[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D7G801CFAMMGEZPESK7D8Q":3,"skill-same:01M6D7G801CFAMMGEZPESK7D8Q":67},{"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":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":50,"ownerDescription":51,"updatedAt":52,"install":53,"resources":66},"01M6D7G801CFAMMGEZPESK7D8Q","jtbd-positioning",null,"Jobs-to-be-Done positioning analysis — identify primary job, map functional\u002Fsocial\u002Femotional dimensions, position around job outcome","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\u002Fbusiness-research\u002Fcodex\u002Fpositioning\u002Fframeworks\u002Fjtbd-positioning\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",[24,25,26,27,28,29,30,31,32,33,34,35],"jtbd","positioning","jtbd positioning","research","analysis","outcome","v0","jobs","social","dimensions","done","map","2026-11-10 10:12:30",false,"---\nname: jtbd-positioning\ndescription: Jobs-to-be-Done positioning analysis — identify primary job, map functional\u002Fsocial\u002Femotional dimensions, position around job outcome\ntype: research\nversion: v0.3\ninvocation: sub-skill\nparent: positioning\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 `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# JTBD Positioning — Jobs-to-be-Done Analysis\n\nInvoke as `$jtbd-positioning`.\n\n## Report-First Approval Gate\n\nDefault to report-only: present findings, evidence coverage, assumptions, recommended artifact path, and proposed file changes in a pre-approval alignment page plus a concise conversation summary for user approval before creating or updating canonical research files.\n\nDo not write or overwrite synthesized deliverables until the user explicitly approves. Raw evidence capture may be persisted before analysis when reproducibility requires it.\n\nWhen stopping for approval, build and attempt to open the alignment preview page first, then ask the user to review it and approve, question, or request adjustments. Do not include `Recommended next skill`, `Recommended next command`, or downstream routing language until after final compiled YAML has been provided and the approved artifacts have 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 - Research and clarify.** Perform the research, run required source\u002Fcode checks, and ask any needed clarification questions. 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. Do not create or update canonical research, spec, or task files in Stage 1. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet.\n2. **Stage 2 - Review alignment.** Consume the working packet and build the `review` HTML alignment page. The page must render the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and 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 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. If the user appears to misunderstand the evidence or states something factually incorrect, push back clearly and cite the evidence. Do not rewrite findings merely to agree.\n- For taste, brand, positioning preference, risk appetite, prioritization, or other subjective judgment calls: weigh user feedback heavily and adapt the recommendation unless it conflicts with verified evidence.\n- When feedback mixes facts and preference, separate them explicitly: correct the factual part, then incorporate the preference where it is a legitimate judgment call.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Purpose\n\nApplies Clayton Christensen's Jobs-to-be-Done framework to positioning. Instead of positioning around features or competitive differences, positions the product around the *job outcome* the customer is trying to achieve. Produces an intermediate artifact that feeds into the parent `$positioning` synthesis.\n\n## Prerequisites\n\n- **Hard**: `research\u002Ficp.md` (or `research\u002F{slug}\u002Ficp.md`) must exist. If not, tell the user to run `$icp` first and stop.\n- **Hard**: `research\u002Fcompetitive-analysis.md` (or `research\u002F{slug}\u002Fcompetitive-analysis.md`) must exist. If not, tell the user to run `$competitive-analysis` first and stop.\n- **Hard**: `research\u002Fjourney-map.md` (or `research\u002F{slug}\u002Fjourney-map.md`) must exist. If not, tell the user to run `$journey-map` first and stop.\n- **Soft**: Read if they exist:\n  - `research\u002Fcustomer-feedback.md` — real language about what customers hire the product to do\n  - `research\u002Fpositioning.md` — existing positioning to build upon\n\n## 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. Suggest creating a missing `research\u002F{slug}\u002F` product path when code clearly exposes an app, but do not require code or monorepo detection before using `research\u002F{slug}\u002F`.\n\nWhen product path `{slug}` is active, read and write research under `research\u002F{slug}\u002F`, specs under `specs\u002F{slug}\u002F`, and treat top-level `research\u002F*.md` files as flat-mode documents or cross-path summaries.\n\n## Process\n\n### 1. Load Context\n\n- Read `research\u002Ficp.md` — segments, pain points, trigger events\n- Read `research\u002Fcompetitive-analysis.md` — how alternatives frame themselves\n- Read `research\u002Fjourney-map.md` — where value is delivered, switching triggers\n- Read `research\u002Fcustomer-feedback.md` if it exists — actual hiring\u002Ffiring language\n\n### 2. Identify the Primary Job\n\nResearch and determine the core job the customer is trying to get done:\n\n- Use WebSearch with 3-5 queries targeting job language in the domain\n- Distinguish the **core functional job** from related consumption-chain jobs\n- Frame as: \"When [situation], I want to [motivation], so I can [expected outcome]\"\n- Identify the job at the right level of abstraction — not too broad (meaningless), not too narrow (feature-level)\n\nValidate with user. If the session is already in Plan mode, prefer `request_user_input`; otherwise ask in plain text:\n- \"Here is the primary job the evidence supports. Is the abstraction level right? Are there competing job framings I should consider?\"\n\n### 3. Map Job Dimensions\n\nFor the primary job, map three dimensions:\n\n**Functional dimension** — What the customer is practically trying to accomplish:\n- Core steps in getting the job done\n- Speed, accuracy, reliability requirements\n- Where current solutions break down\n\n**Social dimension** — How the customer wants to be perceived:\n- Professional identity alignment\n- Team\u002Fpeer perception\n- Status and credibility implications\n\n**Emotional dimension** — How the customer wants to feel:\n- Confidence and control\n- Reduced anxiety or frustration\n- Sense of progress\n\n### 4. Identify Job Outcome Metrics\n\nDefine success metrics from the customer's perspective (not product metrics):\n- **Speed**: How quickly can the job be completed?\n- **Accuracy**: How reliably does the job get done right?\n- **Effort**: How much work does the customer have to put in?\n- **Satisfaction**: How good does the outcome feel?\n\nMap where alternatives fail on these metrics.\n\n### 5. Position Around Job Outcome\n\nSynthesize positioning that frames the product as the best way to achieve the desired job outcome:\n\n- What is the job the product is hired for?\n- What makes this product uniquely suited to the job?\n- What outcome does the customer achieve that alternatives cannot deliver?\n- Which dimension (functional\u002Fsocial\u002Femotional) is the strongest positioning angle?\n\nValidate with user. If the session is already in Plan mode, prefer `request_user_input`; otherwise ask in plain text:\n- \"This JTBD positioning emphasizes [dimension]. Does that match where you see the strongest pull from customers?\"\n\n### 6. Write Output\n\nOnly after user approval.\n\n## Output\n\n### `research\u002Fpositioning-jtbd.md` (or `research\u002F{slug}\u002Fpositioning-jtbd.md`)\n\n```markdown\n# JTBD Positioning Analysis\n\n> Based on: research\u002Ficp.md, research\u002Fcompetitive-analysis.md, research\u002Fjourney-map.md\n> Date: [current date]\n> Methodology: Jobs-to-be-Done (Clayton Christensen \u002F Tony Ulwick)\n\n## Primary Job Statement\n\nWhen [situation], I want to [motivation], so I can [expected outcome].\n\n## Job Dimensions\n\n### Functional\n| Step | Current Solution | Pain Point | Our Advantage |\n|------|-----------------|------------|---------------|\n| [step] | [how done today] | [what breaks] | [how we're better] |\n\n### Social\n- [social dimension 1]\n- [social dimension 2]\n\n### Emotional\n- [emotional dimension 1]\n- [emotional dimension 2]\n\n## Outcome Metrics\n\n| Metric | Customer Need | Alternative Performance | Our Performance |\n|--------|--------------|------------------------|-----------------|\n| Speed | [need] | [how alternatives do] | [how we do] |\n| Accuracy | [need] | [performance] | [performance] |\n| Effort | [need] | [performance] | [performance] |\n\n## Positioning Angle\n\n**Lead dimension**: [Functional \u002F Social \u002F Emotional]\n**Job outcome framing**: [one sentence: how to position around the job outcome]\n**Evidence strength**: [Strong \u002F Moderate \u002F Weak — with justification]\n\n## Competitive Alternatives by Job\n\n| Alternative | Which Job It Serves | Where It Fails |\n|-------------|--------------------|--------------------|\n| [alternative] | [job framing] | [gap] |\n\n## Implications for Positioning Synthesis\n\n[How this JTBD analysis should influence the final positioning statement — what it suggests for market category, target segment, and key differentiator]\n```\n\n## Task Classification\n\nWhen this skill produces follow-up work, file it by execution semantics:\n\n- Immediately actionable work goes in `tasks\u002Ftodo.md`.\n- Human-only external actions go in `tasks\u002Fmanual-todo.md` with blocking\u002Fdependency annotations.\n- Condition-gated records go in `tasks\u002Frecord-todo.md`.\n- Cadence-based reviews go in `tasks\u002Frecurring-todo.md`.\n\n## Constraints\n\n- **Intermediate artifact only.** This produces `research\u002Fpositioning-jtbd.md`, not the canonical `research\u002Fpositioning.md`.\n- **Requires journey evidence.** JTBD positioning without understanding the customer journey is speculative.\n- **Job abstraction level matters.** Challenge yourself: is the job too broad or too narrow?\n- **Present before writing.** Never write output files until findings are validated.\n- **Customer language preferred.** Use actual customer words from feedback\u002Finterviews when available.\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\u002Fjtbd-positioning-{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 `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# JTBD Positioning — Jobs-to-be-Done Analysis\n\nInvoke as `$jtbd-positioning`.\n\n## Report-First Approval Gate\n\nDefault to report-only: present findings, evidence coverage, assumptions, recommended artifact path, and proposed file changes in a pre-approval alignment page plus a concise conversation summary for user approval before creating or updating canonical research files.\n\nDo not write or overwrite synthesized deliverables until the user explicitly approves. Raw evidence capture may be persisted before analysis when reproducibility requires it.\n\nWhen stopping for approval, build and attempt to open the alignment preview page first, then ask the user to review it and approve, question, or request adjustments. Do not include `Recommended next skill`, `Recommended next command`, or downstream routing language until after final compiled YAML has been provided and the approved artifacts have 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 - Research and clarify.** Perform the research, run required source\u002Fcode checks, and ask any needed clarification questions. 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. Do not create or update canonical research, spec, or task files in Stage 1. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet.\n2. **Stage 2 - Review alignment.** Consume the working packet and build the `review` HTML alignment page. The page must render the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and 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 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. If the user appears to misunderstand the evidence or states something factually incorrect, push back clearly and cite the evidence. Do not rewrite findings merely to agree.\n- For taste, brand, positioning preference, risk appetite, prioritization, or other subjective judgment calls: weigh user feedback heavily and adapt the recommendation unless it conflicts with verified evidence.\n- When feedback mixes facts and preference, separate them explicitly: correct the factual part, then incorporate the preference where it is a legitimate judgment call.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Purpose\n\nApplies Clayton Christensen's Jobs-to-be-Done framework to positioning. Instead of positioning around features or competitive differences, positions the product around the *job outcome* the customer is trying to achieve. Produces an intermediate artifact that feeds into the parent `$positioning` synthesis.\n\n## Prerequisites\n\n- **Hard**: `research\u002Ficp.md` (or `research\u002F{slug}\u002Ficp.md`) must exist. If not, tell the user to run `$icp` first and stop.\n- **Hard**: `research\u002Fcompetitive-analysis.md` (or `research\u002F{slug}\u002Fcompetitive-analysis.md`) must exist. If not, tell the user to run `$competitive-analysis` first and stop.\n- **Hard**: `research\u002Fjourney-map.md` (or `research\u002F{slug}\u002Fjourney-map.md`) must exist. If not, tell the user to run `$journey-map` first and stop.\n- **Soft**: Read if they exist:\n  - `research\u002Fcustomer-feedback.md` — real language about what customers hire the product to do\n  - `research\u002Fpositioning.md` — existing positioning to build upon\n\n## 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. Suggest creating a missing `research\u002F{slug}\u002F` product path when code clearly exposes an app, but do not require code or monorepo detection before using `research\u002F{slug}\u002F`.\n\nWhen product path `{slug}` is active, read and write research under `research\u002F{slug}\u002F`, specs under `specs\u002F{slug}\u002F`, and treat top-level `research\u002F*.md` files as flat-mode documents or cross-path summaries.\n\n## Process\n\n### 1. Load Context\n\n- Read `research\u002Ficp.md` — segments, pain points, trigger events\n- Read `research\u002Fcompetitive-analysis.md` — how alternatives frame themselves\n- Read `research\u002Fjourney-map.md` — where value is delivered, switching triggers\n- Read `research\u002Fcustomer-feedback.md` if it exists — actual hiring\u002Ffiring language\n\n### 2. Identify the Primary Job\n\nResearch and determine the core job the customer is trying to get done:\n\n- Use WebSearch with 3-5 queries targeting job language in the domain\n- Distinguish the **core functional job** from related consumption-chain jobs\n- Frame as: \"When [situation], I want to [motivation], so I can [expected outcome]\"\n- Identify the job at the right level of abstraction — not too broad (meaningless), not too narrow (feature-level)\n\nValidate with user. If the session is already in Plan mode, prefer `request_user_input`; otherwise ask in plain text:\n- \"Here is the primary job the evidence supports. Is the abstraction level right? Are there competing job framings I should consider?\"\n\n### 3. Map Job Dimensions\n\nFor the primary job, map three dimensions:\n\n**Functional dimension** — What the customer is practically trying to accomplish:\n- Core steps in getting the job done\n- Speed, accuracy, reliability requirements\n- Where current solutions break down\n\n**Social dimension** — How the customer wants to be perceived:\n- Professional identity alignment\n- Team\u002Fpeer perception\n- Status and credibility implications\n\n**Emotional dimension** — How the customer wants to feel:\n- Confidence and control\n- Reduced anxiety or frustration\n- Sense of progress\n\n### 4. Identify Job Outcome Metrics\n\nDefine success metrics from the customer's perspective (not product metrics):\n- **Speed**: How quickly can the job be completed?\n- **Accuracy**: How reliably does the job get done right?\n- **Effort**: How much work does the customer have to put in?\n- **Satisfaction**: How good does the outcome feel?\n\nMap where alternatives fail on these metrics.\n\n### 5. Position Around Job Outcome\n\nSynthesize positioning that frames the product as the best way to achieve the desired job outcome:\n\n- What is the job the product is hired for?\n- What makes this product uniquely suited to the job?\n- What outcome does the customer achieve that alternatives cannot deliver?\n- Which dimension (functional\u002Fsocial\u002Femotional) is the strongest positioning angle?\n\nValidate with user. If the session is already in Plan mode, prefer `request_user_input`; otherwise ask in plain text:\n- \"This JTBD positioning emphasizes [dimension]. Does that match where you see the strongest pull from customers?\"\n\n### 6. Write Output\n\nOnly after user approval.\n\n## Output\n\n### `research\u002Fpositioning-jtbd.md` (or `research\u002F{slug}\u002Fpositioning-jtbd.md`)\n\n```markdown\n# JTBD Positioning Analysis\n\n> Based on: research\u002Ficp.md, research\u002Fcompetitive-analysis.md, research\u002Fjourney-map.md\n> Date: [current date]\n> Methodology: Jobs-to-be-Done (Clayton Christensen \u002F Tony Ulwick)\n\n## Primary Job Statement\n\nWhen [situation], I want to [motivation], so I can [expected outcome].\n\n## Job Dimensions\n\n### Functional\n| Step | Current Solution | Pain Point | Our Advantage |\n|------|-----------------|------------|---------------|\n| [step] | [how done today] | [what breaks] | [how we're better] |\n\n### Social\n- [social dimension 1]\n- [social dimension 2]\n\n### Emotional\n- [emotional dimension 1]\n- [emotional dimension 2]\n\n## Outcome Metrics\n\n| Metric | Customer Need | Alternative Performance | Our Performance |\n|--------|--------------|------------------------|-----------------|\n| Speed | [need] | [how alternatives do] | [how we do] |\n| Accuracy | [need] | [performance] | [performance] |\n| Effort | [need] | [performance] | [performance] |\n\n## Positioning Angle\n\n**Lead dimension**: [Functional \u002F Social \u002F Emotional]\n**Job outcome framing**: [one sentence: how to position around the job outcome]\n**Evidence strength**: [Strong \u002F Moderate \u002F Weak — with justification]\n\n## Competitive Alternatives by Job\n\n| Alternative | Which Job It Serves | Where It Fails |\n|-------------|--------------------|--------------------|\n| [alternative] | [job framing] | [gap] |\n\n## Implications for Positioning Synthesis\n\n[How this JTBD analysis should influence the final positioning statement — what it suggests for market category, target segment, and key differentiator]\n```\n\n## Task Classification\n\nWhen this skill produces follow-up work, file it by execution semantics:\n\n- Immediately actionable work goes in `tasks\u002Ftodo.md`.\n- Human-only external actions go in `tasks\u002Fmanual-todo.md` with blocking\u002Fdependency annotations.\n- Condition-gated records go in `tasks\u002Frecord-todo.md`.\n- Cadence-based reviews go in `tasks\u002Frecurring-todo.md`.\n\n## Constraints\n\n- **Intermediate artifact only.** This produces `research\u002Fpositioning-jtbd.md`, not the canonical `research\u002Fpositioning.md`.\n- **Requires journey evidence.** JTBD positioning without understanding the customer journey is speculative.\n- **Job abstraction level matters.** Challenge yourself: is the job too broad or too narrow?\n- **Present before writing.** Never write output files until findings are validated.\n- **Customer language preferred.** Use actual customer words from feedback\u002Finterviews when available.\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\u002Fjtbd-positioning-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n",{"name":5,"type":27,"parent":25,"version":41,"invocation":42,"description":7},"v0.3","sub-skill","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fbusiness-research\u002Fcodex\u002Fpositioning\u002Fframeworks\u002Fjtbd-positioning\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":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill jtbd-positioning",{"tool":59,"command":60},"bunx","bunx skills add 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