[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D8BENQ89BGF2AQ45CVE5ZK":3,"skill-same:01M6D8BENQ89BGF2AQ45CVE5ZK":71},{"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":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":41,"commitSha":42,"skillDirectory":43,"forksCount":44,"repositoryHtmlUrl":45,"repositoryHomepageUrl":46,"ownerHtmlUrl":47,"ownerBlogUrl":48,"ownerDescription":49,"updatedAt":50,"install":51,"resources":64},"01M6D8BENQ89BGF2AQ45CVE5ZK","experience-map",null,"Adaptive Path experience map — emotional arc with doing\u002Fthinking\u002Ffeeling layers, pain\u002Fdelight moments, and channel transitions","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\u002Fcustomer-lifecycle\u002Fclaude\u002Fjourney-map\u002Fframeworks\u002Fexperience-map\u002Farchive\u002Fv0.3\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32],"map","experience map","research","v0","channel","thinking","journey","delight","transitions","2026-11-10 10:12:30",false,"---\nname: experience-map\ndescription: Adaptive Path experience map — emotional arc with doing\u002Fthinking\u002Ffeeling layers, pain\u002Fdelight moments, and channel transitions\ntype: research\nversion: v0.3\ninvocation: sub-skill\nparent: journey-map\n---\n\n## Pack Availability Guard\n\nBefore telling the user to run a skill from another project-local pack, check `.agents\u002Fproject.json.enabled_packs`. If the target pack is not enabled, recommend `\u002Fpack install \u003Cpack>` inside Claude Code, or `npx skillpacks install \u003Cpack>` from the project shell, instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# Experience Map — Adaptive Path Analysis\n\n## Report-First Approval Gate\n\nDefault to scope-first approval: before synthesized research, inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions in a `review` alignment page plus a concise conversation summary.\n\nDo not perform synthesized research, rank candidates, make recommendations, or write working packets or canonical deliverables until final compiled YAML approves the research scope. Minimal pre-approval discovery may identify available files, source categories, and open questions; label it as scope evidence, not findings.\n\nAfter approved research-scope YAML, perform the research and write only the non-canonical working packet defined in the staged workflow. Then update the `review` alignment page with findings and stop again for feedback-only YAML or final compiled YAML artifact approval before creating or updating canonical research, spec, or task files.\n\nDo not include `Recommended next skill`, `Recommended next command`, or downstream routing language. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.\n\n## Staged Research Workflow\n\nUse this staged workflow for synthesized research or report outputs that would create or update canonical research, spec, or task files.\n\n1. **Stage 1 - Scope discovery and approval.** Inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions. Build the `review` HTML alignment page before synthesized research. The page must render the proposed scope, available source categories, known context, assumptions\u002Fconfidence, proposed working-packet and canonical output paths, and research-scope approval gates. Stop for final compiled YAML approval of the research scope. Do not perform synthesized research, rank candidates, make recommendations, or write working packets, canonical research, spec, or task files in Stage 1.\n2. **Stage 2 - Research and artifact review.** Only after approved research-scope YAML with no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback, perform the synthesized research, run required source\u002Fcode checks, and write only a non-canonical working packet: flat mode uses `research\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`; product-path mode uses `research\u002F{slug}\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`. Replace `\u003Cskill>` with this skill's `name` value. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet. Update the `review` HTML alignment page with the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and artifact approval gates. Stop for either feedback-only YAML or final compiled YAML. Feedback-only YAML revises the working packet and page, then remains in Stage 2.\n3. **Stage 3 - Finalize approved artifacts.** Consume final compiled YAML for artifact approval only when it has no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet to `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-working-path>`, remove the active working packet, write the approved canonical artifacts to the unchanged output paths below, and convert the alignment page to `confirmed` with the approval record preserved.\n\nCanonical output paths remain unchanged. Search logs and other supporting evidence remain allowed only where this skill's output contract already requires them.\n\n## Evidence And Feedback Handling\n\nTreat user feedback as input to evaluate, not as automatic ground truth.\n\n- For factual, evidentiary, technical, or source-backed claims: verify against available evidence. Push back clearly and cite the evidence when the user appears to misunderstand.\n- For taste, prioritization, or subjective judgment calls: weigh user feedback heavily and adapt unless it conflicts with verified evidence.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Prerequisites\n\n- **Hard**: `research\u002Ficp.md` (or `research\u002F{slug}\u002Ficp.md`) must exist. If not, tell the user to run `\u002Fcustomer-discovery` first and stop.\n- **Soft**: `research\u002Fcompetitive-analysis.md`, `research\u002Fcustomer-feedback.md`, specs, and codebase context when available.\n\n## Process\n\n### 0. Product-Path Scope Resolution\n\nResolve research scope by product path before using code or app structure as a hint:\n\n1. If `$ARGUMENTS` names a non-archived `research\u002F{slug}\u002F` directory or a product-path ID whose `scope_path` points there, use that path. Treat `{slug}` as the product\u002Fapp name, not the ICP, audience, or segment label.\n2. If `$ARGUMENTS` names only `research\u002F_archive\u002F{slug}\u002F` or a manifest entry with `status: archived` or legacy `status: abandoned`, stop and warn that the path is archived; do not write or update scoped outputs there.\n3. Read `research\u002F.progress.yaml` when present. Normalize legacy `active_path` to `active_paths` on read and write back `active_paths` on manifest updates. Treat legacy `abandoned` as `archived`; exclude `archived`, `abandoned`, `deferred`, `revisit_candidate`, `promoted`, and any `scope_path` under `research\u002F_archive\u002F` from active target selection.\n4. If active product paths exist in the manifest, use those paths. If multiple active paths exist, ask which one to target unless this skill explicitly supports cross-path output.\n5. If no active manifest target exists, list non-archived product directories under `research\u002F`, excluding `research\u002F_archive\u002F` and dot directories. Auto-select only when exactly one exists; ask when multiple exist.\n6. If no product directories exist, use flat `research\u002F` single-product mode.\n7. Detect monorepo\u002Fapp\u002Fpackage structure only as a secondary hint.\n\nWhen product path `{slug}` is active, read and write research under `research\u002F{slug}\u002F`, specs under `specs\u002F{slug}\u002F`.\n\n### 1. Load Context\n\n- Read `research\u002Ficp.md` — ICP segments, pain points, trigger events\n- Read `research\u002Fcompetitive-analysis.md` if it exists\n- Read `research\u002Fcustomer-feedback.md` if it exists — emotional language, satisfaction drivers\n- Read CLAUDE.md, README for product context\n\n### 2. Define Experience Phases\n\nMap the end-to-end experience across phases that span the full lifecycle, not just the product interaction. Typical phases: awareness, research, first contact, onboarding, core usage, deepening, advocacy\u002Fdeparture.\n\n### 3. Map Doing Layer\n\nFor each phase, document what the person is actively doing:\n- Actions taken (searching, comparing, signing up, configuring, using features)\n- Tools and channels used\n- Time spent per action\n- Frequency and patterns\n\n### 4. Map Thinking Layer\n\nFor each phase, document what the person is thinking:\n- Questions they're asking themselves\n- Comparisons and evaluations they're making\n- Mental models they're building\n- Expectations forming and shifting\n\n### 5. Map Feeling Layer\n\nFor each phase, document the emotional state:\n- Dominant emotion (frustrated, curious, confident, anxious, delighted)\n- Emotional intensity (high\u002Fmedium\u002Flow)\n- Emotional trajectory (rising, falling, stable)\n- Trigger for emotional shifts\n\n### 6. Identify Pain and Delight Moments\n\nAcross all phases, identify:\n- **Pain moments**: where negative emotion peaks — frustration, confusion, abandonment risk\n- **Delight moments**: where positive emotion peaks — aha moments, unexpected value, mastery\n- **Indifference zones**: where the experience is flat and forgettable\n- **Channel transitions**: moments where the user switches between channels, devices, or contexts (these are high-friction by default)\n\n### 7. Plot the Emotional Arc\n\nCreate the emotional journey curve:\n- X-axis: experience phases (time\u002Fsequence)\n- Y-axis: emotional valence (negative ↔ positive)\n- Mark pain points, delight moments, and channel transitions on the curve\n- Identify the overall arc shape (valley-then-peak, steady decline, roller-coaster, etc.)\n\n### 8. Validate with User\n\nPresent the experience map and emotional arc. Ask for corrections, missing phases, and product-specific context.\n\n## Output\n\n### `research\u002Fjourney-map-experience-map.md` (or `research\u002F{slug}\u002Fjourney-map-experience-map.md`)\n\n```markdown\n# Experience Map\n\n> Based on: research\u002Ficp.md[, other evidence]\n> Date: [current date]\n> Methodology: Adaptive Path Experience Map\n\n## Experience Phases\n\n| Phase | Doing | Thinking | Feeling | Intensity |\n|-------|-------|----------|---------|-----------|\n| [phase] | [actions] | [thoughts] | [emotion] | High\u002FMedium\u002FLow |\n\n## Emotional Arc\n\n[Narrative description of the emotional trajectory across phases]\n\n## Pain Moments\n\n| Phase | Pain Point | Emotion | Intensity | Evidence |\n|-------|-----------|---------|-----------|----------|\n| [phase] | [description] | [emotion] | High\u002FMedium\u002FLow | [source] |\n\n## Delight Moments\n\n| Phase | Delight Point | Emotion | Intensity | Evidence |\n|-------|--------------|---------|-----------|----------|\n| [phase] | [description] | [emotion] | High\u002FMedium\u002FLow | [source] |\n\n## Channel Transitions\n\n| From | To | Phase | Friction Level | Evidence |\n|------|-----|-------|---------------|----------|\n| [channel] | [channel] | [phase] | High\u002FMedium\u002FLow | [source] |\n\n## Evidence Matrix\n\n| Claim | Evidence Source | Evidence Type | Confidence |\n|-------|---------------|---------------|------------|\n| [claim] | [source] | Observed\u002FInferred\u002FHypothesized | High\u002FMedium\u002FLow |\n```\n\n## Constraints\n\n- Ground every experience element in ICP, research, specs, feedback, or codebase evidence.\n- Do not prescribe UI or architecture — describe the experience, not the solution.\n- Present findings before writing.\n- Do not overwrite existing output without asking the user first.\n- This is a sub-skill — do not emit next-step routing.\n\n## Alignment Page\n\nWhen this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page following `ALIGNMENT-PAGE.md` in this skill's directory. Output: `alignment\u002Fexperience-map-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n","## Pack Availability Guard\n\nBefore telling the user to run a skill from another project-local pack, check `.agents\u002Fproject.json.enabled_packs`. If the target pack is not enabled, recommend `\u002Fpack install \u003Cpack>` inside Claude Code, or `npx skillpacks install \u003Cpack>` from the project shell, instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# Experience Map — Adaptive Path Analysis\n\n## Report-First Approval Gate\n\nDefault to scope-first approval: before synthesized research, inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions in a `review` alignment page plus a concise conversation summary.\n\nDo not perform synthesized research, rank candidates, make recommendations, or write working packets or canonical deliverables until final compiled YAML approves the research scope. Minimal pre-approval discovery may identify available files, source categories, and open questions; label it as scope evidence, not findings.\n\nAfter approved research-scope YAML, perform the research and write only the non-canonical working packet defined in the staged workflow. Then update the `review` alignment page with findings and stop again for feedback-only YAML or final compiled YAML artifact approval before creating or updating canonical research, spec, or task files.\n\nDo not include `Recommended next skill`, `Recommended next command`, or downstream routing language. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.\n\n## Staged Research Workflow\n\nUse this staged workflow for synthesized research or report outputs that would create or update canonical research, spec, or task files.\n\n1. **Stage 1 - Scope discovery and approval.** Inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions. Build the `review` HTML alignment page before synthesized research. The page must render the proposed scope, available source categories, known context, assumptions\u002Fconfidence, proposed working-packet and canonical output paths, and research-scope approval gates. Stop for final compiled YAML approval of the research scope. Do not perform synthesized research, rank candidates, make recommendations, or write working packets, canonical research, spec, or task files in Stage 1.\n2. **Stage 2 - Research and artifact review.** Only after approved research-scope YAML with no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback, perform the synthesized research, run required source\u002Fcode checks, and write only a non-canonical working packet: flat mode uses `research\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`; product-path mode uses `research\u002F{slug}\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`. Replace `\u003Cskill>` with this skill's `name` value. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet. Update the `review` HTML alignment page with the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and artifact approval gates. Stop for either feedback-only YAML or final compiled YAML. Feedback-only YAML revises the working packet and page, then remains in Stage 2.\n3. **Stage 3 - Finalize approved artifacts.** Consume final compiled YAML for artifact approval only when it has no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet to `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-working-path>`, remove the active working packet, write the approved canonical artifacts to the unchanged output paths below, and convert the alignment page to `confirmed` with the approval record preserved.\n\nCanonical output paths remain unchanged. Search logs and other supporting evidence remain allowed only where this skill's output contract already requires them.\n\n## Evidence And Feedback Handling\n\nTreat user feedback as input to evaluate, not as automatic ground truth.\n\n- For factual, evidentiary, technical, or source-backed claims: verify against available evidence. Push back clearly and cite the evidence when the user appears to misunderstand.\n- For taste, prioritization, or subjective judgment calls: weigh user feedback heavily and adapt unless it conflicts with verified evidence.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Prerequisites\n\n- **Hard**: `research\u002Ficp.md` (or `research\u002F{slug}\u002Ficp.md`) must exist. If not, tell the user to run `\u002Fcustomer-discovery` first and stop.\n- **Soft**: `research\u002Fcompetitive-analysis.md`, `research\u002Fcustomer-feedback.md`, specs, and codebase context when available.\n\n## Process\n\n### 0. Product-Path Scope Resolution\n\nResolve research scope by product path before using code or app structure as a hint:\n\n1. If `$ARGUMENTS` names a non-archived `research\u002F{slug}\u002F` directory or a product-path ID whose `scope_path` points there, use that path. Treat `{slug}` as the product\u002Fapp name, not the ICP, audience, or segment label.\n2. If `$ARGUMENTS` names only `research\u002F_archive\u002F{slug}\u002F` or a manifest entry with `status: archived` or legacy `status: abandoned`, stop and warn that the path is archived; do not write or update scoped outputs there.\n3. Read `research\u002F.progress.yaml` when present. Normalize legacy `active_path` to `active_paths` on read and write back `active_paths` on manifest updates. Treat legacy `abandoned` as `archived`; exclude `archived`, `abandoned`, `deferred`, `revisit_candidate`, `promoted`, and any `scope_path` under `research\u002F_archive\u002F` from active target selection.\n4. If active product paths exist in the manifest, use those paths. If multiple active paths exist, ask which one to target unless this skill explicitly supports cross-path output.\n5. If no active manifest target exists, list non-archived product directories under `research\u002F`, excluding `research\u002F_archive\u002F` and dot directories. Auto-select only when exactly one exists; ask when multiple exist.\n6. If no product directories exist, use flat `research\u002F` single-product mode.\n7. Detect monorepo\u002Fapp\u002Fpackage structure only as a secondary hint.\n\nWhen product path `{slug}` is active, read and write research under `research\u002F{slug}\u002F`, specs under `specs\u002F{slug}\u002F`.\n\n### 1. Load Context\n\n- Read `research\u002Ficp.md` — ICP segments, pain points, trigger events\n- Read `research\u002Fcompetitive-analysis.md` if it exists\n- Read `research\u002Fcustomer-feedback.md` if it exists — emotional language, satisfaction drivers\n- Read CLAUDE.md, README for product context\n\n### 2. Define Experience Phases\n\nMap the end-to-end experience across phases that span the full lifecycle, not just the product interaction. Typical phases: awareness, research, first contact, onboarding, core usage, deepening, advocacy\u002Fdeparture.\n\n### 3. Map Doing Layer\n\nFor each phase, document what the person is actively doing:\n- Actions taken (searching, comparing, signing up, configuring, using features)\n- Tools and channels used\n- Time spent per action\n- Frequency and patterns\n\n### 4. Map Thinking Layer\n\nFor each phase, document what the person is thinking:\n- Questions they're asking themselves\n- Comparisons and evaluations they're making\n- Mental models they're building\n- Expectations forming and shifting\n\n### 5. Map Feeling Layer\n\nFor each phase, document the emotional state:\n- Dominant emotion (frustrated, curious, confident, anxious, delighted)\n- Emotional intensity (high\u002Fmedium\u002Flow)\n- Emotional trajectory (rising, falling, stable)\n- Trigger for emotional shifts\n\n### 6. Identify Pain and Delight Moments\n\nAcross all phases, identify:\n- **Pain moments**: where negative emotion peaks — frustration, confusion, abandonment risk\n- **Delight moments**: where positive emotion peaks — aha moments, unexpected value, mastery\n- **Indifference zones**: where the experience is flat and forgettable\n- **Channel transitions**: moments where the user switches between channels, devices, or contexts (these are high-friction by default)\n\n### 7. Plot the Emotional Arc\n\nCreate the emotional journey curve:\n- X-axis: experience phases (time\u002Fsequence)\n- Y-axis: emotional valence (negative ↔ positive)\n- Mark pain points, delight moments, and channel transitions on the curve\n- Identify the overall arc shape (valley-then-peak, steady decline, roller-coaster, etc.)\n\n### 8. Validate with User\n\nPresent the experience map and emotional arc. Ask for corrections, missing phases, and product-specific context.\n\n## Output\n\n### `research\u002Fjourney-map-experience-map.md` (or `research\u002F{slug}\u002Fjourney-map-experience-map.md`)\n\n```markdown\n# Experience Map\n\n> Based on: research\u002Ficp.md[, other evidence]\n> Date: [current date]\n> Methodology: Adaptive Path Experience Map\n\n## Experience Phases\n\n| Phase | Doing | Thinking | Feeling | Intensity |\n|-------|-------|----------|---------|-----------|\n| [phase] | [actions] | [thoughts] | [emotion] | High\u002FMedium\u002FLow |\n\n## Emotional Arc\n\n[Narrative description of the emotional trajectory across phases]\n\n## Pain Moments\n\n| Phase | Pain Point | Emotion | Intensity | Evidence |\n|-------|-----------|---------|-----------|----------|\n| [phase] | [description] | [emotion] | High\u002FMedium\u002FLow | [source] |\n\n## Delight Moments\n\n| Phase | Delight Point | Emotion | Intensity | Evidence |\n|-------|--------------|---------|-----------|----------|\n| [phase] | [description] | [emotion] | High\u002FMedium\u002FLow | [source] |\n\n## Channel Transitions\n\n| From | To | Phase | Friction Level | Evidence |\n|------|-----|-------|---------------|----------|\n| [channel] | [channel] | [phase] | High\u002FMedium\u002FLow | [source] |\n\n## Evidence Matrix\n\n| Claim | Evidence Source | Evidence Type | Confidence |\n|-------|---------------|---------------|------------|\n| [claim] | [source] | Observed\u002FInferred\u002FHypothesized | High\u002FMedium\u002FLow |\n```\n\n## Constraints\n\n- Ground every experience element in ICP, research, specs, feedback, or codebase evidence.\n- Do not prescribe UI or architecture — describe the experience, not the solution.\n- Present findings before writing.\n- Do not overwrite existing output without asking the user first.\n- This is a sub-skill — do not emit next-step routing.\n\n## Alignment Page\n\nWhen this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page following `ALIGNMENT-PAGE.md` in this skill's directory. Output: `alignment\u002Fexperience-map-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n",{"name":5,"type":26,"parent":38,"version":39,"invocation":40,"description":7},"journey-map","v0.3","sub-skill","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fcustomer-lifecycle\u002Fclaude\u002Fjourney-map\u002Fframeworks\u002Fexperience-map\u002Farchive\u002Fv0.3",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":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill experience-map",{"tool":57,"command":58},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill experience-map",{"tool":60,"command":61},"pnpm","pnpm dlx skills add GeorgeQLe\u002Fagentic-skills --skill 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