[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CSX487J6JVX23GMTY3MAGG":3,"skill-same:01M6CSX487J6JVX23GMTY3MAGG":82},{"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":18,"publishedAt":28,"linkOnly":29,"markdownContent":30,"markdownBody":31,"frontMatter":32,"refName":33,"commitSha":34,"skillDirectory":35,"forksCount":14,"repositoryHtmlUrl":36,"repositoryHomepageUrl":6,"ownerHtmlUrl":37,"ownerBlogUrl":38,"ownerDescription":6,"updatedAt":39,"install":40,"resources":53},"01M6CSX487J6JVX23GMTY3MAGG","diagnosing-bugs",null,"Diagnosis loop for hard bugs and performance regressions. Use when the user says \"diagnose\"\u002F\"debug this\", or reports something broken\u002Fthrowing\u002Ffailing\u002Fslow.","goffity\u002Fdev-km","goffity","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F778547?v=4","01M6CSW9QQ32YQYTRKQWVKYCAY","Goffity","01M6CSW9VQFVZ3QS6RB4VYJGE6",0,"MIT","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fdiagnosing-bugs\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27],"diagnosing bugs","performance","debug","diagnose","loop","broken","user","use","reports","2026-11-10 10:12:30",false,"---\nname: diagnosing-bugs\ndescription: Diagnosis loop for hard bugs and performance regressions. Use when the user says \"diagnose\"\u002F\"debug this\", or reports something broken\u002Fthrowing\u002Ffailing\u002Fslow.\n---\n\n# Diagnosing Bugs\n\n> Vendored from [mattpocock\u002Fskills](https:\u002F\u002Fgithub.com\u002Fmattpocock\u002Fskills) (MIT), adapted for kol.\n\nA discipline for hard bugs. Skip phases only when explicitly justified.\n\n## Phase 0 (kol): Search the knowledge base first\n\nBefore anything else, grep the kol-brain vault for this symptom — the org may have already diagnosed it (and an existing note may even contain wrong info that needs correcting):\n\n```bash\ngrep -ril \"\u003Csymptom keywords>\" ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F03-bugs ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F00-inbox ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F05-ai-reviewed\n```\n\nAlso read `kb\u002FGLOSSARY.md` for the domain vocabulary, and check ADRs (`kb\u002F04-decisions\u002F`) in the area you're touching. A prior note with the root cause turns this whole skill into a verification exercise. When the diagnosis is done, capture new findings back to `kb\u002F03-bugs\u002F` per Template D.\n\n## Redact\n\nThis skill has you show commands, outputs and captured artifacts. **Redact every secret first**: write `\u003CREDACTED>` in its place. Build loops against env vars, so the credential stays in the environment rather than in what you show. Captured artifacts carry auth headers: quote only the lines that carry the signal.\n\nIf the redacted output is not enough to diagnose the bug, say so and ask the user.\n\n## Phase 1: Build a feedback loop\n\n**This is the skill.** Everything else is mechanical. If you have a **tight** pass\u002Ffail signal for the bug (one that goes red on _this_ bug), you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.\n\nSpend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**\n\n### Ways to construct one, in roughly this order\n\n1. **Failing test** at whatever seam reaches the bug: unit, integration, e2e.\n2. **Curl \u002F HTTP script** against a running dev server.\n3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.\n4. **Headless browser script** (Playwright \u002F Puppeteer) that drives the UI and asserts on DOM\u002Fconsole\u002Fnetwork.\n5. **Replay a captured trace.** Save a real network request \u002F payload \u002F event log to disk; replay it through the code path in isolation.\n6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.\n7. **Property \u002F fuzz loop.** If the bug is \"sometimes wrong output\", run 1000 random inputs and look for the failure mode.\n8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate \"boot at state X, check, repeat\" so you can `git bisect run` it.\n9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.\n10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts\u002Fhitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.\n\nBuild the right feedback loop, and the bug is 90% fixed.\n\n### Tighten the loop\n\nTreat the loop as a product. Once you have _a_ loop, **tighten** it:\n\n- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)\n- Can I make the signal sharper? (Assert on the specific symptom, not \"didn't crash\".)\n- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)\n\nA 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight, a debugging superpower.\n\n### Non-deterministic bugs\n\nThe goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not, so keep raising the rate until it's debuggable.\n\n### When you genuinely cannot build a loop\n\nStop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a redacted captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.\n\n### Completion criterion: a tight loop that goes red\n\nPhase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** (a script path, a test invocation, a curl) that you have **already run at least once** (show the invocation and its output, redacted), and that is:\n\n- [ ] **Red-capable**: it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not \"runs without erroring\"; it must be able to _catch this specific bug_.\n- [ ] **Deterministic**: same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).\n- [ ] **Fast**: seconds, not minutes.\n- [ ] **Agent-runnable**: you can run it unattended; a human in the loop only via `scripts\u002Fhitl-loop.template.sh`.\n\nIf you catch yourself reading code to build a theory before this command exists, **stop: jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.\n\n## Phase 2: Reproduce + minimise\n\nRun the loop. Watch it go red as the bug appears.\n\nConfirm:\n\n- [ ] The loop produces the failure mode the **user** described, not a different failure that happens to be nearby. Wrong bug = wrong fix.\n- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).\n- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.\n\n### Minimise\n\nOnce it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut, and keep only what's load-bearing for the failure.\n\nWhy bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.\n\nDone when **every remaining element is load-bearing**: removing any one of them makes the loop go green.\n\nDo not proceed until you have reproduced **and** minimised.\n\n## Phase 3: Hypothesise\n\nGenerate **3–5 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.\n\nEach hypothesis must be **falsifiable**: state the prediction it makes.\n\n> Format: \"If \u003CX> is the cause, then \u003Cchanging Y> will make the bug disappear \u002F \u003Cchanging Z> will make it worse.\"\n\nIf you cannot state the prediction, the hypothesis is a vibe: discard or sharpen it.\n\n**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly (\"we just deployed a change to #3\"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it; proceed with your ranking if the user is AFK.\n\n## Phase 4: Instrument\n\nEach probe must map to a specific prediction from Phase 3. **Change one variable at a time.**\n\nTool preference:\n\n1. **Debugger \u002F REPL inspection** if the env supports it. One breakpoint beats ten logs.\n2. **Targeted logs** at the boundaries that distinguish hypotheses.\n3. Never \"log everything and grep\".\n\n**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.\n\n**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.\n\n## Phase 5: Fix + regression test\n\nWrite the regression test **before the fix**, but only if there is a **correct seam** for it.\n\nA correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.\n\n**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.\n\nIf a correct seam exists:\n\n1. Turn the minimised repro into a failing test at that seam.\n2. Watch it fail.\n3. Apply the fix.\n4. Watch it pass.\n5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.\n\n## Phase 6: Cleanup\n\nRequired before declaring done:\n\n- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)\n- [ ] Regression test passes (or absence of seam is documented)\n- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)\n- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)\n- [ ] The hypothesis that turned out correct is stated in the commit \u002F PR message, so the next debugger learns\n","# Diagnosing Bugs\n\n> Vendored from [mattpocock\u002Fskills](https:\u002F\u002Fgithub.com\u002Fmattpocock\u002Fskills) (MIT), adapted for kol.\n\nA discipline for hard bugs. Skip phases only when explicitly justified.\n\n## Phase 0 (kol): Search the knowledge base first\n\nBefore anything else, grep the kol-brain vault for this symptom — the org may have already diagnosed it (and an existing note may even contain wrong info that needs correcting):\n\n```bash\ngrep -ril \"\u003Csymptom keywords>\" ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F03-bugs ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F00-inbox ~\u002FDevelopment\u002Fkol\u002Fkol-brain\u002F05-ai-reviewed\n```\n\nAlso read `kb\u002FGLOSSARY.md` for the domain vocabulary, and check ADRs (`kb\u002F04-decisions\u002F`) in the area you're touching. A prior note with the root cause turns this whole skill into a verification exercise. When the diagnosis is done, capture new findings back to `kb\u002F03-bugs\u002F` per Template D.\n\n## Redact\n\nThis skill has you show commands, outputs and captured artifacts. **Redact every secret first**: write `\u003CREDACTED>` in its place. Build loops against env vars, so the credential stays in the environment rather than in what you show. Captured artifacts carry auth headers: quote only the lines that carry the signal.\n\nIf the redacted output is not enough to diagnose the bug, say so and ask the user.\n\n## Phase 1: Build a feedback loop\n\n**This is the skill.** Everything else is mechanical. If you have a **tight** pass\u002Ffail signal for the bug (one that goes red on _this_ bug), you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.\n\nSpend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**\n\n### Ways to construct one, in roughly this order\n\n1. **Failing test** at whatever seam reaches the bug: unit, integration, e2e.\n2. **Curl \u002F HTTP script** against a running dev server.\n3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.\n4. **Headless browser script** (Playwright \u002F Puppeteer) that drives the UI and asserts on DOM\u002Fconsole\u002Fnetwork.\n5. **Replay a captured trace.** Save a real network request \u002F payload \u002F event log to disk; replay it through the code path in isolation.\n6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.\n7. **Property \u002F fuzz loop.** If the bug is \"sometimes wrong output\", run 1000 random inputs and look for the failure mode.\n8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate \"boot at state X, check, repeat\" so you can `git bisect run` it.\n9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.\n10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts\u002Fhitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.\n\nBuild the right feedback loop, and the bug is 90% fixed.\n\n### Tighten the loop\n\nTreat the loop as a product. Once you have _a_ loop, **tighten** it:\n\n- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)\n- Can I make the signal sharper? (Assert on the specific symptom, not \"didn't crash\".)\n- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)\n\nA 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight, a debugging superpower.\n\n### Non-deterministic bugs\n\nThe goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not, so keep raising the rate until it's debuggable.\n\n### When you genuinely cannot build a loop\n\nStop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a redacted captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.\n\n### Completion criterion: a tight loop that goes red\n\nPhase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** (a script path, a test invocation, a curl) that you have **already run at least once** (show the invocation and its output, redacted), and that is:\n\n- [ ] **Red-capable**: it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not \"runs without erroring\"; it must be able to _catch this specific bug_.\n- [ ] **Deterministic**: same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).\n- [ ] **Fast**: seconds, not minutes.\n- [ ] **Agent-runnable**: you can run it unattended; a human in the loop only via `scripts\u002Fhitl-loop.template.sh`.\n\nIf you catch yourself reading code to build a theory before this command exists, **stop: jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.\n\n## Phase 2: Reproduce + minimise\n\nRun the loop. Watch it go red as the bug appears.\n\nConfirm:\n\n- [ ] The loop produces the failure mode the **user** described, not a different failure that happens to be nearby. Wrong bug = wrong fix.\n- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).\n- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.\n\n### Minimise\n\nOnce it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut, and keep only what's load-bearing for the failure.\n\nWhy bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.\n\nDone when **every remaining element is load-bearing**: removing any one of them makes the loop go green.\n\nDo not proceed until you have reproduced **and** minimised.\n\n## Phase 3: Hypothesise\n\nGenerate **3–5 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.\n\nEach hypothesis must be **falsifiable**: state the prediction it makes.\n\n> Format: \"If \u003CX> is the cause, then \u003Cchanging Y> will make the bug disappear \u002F \u003Cchanging Z> will make it worse.\"\n\nIf you cannot state the prediction, the hypothesis is a vibe: discard or sharpen it.\n\n**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly (\"we just deployed a change to #3\"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it; proceed with your ranking if the user is AFK.\n\n## Phase 4: Instrument\n\nEach probe must map to a specific prediction from Phase 3. **Change one variable at a time.**\n\nTool preference:\n\n1. **Debugger \u002F REPL inspection** if the env supports it. One breakpoint beats ten logs.\n2. **Targeted logs** at the boundaries that distinguish hypotheses.\n3. Never \"log everything and grep\".\n\n**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.\n\n**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.\n\n## Phase 5: Fix + regression test\n\nWrite the regression test **before the fix**, but only if there is a **correct seam** for it.\n\nA correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.\n\n**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.\n\nIf a correct seam exists:\n\n1. Turn the minimised repro into a failing test at that seam.\n2. Watch it fail.\n3. Apply the fix.\n4. Watch it pass.\n5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.\n\n## Phase 6: Cleanup\n\nRequired before declaring done:\n\n- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)\n- [ ] Regression test passes (or absence of seam is documented)\n- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)\n- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)\n- [ ] The hypothesis that turned out correct is stated in the commit \u002F PR message, so the next debugger learns\n",{"name":5,"description":7},"main","835c1f754a3eab31c2e7eb408d21431a98c633ee","skills\u002Fdiagnosing-bugs","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km","https:\u002F\u002Fgithub.com\u002Fgoffity","www.narongwate.com","2026-11-10 01:34:18",{"source":8,"skillName":5,"commands":41,"prompt":51,"zipAvailable":52},[42,45,48],{"tool":43,"command":44},"npx","npx skills add goffity\u002Fdev-km --skill diagnosing-bugs",{"tool":46,"command":47},"bunx","bunx skills add goffity\u002Fdev-km --skill diagnosing-bugs",{"tool":49,"command":50},"pnpm","pnpm dlx skills add goffity\u002Fdev-km --skill diagnosing-bugs","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fdiagnosing-bugs\u002FSKILL.md",true,[54,60,64,68,74,78],{"path":55,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":58,"sourceHtmlUrl":59},"example.html","REFERENCE","参考文档",82610,"https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FPPT-Design\u002Fopen-design-open-design-landing-deck\u002Fexample.html",{"path":61,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":62,"sourceHtmlUrl":63},"inputs.example.json",7682,"https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FPPT-Design\u002Fopen-design-open-design-landing-deck\u002Finputs.example.json",{"path":65,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":66,"sourceHtmlUrl":67},"README.md",4291,"https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FPPT-Design\u002Fopen-design-open-design-landing-deck\u002FREADME.md",{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"schema.ts","SCRIPT","脚本",3877,"https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FPPT-Design\u002Fopen-design-open-design-landing-deck\u002Fschema.ts",{"path":75,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":76,"sourceHtmlUrl":77},"scripts\u002Fcompose.ts",33944,"https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FPPT-Design\u002Fopen-design-open-design-landing-deck\u002Fscripts\u002Fcompose.ts",{"path":79,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":80,"sourceHtmlUrl":81},"scripts\u002Fhitl-loop.template.sh",1316,"https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fdiagnosing-bugs\u002Fscripts\u002Fhitl-loop.template.sh",[83,94,126,138,146,161],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":28},"01M6CSZ9DKT0CG5Y2HE8F5D9KX","wait-what","Stop. That last message did not land: re-pitch it.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fwait-what\u002FSKILL.md",[],[90,91,92,93],"wait what","land","stop","message",{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":108,"publishedAt":28},"01M6CSZ6B0GH2N75WNPPESCDHX","tdd","Test-driven development loop (red-green-refactor) with commit-based phase state and Jira traceability. Use when the user wants to build a feature or fix a bug test-first, mentions \"tdd\", \"red-green-refactor\", or \"test-first\". Replaces the tdg plugin — combines its commit\u002Fphase discipline with seam-based test quality rules from kb Testing Standards.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Ftdd\u002FSKILL.md",[100,105],{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000007","代码审查","SCENARIO","使用场景",{"categoryNo":106,"categoryName":107,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000008","测试与质量",[96,109,110,111,112,23,113,114,115,116,26,117,118,119,120,121,122,123,124,125],"discipline","development","state","first","quality","Rules","fix","kb","test","standards","red-green-refactor","build","green","jira","testing","commit","plugin",{"skillNo":127,"name":128,"nameZh":6,"description":129,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":130,"categories":131,"keywords":132,"publishedAt":28},"01M6CSZ3PNYFR2K5GB197TA7GP","td","Creates post-task retrospectives with Before\u002FAfter context and session documentation.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Ftd\u002FSKILL.md",[],[128,133,134,135,136,137],"documentation","context","session","task","done",{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":144,"publishedAt":28},"01M6CSZ1TZKVNHS07B4EBQEKFQ","summary","Generates weekly or monthly session summaries from retrospectives and activity logs.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fsummary\u002FSKILL.md",[],[140,145,135],"logs",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":155,"publishedAt":28},"01M6CSYZQHMHJT9ZV8FYY06XZN","share","Shares knowledge across projects by copying to shared-knowledge directory with cross-project metadata.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fshare\u002FSKILL.md",[152],{"categoryNo":153,"categoryName":154,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000021","资料检索与研究",[148,156,157,158,159,160],"directory","metadata","file","knowledge","projects",{"skillNo":162,"name":163,"nameZh":6,"description":164,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":165,"categories":166,"keywords":167,"publishedAt":28},"01M6CSYXFZ7D7EKEFXCQE8QW7S","session-analyzer","Analyzes git changes and creates retrospective drafts with Before\u002FAfter context.","https:\u002F\u002Fgithub.com\u002Fgoffity\u002Fdev-km\u002Fblob\u002Fmain\u002Fskills\u002Fsession-analyzer\u002FSKILL.md",[],[135,168,169,134,170],"session analyzer","git","retrospective"]