[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6P0ET751SC575B5G17YTJ1Y":3,"skill-same:01M6P0ET751SC575B5G17YTJ1Y":72},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":14,"repositoryHtmlUrl":54,"repositoryHomepageUrl":6,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":71},"01M6P0ET751SC575B5G17YTJ1Y","career-ops",null,"AI job search command center -- evaluate offers, generate CVs, scan portals, track applications. Use when the user pastes a job URL or JD, asks to scan portals, generate a CV\u002FPDF, track applications, prepare for interviews, draft outreach\u002Femails, or run any career-ops mode.","shreyasbhakta\u002FCareerReboot","shreyasbhakta","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F55823227?v=4","01M6P0DV5QY0C5FEMNYKBD4YFJ","Shreyas Bhakta","01M6P0DV9YG9JPTG0VVGG866PP",0,"MIT","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fagents\u002Fcareer-ops\u002F.agents\u002Fskills\u002Fcareer-ops\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"career ops","ops","career","project","track","SWE","mode","command center","URL","debrief","expand","discover","PDF","deep","text","pipeline","batch","search","inbox","training","2026-11-10 10:12:30",false,"---\nname: career-ops\ndescription: >-\n  AI job search command center -- evaluate offers, generate CVs, scan portals,\n  track applications. Use when the user pastes a job URL or JD, asks to scan\n  portals, generate a CV\u002FPDF, track applications, prepare for interviews, draft\n  outreach\u002Femails, or run any career-ops mode.\narguments: mode\nuser_invocable: true\nuser-invocable: true\nargument-hint: \"[scan | discover | deep | pdf | text | latex | latex-tex | cover | email | add | expand | eu-swe | oferta | ofertas | apply | batch | tracker | agent-inbox | pipeline | contacto | training | project | interview-prep | interview | interview\u002Fplan | interview\u002Fpractice | interview\u002Fdebrief | interview-redflag | patterns | offer-prep | titles | upskill | followup | reply-watch | outcome | update]\"\nlicense: MIT\n---\n\n# career-ops -- Router\n\ncareer-ops is a multi-CLI job-search command center. The routing below is shared across supported agent CLIs even when the invocation surface differs.\n\n## Project Root Resolution\n\nBefore reading any repo-relative path, derive `PROJECT_ROOT` from this loaded `SKILL.md`: start at the skill file's directory and walk upward until the nearest directory containing both `AGENTS.md` and `modes\u002F`. Resolve every path in this router (`modes\u002F`, `config\u002F`, `data\u002F`, scripts, templates, and output paths) against `PROJECT_ROOT`, never against the process's current working directory. This is required even when the checkout itself is nested (for example `Development\\\\career-ops`) or the command starts from a subdirectory. If those two sentinels cannot be found, stop and locate the career-ops checkout before reading or writing files.\n\n## Invocation Notes\n\n- CLIs with slash-command registration can expose this router as `\u002Fcareer-ops`.\n- In Cursor, this skill lives at `.cursor\u002Fskills\u002Fcareer-ops\u002F` and is auto-discovered; ask for a mode by name, or paste a JD\u002FURL to trigger auto-pipeline.\n- Interactive Codex sessions use `codex` in the repo root. Slash commands are not guaranteed in Codex, so ask Codex to run the same mode by name if `\u002Fcareer-ops` is unavailable.\n- Headless Codex workers use `codex exec \"prompt\"`.\n- The routing semantics below stay the same regardless of whether the entrypoint is a slash command or a natural-language prompt.\n\nCodex prompt examples that map to the same router semantics:\n\n```text\nEvaluate this JD with career-ops auto-pipeline: https:\u002F\u002Fcompany.com\u002Fjobs\u002F123\nRun the career-ops scan mode and summarize new matches.\nRun the career-ops pipeline mode for data\u002Fpipeline.md.\nRun the career-ops pdf mode for the latest evaluated role.\nRun the career-ops tracker mode and summarize the current statuses.\n```\n\n## Mode Routing\n\nDetermine the mode from `$mode`:\n\n| Input | Mode |\n|-------|------|\n| (empty \u002F no args) | `discovery` -- Show command menu |\n| JD text or URL (no sub-command) | **`auto-pipeline`** |\n| `oferta` | `oferta` |\n| `ofertas` | `ofertas` |\n| `contacto` | `contacto` |\n| `deep` | `deep` |\n| `interview-prep` | `interview-prep` |\n| `interview` | `interview` |\n| `eu-swe` | `regional\u002Feu-swe` |\n| `eu-fintech` | `regional\u002Feu-fintech` |\n| `interview\u002Fplan` | `interview\u002Fplan` |\n| `interview\u002Fpractice` | `interview\u002Fpractice` |\n| `interview\u002Fdebrief` | `interview\u002Fdebrief` |\n| `pdf` | `pdf` |\n| `text` | `text` |\n| `latex` | `latex` |\n| `latex-tex` | `latex-tex` |\n| `email` | `email` |\n| `add` | `add` |\n| `expand` | `expand` |\n| `training` | `training` |\n| `project` | `project` |\n| `tracker` | `tracker` |\n| `agent-inbox` | `agent-inbox` |\n| `inbox` | `agent-inbox` |\n| `pipeline` | `pipeline` |\n| `apply` | `apply` |\n| `scan` | `scan` |\n| `discover` | `discover` |\n| `batch` | `batch` |\n| `patterns` | `patterns` |\n| `offer-prep` | `offer-prep` |\n| `titles` | `titles` |\n| `upskill` | `upskill` |\n| `followup` | `followup` |\n| `reply-watch` | `reply-watch` |\n| `outcome` | `outcome` |\n| `interview-redflag` | `interview-redflag` |\n| `update` | `update` |\n| `cover` | `cover` |\n\n**Auto-pipeline detection:** If `$mode` is not a known sub-command AND contains JD text (keywords: \"responsibilities\", \"requirements\", \"qualifications\", \"about the role\", \"we're looking for\", company name + role) or a URL to a JD, execute `auto-pipeline`.\n\nIf `$mode` is not a sub-command AND doesn't look like a JD, show discovery.\n\n---\n\n## Output Language Directive\n\nBefore executing any mode, read `config\u002Fprofile.yml` if it exists and resolve:\n\n- `language.output` → ISO language code for human-facing output. Default: `en`.\n- `language.modes_dir` → optional market-mode directory. This controls market vocabulary and local evaluation rules only.\n\nInject this directive after loading the mode instructions and before producing any user-visible content:\n\n> Write all human-facing output in `{language.output}` regardless of the language of these instructions or of the job description. This includes reports, tracker notes, PDFs, cover letters, outreach, interview prep, form answers, and summaries. If `language.modes_dir` supplies market-specific vocabulary, keep the market logic but explain terms in `{language.output}` when needed.\n\n`language.output` is authoritative for prose. `modes_dir` is market context; it must not force the prose language.\n\n---\n\n## Discovery Mode (no arguments)\n\nIf your CLI supports `\u002Fcareer-ops`, show this menu. In Codex, surface the same options in plain text and map the requested mode the same way.\n\nConcrete equivalents for Codex prompt-driven sessions:\n\n```text\n\u002Fcareer-ops {JD}           ↔ \"Evaluate this JD with career-ops auto-pipeline: {JD or URL}\"\n\u002Fcareer-ops scan           ↔ \"Run the career-ops scan mode and summarize new matches.\"\n\u002Fcareer-ops pipeline       ↔ \"Run the career-ops pipeline mode for data\u002Fpipeline.md.\"\n\u002Fcareer-ops pdf            ↔ \"Run the career-ops pdf mode for the latest evaluated role.\"\n\u002Fcareer-ops email          ↔ \"Run the career-ops email mode for the latest evaluated role.\"\n\u002Fcareer-ops tracker        ↔ \"Run the career-ops tracker mode and summarize the current statuses.\"\n```\n\nShow this menu:\n\n```\ncareer-ops -- Command Center\n\nAvailable commands:\n  \u002Fcareer-ops {JD}      → AUTO-PIPELINE: evaluate + report + PDF + tracker (paste text or URL)\n  \u002Fcareer-ops pipeline  → Process pending URLs from inbox (data\u002Fpipeline.md)\n  \u002Fcareer-ops oferta    → Evaluation only A-F (no auto PDF)\n  \u002Fcareer-ops ofertas   → Compare and rank multiple offers\n  \u002Fcareer-ops contacto  → LinkedIn power move: find contacts + draft message\n  \u002Fcareer-ops deep      → Deep research prompt about company\n  \u002Fcareer-ops interview-prep → Generate company-specific interview prep doc\n  \u002Fcareer-ops interview    → Interactive profile\u002FCV onboarding interview\n  \u002Fcareer-ops eu-swe    → Calibrate a European SWE application before CV\u002Fapply\u002Finterview\n  \u002Fcareer-ops eu-fintech → Scan 21 EU fintech portals for Product Manager roles (zero-token)\n  \u002Fcareer-ops interview\u002Fplan → Time-blocked prep plan for an upcoming interview\n  \u002Fcareer-ops interview\u002Fpractice → Practice interview, one question at a time with feedback\n  \u002Fcareer-ops interview\u002Fdebrief → Post-interview debrief: close gaps, predict next round\n  \u002Fcareer-ops pdf       → PDF only, ATS-optimized CV\n  \u002Fcareer-ops text      → Tailored markdown CV (mirrors cv.md, no PDF)\n  \u002Fcareer-ops latex     → Export CV as LaTeX\u002FOverleaf .tex\n  \u002Fcareer-ops latex-tex → Tailor your own resume.tex in place (opt-in; cv.md stays default)\n  \u002Fcareer-ops cover     → Cover letter: standalone JD paste or \u002Fcareer-ops cover {slug}\n  \u002Fcareer-ops email     → Formal application email draft (draft-only; never sends, submits, or clicks)\n  \u002Fcareer-ops add       → Add a project\u002Fpaper\u002Frole to your CV (fetch + preview + confirm)\n  \u002Fcareer-ops expand    → Auto-discover and add missing competencies from profile links\n  \u002Fcareer-ops training  → Evaluate course\u002Fcert against North Star\n  \u002Fcareer-ops project   → Evaluate portfolio project idea\n  \u002Fcareer-ops tracker   → Application status overview\n  \u002Fcareer-ops agent-inbox → Queue\u002Fdrain requests for the next session (data\u002Fagent-inbox.md)\n  \u002Fcareer-ops apply     → Live application assistant (reads form + generates answers)\n  \u002Fcareer-ops scan      → Scan portals and discover new offers\n  \u002Fcareer-ops discover  → Resolve a company list to scannable ATS boards + append to portals.yml (zero-token)\n  \u002Fcareer-ops batch     → Batch processing with parallel workers\n  \u002Fcareer-ops patterns  → Analyze rejection patterns and improve targeting\n  \u002Fcareer-ops offer-prep → Read a received offer\u002Fcontract with the candidate: clause walk + lawyer questions (not legal advice)\n  \u002Fcareer-ops titles    → Suggest adjacent job titles from your CV to broaden the search\n  \u002Fcareer-ops upskill   → Aggregate skill-gap analysis from your evaluated reports\n  \u002Fcareer-ops followup  → Follow-up cadence tracker: flag overdue, generate drafts\n  \u002Fcareer-ops outcome   → Record application outcome & archive artifacts\n  \u002Fcareer-ops update    → Update career-ops system files with diff preview + compat check\n\nInbox: add URLs to data\u002Fpipeline.md → \u002Fcareer-ops pipeline\nOr paste a JD directly to run the full pipeline.\n```\n\n---\n\n## Context Loading by Mode\n\nAfter determining the mode, load the necessary files before executing:\n\nIf `modes\u002F_custom.md` exists, read it after `modes\u002F_profile.md` and before the selected mode file. It contains user house rules and procedural preferences. It may override workflow\u002Fstyle defaults, but it never adds factual claims about the candidate.\n\n### Modes that require `_shared.md` + their mode file\n\nRead `modes\u002F_shared.md` + `modes\u002F_profile.md` (if exists) + `modes\u002F_custom.md` (if exists) + `modes\u002F{mode}.md`\n\nApplies to: `auto-pipeline`, `oferta`, `ofertas`, `pdf`, `text`, `contacto`, `apply`, `pipeline`, `scan`, `batch`\n\n### Standalone modes with profile and custom context\n\nRead `modes\u002F_profile.md` (if exists) + `modes\u002F_custom.md` (if exists) + `modes\u002F{mode}.md`\n\nApplies to: `tracker`, `agent-inbox`, `deep`, `interview-prep`, `interview`, `regional\u002Feu-swe`, `interview\u002Fplan`, `interview\u002Fpractice`, `interview\u002Fdebrief`, `latex`, `latex-tex`, `training`, `project`, `patterns`, `titles`, `upskill`, `followup`, `reply-watch`, `outcome`, `cover`, `email`, `add`, `offer-prep`, `discover`\n\n### Modes delegated to subagent\n\nFor `scan`, `apply` (with Playwright), and `pipeline` (3+ URLs): launch as a worker\u002Fsubagent with the content of `_shared.md` + `_profile.md` (if exists) + `_custom.md` (if exists) + `modes\u002F{mode}.md` injected into the worker prompt. If your CLI exposes an `Agent(...)` primitive, the call looks like this:\n\n```python\nAgent(\n  subagent_type=\"general-purpose\",\n  prompt=\"[output language directive]\\n\\n[content of modes\u002F_shared.md]\\n\\n[content of modes\u002F_profile.md if exists]\\n\\n[content of modes\u002F_custom.md if exists]\\n\\n[content of modes\u002F{mode}.md]\\n\\n[invocation-specific data]\",\n  description=\"career-ops {mode}\"\n)\n```\n\nExecute the instructions from the loaded mode file.\n","# career-ops -- Router\n\ncareer-ops is a multi-CLI job-search command center. The routing below is shared across supported agent CLIs even when the invocation surface differs.\n\n## Project Root Resolution\n\nBefore reading any repo-relative path, derive `PROJECT_ROOT` from this loaded `SKILL.md`: start at the skill file's directory and walk upward until the nearest directory containing both `AGENTS.md` and `modes\u002F`. Resolve every path in this router (`modes\u002F`, `config\u002F`, `data\u002F`, scripts, templates, and output paths) against `PROJECT_ROOT`, never against the process's current working directory. This is required even when the checkout itself is nested (for example `Development\\\\career-ops`) or the command starts from a subdirectory. If those two sentinels cannot be found, stop and locate the career-ops checkout before reading or writing files.\n\n## Invocation Notes\n\n- CLIs with slash-command registration can expose this router as `\u002Fcareer-ops`.\n- In Cursor, this skill lives at `.cursor\u002Fskills\u002Fcareer-ops\u002F` and is auto-discovered; ask for a mode by name, or paste a JD\u002FURL to trigger auto-pipeline.\n- Interactive Codex sessions use `codex` in the repo root. Slash commands are not guaranteed in Codex, so ask Codex to run the same mode by name if `\u002Fcareer-ops` is unavailable.\n- Headless Codex workers use `codex exec \"prompt\"`.\n- The routing semantics below stay the same regardless of whether the entrypoint is a slash command or a natural-language prompt.\n\nCodex prompt examples that map to the same router semantics:\n\n```text\nEvaluate this JD with career-ops auto-pipeline: https:\u002F\u002Fcompany.com\u002Fjobs\u002F123\nRun the career-ops scan mode and summarize new matches.\nRun the career-ops pipeline mode for data\u002Fpipeline.md.\nRun the career-ops pdf mode for the latest evaluated role.\nRun the career-ops tracker mode and summarize the current statuses.\n```\n\n## Mode Routing\n\nDetermine the mode from `$mode`:\n\n| Input | Mode |\n|-------|------|\n| (empty \u002F no args) | `discovery` -- Show command menu |\n| JD text or URL (no sub-command) | **`auto-pipeline`** |\n| `oferta` | `oferta` |\n| `ofertas` | `ofertas` |\n| `contacto` | `contacto` |\n| `deep` | `deep` |\n| `interview-prep` | `interview-prep` |\n| `interview` | `interview` |\n| `eu-swe` | `regional\u002Feu-swe` |\n| `eu-fintech` | `regional\u002Feu-fintech` |\n| `interview\u002Fplan` | `interview\u002Fplan` |\n| `interview\u002Fpractice` | `interview\u002Fpractice` |\n| `interview\u002Fdebrief` | `interview\u002Fdebrief` |\n| `pdf` | `pdf` |\n| `text` | `text` |\n| `latex` | `latex` |\n| `latex-tex` | `latex-tex` |\n| `email` | `email` |\n| `add` | `add` |\n| `expand` | `expand` |\n| `training` | `training` |\n| `project` | `project` |\n| `tracker` | `tracker` |\n| `agent-inbox` | `agent-inbox` |\n| `inbox` | `agent-inbox` |\n| `pipeline` | `pipeline` |\n| `apply` | `apply` |\n| `scan` | `scan` |\n| `discover` | `discover` |\n| `batch` | `batch` |\n| `patterns` | `patterns` |\n| `offer-prep` | `offer-prep` |\n| `titles` | `titles` |\n| `upskill` | `upskill` |\n| `followup` | `followup` |\n| `reply-watch` | `reply-watch` |\n| `outcome` | `outcome` |\n| `interview-redflag` | `interview-redflag` |\n| `update` | `update` |\n| `cover` | `cover` |\n\n**Auto-pipeline detection:** If `$mode` is not a known sub-command AND contains JD text (keywords: \"responsibilities\", \"requirements\", \"qualifications\", \"about the role\", \"we're looking for\", company name + role) or a URL to a JD, execute `auto-pipeline`.\n\nIf `$mode` is not a sub-command AND doesn't look like a JD, show discovery.\n\n---\n\n## Output Language Directive\n\nBefore executing any mode, read `config\u002Fprofile.yml` if it exists and resolve:\n\n- `language.output` → ISO language code for human-facing output. Default: `en`.\n- `language.modes_dir` → optional market-mode directory. This controls market vocabulary and local evaluation rules only.\n\nInject this directive after loading the mode instructions and before producing any user-visible content:\n\n> Write all human-facing output in `{language.output}` regardless of the language of these instructions or of the job description. This includes reports, tracker notes, PDFs, cover letters, outreach, interview prep, form answers, and summaries. If `language.modes_dir` supplies market-specific vocabulary, keep the market logic but explain terms in `{language.output}` when needed.\n\n`language.output` is authoritative for prose. `modes_dir` is market context; it must not force the prose language.\n\n---\n\n## Discovery Mode (no arguments)\n\nIf your CLI supports `\u002Fcareer-ops`, show this menu. In Codex, surface the same options in plain text and map the requested mode the same way.\n\nConcrete equivalents for Codex prompt-driven sessions:\n\n```text\n\u002Fcareer-ops {JD}           ↔ \"Evaluate this JD with career-ops auto-pipeline: {JD or URL}\"\n\u002Fcareer-ops scan           ↔ \"Run the career-ops scan mode and summarize new matches.\"\n\u002Fcareer-ops pipeline       ↔ \"Run the career-ops pipeline mode for data\u002Fpipeline.md.\"\n\u002Fcareer-ops pdf            ↔ \"Run the career-ops pdf mode for the latest evaluated role.\"\n\u002Fcareer-ops email          ↔ \"Run the career-ops email mode for the latest evaluated role.\"\n\u002Fcareer-ops tracker        ↔ \"Run the career-ops tracker mode and summarize the current statuses.\"\n```\n\nShow this menu:\n\n```\ncareer-ops -- Command Center\n\nAvailable commands:\n  \u002Fcareer-ops {JD}      → AUTO-PIPELINE: evaluate + report + PDF + tracker (paste text or URL)\n  \u002Fcareer-ops pipeline  → Process pending URLs from inbox (data\u002Fpipeline.md)\n  \u002Fcareer-ops oferta    → Evaluation only A-F (no auto PDF)\n  \u002Fcareer-ops ofertas   → Compare and rank multiple offers\n  \u002Fcareer-ops contacto  → LinkedIn power move: find contacts + draft message\n  \u002Fcareer-ops deep      → Deep research prompt about company\n  \u002Fcareer-ops interview-prep → Generate company-specific interview prep doc\n  \u002Fcareer-ops interview    → Interactive profile\u002FCV onboarding interview\n  \u002Fcareer-ops eu-swe    → Calibrate a European SWE application before CV\u002Fapply\u002Finterview\n  \u002Fcareer-ops eu-fintech → Scan 21 EU fintech portals for Product Manager roles (zero-token)\n  \u002Fcareer-ops interview\u002Fplan → Time-blocked prep plan for an upcoming interview\n  \u002Fcareer-ops interview\u002Fpractice → Practice interview, one question at a time with feedback\n  \u002Fcareer-ops interview\u002Fdebrief → Post-interview debrief: close gaps, predict next round\n  \u002Fcareer-ops pdf       → PDF only, ATS-optimized CV\n  \u002Fcareer-ops text      → Tailored markdown CV (mirrors cv.md, no PDF)\n  \u002Fcareer-ops latex     → Export CV as LaTeX\u002FOverleaf .tex\n  \u002Fcareer-ops latex-tex → Tailor your own resume.tex in place (opt-in; cv.md stays default)\n  \u002Fcareer-ops cover     → Cover letter: standalone JD paste or \u002Fcareer-ops cover {slug}\n  \u002Fcareer-ops email     → Formal application email draft (draft-only; never sends, submits, or clicks)\n  \u002Fcareer-ops add       → Add a project\u002Fpaper\u002Frole to your CV (fetch + preview + confirm)\n  \u002Fcareer-ops expand    → Auto-discover and add missing competencies from profile links\n  \u002Fcareer-ops training  → Evaluate course\u002Fcert against North Star\n  \u002Fcareer-ops project   → Evaluate portfolio project idea\n  \u002Fcareer-ops tracker   → Application status overview\n  \u002Fcareer-ops agent-inbox → Queue\u002Fdrain requests for the next session (data\u002Fagent-inbox.md)\n  \u002Fcareer-ops apply     → Live application assistant (reads form + generates answers)\n  \u002Fcareer-ops scan      → Scan portals and discover new offers\n  \u002Fcareer-ops discover  → Resolve a company list to scannable ATS boards + append to portals.yml (zero-token)\n  \u002Fcareer-ops batch     → Batch processing with parallel workers\n  \u002Fcareer-ops patterns  → Analyze rejection patterns and improve targeting\n  \u002Fcareer-ops offer-prep → Read a received offer\u002Fcontract with the candidate: clause walk + lawyer questions (not legal advice)\n  \u002Fcareer-ops titles    → Suggest adjacent job titles from your CV to broaden the search\n  \u002Fcareer-ops upskill   → Aggregate skill-gap analysis from your evaluated reports\n  \u002Fcareer-ops followup  → Follow-up cadence tracker: flag overdue, generate drafts\n  \u002Fcareer-ops outcome   → Record application outcome & archive artifacts\n  \u002Fcareer-ops update    → Update career-ops system files with diff preview + compat check\n\nInbox: add URLs to data\u002Fpipeline.md → \u002Fcareer-ops pipeline\nOr paste a JD directly to run the full pipeline.\n```\n\n---\n\n## Context Loading by Mode\n\nAfter determining the mode, load the necessary files before executing:\n\nIf `modes\u002F_custom.md` exists, read it after `modes\u002F_profile.md` and before the selected mode file. It contains user house rules and procedural preferences. It may override workflow\u002Fstyle defaults, but it never adds factual claims about the candidate.\n\n### Modes that require `_shared.md` + their mode file\n\nRead `modes\u002F_shared.md` + `modes\u002F_profile.md` (if exists) + `modes\u002F_custom.md` (if exists) + `modes\u002F{mode}.md`\n\nApplies to: `auto-pipeline`, `oferta`, `ofertas`, `pdf`, `text`, `contacto`, `apply`, `pipeline`, `scan`, `batch`\n\n### Standalone modes with profile and custom context\n\nRead `modes\u002F_profile.md` (if exists) + `modes\u002F_custom.md` (if exists) + `modes\u002F{mode}.md`\n\nApplies to: `tracker`, `agent-inbox`, `deep`, `interview-prep`, `interview`, `regional\u002Feu-swe`, `interview\u002Fplan`, `interview\u002Fpractice`, `interview\u002Fdebrief`, `latex`, `latex-tex`, `training`, `project`, `patterns`, `titles`, `upskill`, `followup`, `reply-watch`, `outcome`, `cover`, `email`, `add`, `offer-prep`, `discover`\n\n### Modes delegated to subagent\n\nFor `scan`, `apply` (with Playwright), and `pipeline` (3+ URLs): launch as a worker\u002Fsubagent with the content of `_shared.md` + `_profile.md` (if exists) + `_custom.md` (if exists) + `modes\u002F{mode}.md` injected into the worker prompt. If your CLI exposes an `Agent(...)` primitive, the call looks like this:\n\n```python\nAgent(\n  subagent_type=\"general-purpose\",\n  prompt=\"[output language directive]\\n\\n[content of modes\u002F_shared.md]\\n\\n[content of modes\u002F_profile.md if exists]\\n\\n[content of modes\u002F_custom.md if exists]\\n\\n[content of modes\u002F{mode}.md]\\n\\n[invocation-specific data]\",\n  description=\"career-ops {mode}\"\n)\n```\n\nExecute the instructions from the loaded mode file.\n",{"name":5,"license":15,"arguments":30,"description":7,"argument-hint":49,"user-invocable":50,"user_invocable":50},"[scan | discover | deep | pdf | text | latex | latex-tex | cover | email | add | expand | eu-swe | oferta | ofertas | apply | batch | tracker | agent-inbox | pipeline | contacto | training | project | interview-prep | interview | interview\u002Fplan | interview\u002Fpractice | interview\u002Fdebrief | interview-redflag | patterns | offer-prep | titles | upskill | followup | reply-watch | outcome | update]",true,"main","466b9f58403b6b473023097f5b9f3f094ebeb493","agents\u002Fcareer-ops\u002F.agents\u002Fskills\u002Fcareer-ops","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta","shreyasbhakta.dev","Software Engineer | Backend & Distributed Systems | Java, Spring Boot, Kafka, Python | Agentic AI, LangGraph, RAG | Ex-Vymo, Ex-SIXT | Cybersecurity Enthusiast","2026-10-17 04:01:42",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":50},[61,64,67],{"tool":62,"command":63},"npx","npx skills add shreyasbhakta\u002FCareerReboot --skill career-ops",{"tool":65,"command":66},"bunx","bunx skills add shreyasbhakta\u002FCareerReboot --skill career-ops",{"tool":68,"command":69},"pnpm","pnpm dlx skills add shreyasbhakta\u002FCareerReboot --skill career-ops","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fagents\u002Fcareer-ops\u002F.agents\u002Fskills\u002Fcareer-ops\u002FSKILL.md",[],[73,99,119,133,143,154],{"skillNo":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":78,"categories":79,"keywords":85,"publishedAt":44},"01M6P0SGCMXDZ5DH19S9RS4PZZ","tech-resume-optimizer","Optimize resumes for software engineering, PM, and technical roles","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Ftech-resume-optimizer\u002FSKILL.md",[80],{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},"01JBSEEDCAT000000000000038","人力资源","PROFESSION","适用职业",[86,87,88,89,90,91,92,93,94,95,96,97,98],"tech resume optimizer","resume","resume optimizer","optimizer","tech","software engineering","for","engineering","technical","optimize","pm","roles","software",{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":108,"publishedAt":44},"01M6P0SC37HWQ8CTWA37SVPAA3","salary-negotiation-prep","Research market rates, build negotiation strategy, and create counter-offer scripts","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Fsalary-negotiation-prep\u002FSKILL.md",[105],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",[109,110,111,112,113,114,115,116,117,118],"negotiation prep","prep","negotiation","salary negotiation prep","build","scripts","Market","research","create","strategy",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":126,"publishedAt":44},"01M6P0RSXGGR789TX42ZXNR09N","resume-version-manager","Track different resume versions, maintain master resume, manage tailored versions","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Fresume-version-manager\u002FSKILL.md",[125],{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},[127,87,128,129,130,131,132,28],"manager","version","resume version manager","master","manage","maintain",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":137,"categories":138,"keywords":140,"publishedAt":44},"01M6P0RK6FX16FYCC01T2HA2MA","resume-tailor","Customize resume for specific job postings while maintaining truthfulness","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Fresume-tailor\u002FSKILL.md",[139],{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},[87,141,92,142],"resume tailor","customize",{"skillNo":144,"name":145,"nameZh":6,"description":146,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":147,"categories":148,"keywords":150,"publishedAt":44},"01M6P0R57S7ASRV6VAYQ4K2J9Y","resume-section-builder","Create targeted resume sections optimized for different experience levels and roles","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Fresume-section-builder\u002FSKILL.md",[149],{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},[151,152,87,153,117,97,92],"section","builder","resume section builder",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":77,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":161,"publishedAt":44},"01M6P0R0TVRRDSTTM047HWXNCD","resume-quantifier","Find opportunities to add metrics and estimate numbers when exact data unavailable","https:\u002F\u002Fgithub.com\u002Fshreyasbhakta\u002FCareerReboot\u002Fblob\u002Fmain\u002Fskills\u002Fresume-skills\u002Fskills\u002Fresume-quantifier\u002FSKILL.md",[160],{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},[87,162,163,164,165,166,167],"resume quantifier","metrics","data","find","add","estimate"]