues: [should fix]\n    - Minor Issues: [optional]\n    - Verdict: APPROVED or REQUEST_CHANGES\n    \"\"\",\n    toolsets=['file']\n)\n```\n\n**If quality issues found:** Fix issues, re-review. Continue only when approved.\n\n#### Step 4: Mark Complete\n\n```python\ntodo([{\"id\": \"task-1\", \"content\": \"Create User model with email field\", \"status\": \"completed\"}], merge=True)\n```\n\n### 3. Final Review\n\nAfter ALL tasks are complete, dispatch a final integration reviewer:\n\n```python\ndelegate_task(\n    goal=\"Review the entire implementation for consistency and integration issues\",\n    context=\"\"\"\n    All tasks from the plan are complete. Review the full implementation:\n    - Do all components work together?\n    - Any inconsistencies between tasks?\n    - All tests passing?\n    - Ready for merge?\n    \"\"\",\n    toolsets=['terminal', 'file']\n)\n```\n\n### 4. Verify and Commit\n\n```bash\n# Run full test suite\npytest tests\u002F -q\n\n# Review all changes\ngit diff --stat\n\n# Final commit if needed\ngit add -A && git commit -m \"feat: complete [feature name] implementation\"\n```\n\n## Task Granularity\n\n**Each task = 2-5 minutes of focused work.**\n\n**Too big:**\n- \"Implement user authentication system\"\n\n**Right size:**\n- \"Create User model with email and password fields\"\n- \"Add password hashing function\"\n- \"Create login endpoint\"\n- \"Add JWT token generation\"\n- \"Create registration endpoint\"\n\n## Red Flags — Never Do These\n\n- Start implementation without a plan\n- Skip reviews (spec compliance OR code quality)\n- Proceed with unfixed critical\u002Fimportant issues\n- Dispatch multiple implementation subagents for tasks that touch the same files\n- Make subagent read the plan file (provide full text in context instead)\n- Skip scene-setting context (subagent needs to understand where the task fits)\n- Ignore subagent questions (answer before letting them proceed)\n- Accept \"close enough\" on spec compliance\n- Skip review loops (reviewer found issues → implementer fixes → review again)\n- Let implementer self-review replace actual review (both are needed)\n- **Start code quality review before spec compliance is PASS** (wrong order)\n- Move to next task while either review has open issues\n\n## Handling Issues\n\n### If Subagent Asks Questions\n\n- Answer clearly and completely\n- Provide additional context if needed\n- Don't rush them into implementation\n\n### If Reviewer Finds Issues\n\n- Implementer subagent (or a new one) fixes them\n- Reviewer reviews again\n- Repeat until approved\n- Don't skip the re-review\n\n### If Subagent Fails a Task\n\n- Dispatch a new fix subagent with specific instructions about what went wrong\n- Don't try to fix manually in the controller session (context pollution)\n\n## Efficiency Notes\n\n**Why fresh subagent per task:**\n- Prevents context pollution from accumulated state\n- Each subagent gets clean, focused context\n- No confusion from prior tasks' code or reasoning\n\n**Why two-stage review:**\n- Spec review catches under\u002Fover-building early\n- Quality review ensures the implementation is well-built\n- Catches issues before they compound across tasks\n\n**Cost trade-off:**\n- More subagent invocations (implementer + 2 reviewers per task)\n- But catches issues early (cheaper than debugging compounded problems later)\n\n## Integration with Other Skills\n\n### With writing-plans\n\nThis skill EXECUTES plans created by the writing-plans skill:\n1. User requirements → writing-plans → implementation plan\n2. Implementation plan → subagent-driven-development → working code\n\n### With test-driven-development\n\nImplementer subagents should follow TDD:\n1. Write failing test first\n2. Implement minimal code\n3. Verify test passes\n4. Commit\n\nInclude TDD instructions in every implementer context.\n\n### With requesting-code-review\n\nThe two-stage review process IS the code review. For final integration review, use the requesting-code-review skill's review dimensions.\n\n### With systematic-debugging\n\nIf a subagent encounters bugs during implementation:\n1. Follow systematic-debugging process\n2. Find root cause before fixing\n3. Write regression test\n4. Resume implementation\n\n## Example Workflow\n\n```\n[Read plan: docs\u002Fplans\u002Fauth-feature.md]\n[Create todo list with 5 tasks]\n\n--- Task 1: Create User model ---\n[Dispatch implementer subagent]\n  Implementer: \"Should email be unique?\"\n  You: \"Yes, email must be unique\"\n  Implementer: Implemented, 3\u002F3 tests passing, committed.\n\n[Dispatch spec reviewer]\n  Spec reviewer: ✅ PASS — all requirements met\n\n[Dispatch quality reviewer]\n  Quality reviewer: ✅ APPROVED — clean code, good tests\n\n[Mark Task 1 complete]\n\n--- Task 2: Password hashing ---\n[Dispatch implementer subagent]\n  Implementer: No questions, implemented, 5\u002F5 tests passing.\n\n[Dispatch spec reviewer]\n  Spec reviewer: ❌ Missing: password strength validation (spec says \"min 8 chars\")\n\n[Implementer fixes]\n  Implementer: Added validation, 7\u002F7 tests passing.\n\n[Dispatch spec reviewer again]\n  Spec reviewer: ✅ PASS\n\n[Dispatch quality reviewer]\n  Quality reviewer: Important: Magic number 8, extract to constant\n  Implementer: Extracted MIN_PASSWORD_LENGTH constant\n  Quality reviewer: ✅ APPROVED\n\n[Mark Task 2 complete]\n\n... (continue for all tasks)\n\n[After all tasks: dispatch final integration reviewer]\n[Run full test suite: all passing]\n[Done!]\n```\n\n## Remember\n\n```\nFresh subagent per task\nTwo-stage review every time\nSpec compliance FIRST\nCode quality SECOND\nNever skip reviews\nCatch issues early\n```\n\n**Quality is not an accident. It's the result of systematic process.**\n\n## Further reading (load when relevant)\n\nWhen the orchestration involves significant context usage, long review loops, or complex validation checkpoints, load these references for the specific discipline:\n\n- **`references\u002Fcontext-budget-discipline.md`** — Four-tier context degradation model (PEAK \u002F GOOD \u002F DEGRADING \u002F POOR), read-depth rules that scale with context window size, and early warning signs of silent degradation. Load when a run will clearly consume significant context (multi-phase plans, many subagents, large artifacts).\n- **`references\u002Fgates-taxonomy.md`** — The four canonical gate types (Pre-flight, Revision, Escalation, Abort) with behavior, recovery, and examples. Load when designing or reviewing any workflow that has validation checkpoints — use the vocabulary explicitly so each gate has defined entry, failure behavior, and resumption rules.\n\nBoth references adapted from gsd-build\u002Fget-shit-done (MIT © 2025 Lex Christopherson).\n",{"name":5,"author":23,"license":14,"version":24,"metadata":25,"platforms":37,"description":7},"Hermes Agent (adapted from obra\u002Fsuperpowers)","1.1.0",{"hermes":26},{"tags":27,"related_skills":33},[28,29,30,31,32],"delegation","subagent","implementation","workflow","parallel",[34,35,36],"writing-plans","requesting-code-review","test-driven-development",[38,39,40],"linux","macos","windows","main","e0ec177d00f087cb04e90206b2f7d3aa2f5a1350","References\u002FAgent\u002FPlatforms\u002Fhermes-agent\u002Fskills\u002Fsoftware-development\u002Fsubagent-driven-development","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim","https:\u002F\u002Fgithub.com\u002Flzy18001500226","2026-08-31 23:29:00",{"source":8,"skillName":5,"commands":48,"prompt":58,"zipAvailable":59},[49,52,55],{"tool":50,"command":51},"npx","npx skills add lzy18001500226\u002FMoSim --skill subagent-driven-development",{"tool":53,"command":54},"bunx","bunx skills add lzy18001500226\u002FMoSim --skill subagent-driven-development",{"tool":56,"command":57},"pnpm","pnpm dlx skills add lzy18001500226\u002FMoSim --skill subagent-driven-development","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FPlatforms\u002Fhermes-agent\u002Fskills\u002Fsoftware-development\u002Fsubagent-driven-development\u002FSKILL.md",true,[61,67],{"path":62,"resourceType":63,"resourceTypeDesc":64,"sizeBytes":65,"sourceHtmlUrl":66},"references\u002Fcontext-budget-discipline.md","REFERENCE","参考文档",4209,"https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FPlatforms\u002Fhermes-agent\u002Fskills\u002Fsoftware-development\u002Fsubagent-driven-development\u002Freferences\u002Fcontext-budget-discipline.md",{"path":68,"resourceType":63,"resourceTypeDesc":64,"sizeBytes":69,"sourceHtmlUrl":70},"references\u002Fgates-taxonomy.md",4668,"https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FPlatforms\u002Fhermes-agent\u002Fskills\u002Fsoftware-development\u002Fsubagent-driven-development\u002Freferences\u002Fgates-taxonomy.md",[72,82,90,98,106,114],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":76,"licenseFileUrl":77,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":81},"01M78RK6JGRPTD3TDSMTQWDQ9P","skill-installer","Install Codex skills into $CODEX_HOME\u002Fskills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).","Apache-2.0","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fskill-installer\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fskill-installer\u002FSKILL.md",[],[],"2026-11-15 14:19:17",{"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":76,"licenseFileUrl":86,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":81},"01M78RK29KVRDQXSMVZX1GQTJN","skill-creator","Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fskill-creator\u002Flicense.txt","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fskill-creator\u002FSKILL.md",[],[],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":76,"licenseFileUrl":94,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":81},"01M78RJPF3210Y5DA9VJ6JMMG6","openai-docs","Use for Codex models\u002Fpricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs\u002Fproducts and ChatGPT Work. Also use for model choice\u002Fmigration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat\u002FWork\u002FCodex comparisons. Do not use for generic app\u002Fsoftware tasks that merely mention Codex.","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fopenai-docs\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fopenai-docs\u002FSKILL.md",[],[],{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":76,"licenseFileUrl":102,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":81},"01M78RJH7X67C5AY8ZVS7RQNWJ","imagegen","Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG\u002Fvector\u002Fcode-native assets, extending an established icon or logo system, or building the visual directly in HTML\u002FCSS\u002Fcanvas.","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fimagegen\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002Fsrc\u002FAgent\u002Fcodex-main\u002Fcodex-rs\u002Fskills\u002Fsrc\u002Fassets\u002Fsamples\u002Fimagegen\u002FSKILL.md",[],[],{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":76,"licenseFileUrl":110,"sourceHtmlUrl":111,"categories":112,"keywords":113,"publishedAt":81},"01M78RBBAYMJ6T3ZMAYHCFM6G7","skill-creator-cc","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FWorkflow\u002Fokwinds\u002Fmiscellany\u002Fagent\u002Fskills\u002Fskill-creator-cc\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FWorkflow\u002Fokwinds\u002Fmiscellany\u002Fagent\u002Fskills\u002Fskill-creator-cc\u002FSKILL.md",[],[],{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":118,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":122},"01M76VV9V2R9FZTVGMJZV7Y996","prd-writing-guide","Write complete, unambiguous PRDs that development teams can implement without guesswork. Includes requirement discovery framework, structured documentation methodology, completeness checklists, and common pitfall avoidance. Use when: writing new PRDs, reviewing PRD drafts, validating requirement completeness, preparing for engineering handoff. Triggers: 'write PRD', '写PRD', '产品需求文档', '需求文档', '需求规格', '需求评审', '完善需求', 'create requirements doc', 'product requirements', 'feature spec', 'requirements document'. Anti-triggers: 'technical design doc', 'architecture design', 'implementation plan', 'API design', '架构设计', '技术方案', '实现方案', '接口设计'.","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FWorkflow\u002Fokwinds\u002Fmiscellany\u002Fagent\u002Fskills\u002Fprd-writing-guide\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Flzy18001500226\u002FMoSim\u002Fblob\u002Fmain\u002FReferences\u002FAgent\u002FWorkflow\u002Fokwinds\u002Fmiscellany\u002Fagent\u002Fskills\u002Fprd-writing-guide\u002FSKILL.md",[],[],"2026-11-12 13:55:43"]