Imported from GeorgeQLe/agentic-skills (packs/business-research/codex/customer-feedback/archive/v0.2/SKILL.md). Install upstream with npx skills add GeorgeQLe/agentic-skills --skill v0.2. Copyright stays with the author.

Pack Availability Guard

Before telling the user to run a skill from another project-local pack, check .agents/project.json.enabled_packs. If the target pack is not enabled, recommend $pack install <pack> 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.

Customer Feedback — Ingest & Synthesize

Invoke as $customer-feedback.

Report-First Approval Gate

Default 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, spec, or task files.

Do not write or overwrite synthesized deliverables until the user explicitly approves, unless the user invoked an explicit write/update/fix mode or clearly asked to write files upfront. Raw evidence capture may be persisted before analysis when reproducibility requires it; report those raw paths separately and still gate synthesized research/report writes.

When 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. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.

Append-only skill that ingests customer feedback, categorizes findings against ICP and journey map, and maintains a running synthesis. Each run adds a session; the synthesis section regenerates across all sessions.

Soft Prerequisites

• Read research/icp.md (or research/{slug}/icp.md in product-path mode) if it exists — grounds categorization in ICP segments and pain points.
• Read research/journey-map.md (or research/{slug}/journey-map.md in product-path mode) if it exists — tags findings to journey stages.

These are not required. The skill works without them but categorization will be less precise.

Process

0. Product-Path Scope Resolution

Resolve research scope by product path before using code or app structure as a hint:

1. If $ARGUMENTS names a non-archived research/{slug}/ directory or a product-path ID whose scope_path points there, use that path. Treat {slug} as the product/app name, not the ICP, audience, or segment label.
2. If $ARGUMENTS names only research/_archive/{slug}/ 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.
3. Read research/.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/_archive/ from active target selection.
4. 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.
5. If no active manifest target exists, list non-archived product directories under research/, excluding research/_archive/ and dot directories. Auto-select only when exactly one exists; ask when multiple exist.
6. If no product directories exist, use flat research/ single-product mode.
7. Detect monorepo/app/package structure only as a secondary hint. Suggest creating a missing research/{slug}/ product path when code clearly exposes an app, but do not require code or monorepo detection before using research/{slug}/.

When product path {slug} is active, read and write research under research/{slug}/, specs under specs/{slug}/, and treat top-level research/*.md files as flat-mode documents or cross-path summaries.

1. Load Context

• Read research/icp.md (or research/{slug}/icp.md) if it exists — extract ICP segments, user profiles, pain points, value props
• Read research/journey-map.md (or research/{slug}/journey-map.md) if it exists — extract journey stages, use cases, critical moments
• Read research/customer-feedback.md (or research/{slug}/customer-feedback.md) if it exists — load all previous sessions for synthesis context

2. Ingest Feedback

Check $ARGUMENTS:

• File path provided: Read the file and use its contents as the feedback input
• Text provided: Use the argument text directly as feedback
• Empty: Ask the user to paste or describe the feedback. If the session is already in Plan mode and there are 2-3 concrete input-source choices, prefer request_user_input; otherwise ask in plain text.

Accept any format: interview notes, support tickets, survey responses, NPS comments, user testing observations, sales call notes, social media mentions, app store reviews.

3. Categorize Findings

For each distinct finding in the feedback:

1. Classification: One of:

   • Confirmed — validates an existing ICP assumption, pain point, or journey step
   • Wrong — contradicts an ICP assumption, pain point, or mapped journey
   • New — reveals something not captured in ICP or journey map

2. ICP Tag (when research/icp.md exists): Which ICP section does this relate to? (pain point, value prop, user profile, trigger event, etc.)

3. Journey Stage (when research/journey-map.md exists): Which journey stage does this touch? (discovery, evaluation, onboarding, aha moment, retention, etc.)

4. Severity: High / Medium / Low — based on how many users it affects and how strongly

5. Quote or Evidence: The specific words or behavior that support this finding

4. Present & Validate

Present the categorized findings to the user. If the session is already in Plan mode and there are 2-3 concrete validation choices, prefer request_user_input; otherwise ask in plain text:

• Show each finding with its classification, tags, and evidence
• Ask: "Does this categorization look right? Any findings I've miscategorized or missed?"
• If the user corrects anything, update before writing

5. Check Staleness Triggers

Count the number of Wrong and New findings across ALL sessions (including previous ones):

• If 3+ Wrong findings relate to ICP assumptions: recommend re-running $icp
• If 3+ Wrong findings relate to journey stages: recommend re-running $journey-map
• If 3+ New findings suggest an unserved segment: recommend re-running $icp

Display these recommendations after the categorized findings.

6. Populate Next Steps

Before writing, check which files exist and synthesis results to populate the ## Next Steps section contextually. Include a Recommended item (the single highest-impact next step given current project state) with a one-line reason, followed by Other options (2–4 alternatives). Use this format in the output:

Next Steps

Recommended: [recommended skill] — [one-line reason why this is the highest-impact next action given current state]

Other options:

• $skill — [description]
• ...

Recommendation priority (first applicable becomes the recommendation):

1. IF downstream impact is Major: recommend $reconcile-research — [N] conflicts found in downstream docs need resolution before other work
2. IF staleness alert for ICP: recommend $icp — feedback has invalidated key ICP assumptions that other research depends on
3. IF staleness alert for journey map: recommend $journey-map — real user behavior differs from mapped experience
4. IF 3+ New findings: recommend $brainstorm — newly revealed customer needs deserve solution exploration
5. IF no staleness alerts and no major findings: recommend $research-roadmap — check overall project status for the next priority

Other options (include all applicable items not chosen as recommended):

• IF staleness alert for ICP: $icp — Re-run discovery — feedback has invalidated key assumptions
• IF staleness alert for journey map: $journey-map — Re-map journeys — real behavior differs from mapped experience
• IF 3+ New findings: $brainstorm — Generate ideas for newly revealed customer needs
• IF New findings relate to a gap: $ux-variations [topic] — Explore UX solutions for the most impactful finding
• IF no staleness alerts: $research-roadmap — Check overall project status
• IF feedback came from experiment results: $assumption-tracker — Update assumption validation status with experiment findings
• IF 3+ research docs exist and no research/assumption-tracker.md: $assumption-tracker — Build the assumptions register to track what feedback is validating

Impact-aware adjustments:

• IF downstream impact is Minor: annotate relevant skill suggestions with "(stale — [brief description])"
• If downstream impact has not been classified yet, run the downstream impact check against the proposed output before selecting the final recommendation. Do not emit a Minor/Major impact recommendation speculatively.

7. Write Output

Only after the user validates, write to research/customer-feedback.md:

If the file doesn't exist: Create it with the structure below. If the file exists: Append the new session section, then regenerate the ## Synthesis section at the top.

8. Downstream Impact Check

After writing, check for downstream research documents that may be affected by what was just decided. Only check documents that exist on disk.

Downstream documents to check (use {slug}/ prefix when product-path scope is active):

• research/gtm.md
• research/monetization.md

For each existing downstream document:

1. Read it — focus on > Based on: header, ## Summary, and sections that reference concepts this skill just defined or changed
2. Identify specific conflicts: claims, assumptions, or references that contradict what was just decided. Examples:
   • Customer language or pain point framing in GTM messaging that feedback has invalidated
   • Pricing assumptions in monetization anchored to customer willingness-to-pay signals that have shifted
   • Channel strategy built on customer behavior patterns that new feedback contradicts
3. Note each conflict: downstream file, section, the stale claim (quote it), and what it should now say

Classify the impact:

• None: No downstream documents exist, or no conflicts found. Skip display entirely.
• Minor (1–2 small conflicts): Display conflicts to user inline.
• Major (3+ conflicts OR a foundational assumption changed — e.g., primary pain point invalidated, willingness-to-pay signals contradicted, key customer behavior pattern disproved): Display conflicts and strongly recommend $reconcile-research.

Display to the user after showing the written file confirmation. This should be quick — one read per downstream doc, scan for conflicts against key decisions. Not a deep reconciliation.

Output

research/customer-feedback.md (or research/{slug}/customer-feedback.md)

# Customer Feedback

> Last updated: [current date]
> Sessions: [total count]

## Synthesis

[Regenerated each run. Summarizes patterns across ALL sessions:]

### Confirmed Assumptions
[ICP and journey assumptions that feedback consistently validates]

### Invalidated Assumptions
[ICP and journey assumptions that feedback contradicts — with evidence count]

### New Discoveries
[Findings not captured in any existing research — potential ICP updates or new journey stages]

### Staleness Alerts
[If 3+ Wrong/New findings accumulated, list which research docs should be re-run and why]

<!-- Only include the Downstream Impact section when impact is Minor or Major. Omit entirely for None. -->
### Downstream Impact

> Checked: [list of downstream docs checked]
> Impact: Minor | Major

#### Conflicts Found

1. **research/[file].md** — [Section Name]
   - **Stale**: "[exact quote from downstream doc]"
   - **Now**: [what this skill's output says instead]

[For Major only:]
> **Recommended action**: Run `$reconcile-research` to audit and fix all affected downstream documents.

### Next Steps

**Recommended:** `$skill` — [one-line reason]

Other options:
- [conditional items from step 6 — only include items whose conditions are met]

---

## Feedback Session: [date]

> Source: [file path, "pasted text", or "interview"]
> ICP context: [yes/no — whether research/icp.md was loaded]
> Journey context: [yes/no — whether research/journey-map.md was loaded]

### Findings

| # | Finding | Classification | ICP Tag | Journey Stage | Severity |
|---|---------|---------------|---------|---------------|----------|
| 1 | [finding] | Confirmed/Wrong/New | [tag] | [stage] | H/M/L |

### Details

#### Finding 1: [title]
**Classification**: [Confirmed/Wrong/New]
**Evidence**: "[quote or observation]"
**ICP Tag**: [which ICP section]
**Journey Stage**: [which stage]
**Severity**: [High/Medium/Low]
**Implication**: [what this means for the product]

[Repeat for each finding]

---

[Previous sessions remain below, newest first]

Create the research/ directory if it doesn't exist.

Task Classification

When this skill produces follow-up work, file it by execution semantics:

• Immediately actionable implementation or documentation work goes in tasks/todo.md.
• Human-only external actions tied to automated steps go in tasks/manual-todo.md with _(blocks: Step N.X)_ or _(after: Step N.X)_; repo edits, SDK wiring, generated assets, local commands, tests, audits, and authenticated CLI/API work stay in tasks/todo.md.
• One-time condition-gated records, baselines, or future measurements go in tasks/record-todo.md with source, condition, non-blocking reason, evidence, and promotion rule.
• Cadence-based reviews, playtests, adoption checks, investor updates, retros, or docs-health checks go in tasks/recurring-todo.md with cadence, owner/agent, next due, evidence path, and escalation conditions.
• Do not put non-blocking records or recurring obligations in tasks/todo.md unless they have been explicitly promoted into current execution work.

Constraints

• Append-only. Never delete or overwrite previous sessions in research/customer-feedback.md (or research/{slug}/customer-feedback.md). Only the ## Synthesis section at the top is regenerated.
• Present before writing. Never write until the user validates the categorization.
• Tag to existing research. When ICP and journey map exist, every finding must be tagged. When they don't exist, skip tagging but note "no ICP/journey context" in the session header.
• Count across sessions. Staleness triggers are based on cumulative findings, not just the current session.
• Accept any format. The skill should handle messy, unstructured input gracefully.

Alignment Page

When 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/customer-feedback-{topic}.html.

Default Shipping Contract

Follow the shared shipping contract convention in CLAUDE.md.