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sop-dogfooding-quality-detection
SOP for detecting quality regressions during dogfooding runs and turning them into actionable fixes.
allowed_tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite
model: sonnet
$ Instalar
git clone https://github.com/DNYoussef/context-cascade /tmp/context-cascade && cp -r /tmp/context-cascade/skills/quality/sop-dogfooding-quality-detection ~/.claude/skills/context-cascade// tip: Run this command in your terminal to install the skill
SKILL.md
name: sop-dogfooding-quality-detection description: SOP for detecting quality regressions during dogfooding runs and turning them into actionable fixes. allowed-tools:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
- Task
- TodoWrite model: sonnet x-version: 3.2.0 x-category: quality x-vcl-compliance: v3.1.1 x-cognitive-frames:
- HON
- MOR
- COM
- CLS
- EVD
- ASP
- SPC
STANDARD OPERATING PROCEDURE
Purpose
Identify quality regressions and latent issues while dogfooding, ensuring findings are evidenced, prioritized, and fed back into improvement loops.
Trigger Conditions
- Positive: active dogfooding sessions, regression sweeps after releases, or monitoring new features for emergent issues.
- Negative: isolated bug triage without self-application or pattern capture.
Guardrails
- Confidence ceiling: Use
Confidence: X.XX (ceiling: TYPE Y.YY)with ceilings {inference/report 0.70, research 0.85, observation/definition 0.95}. - Evidence-first: Record file:line, logs, metrics, or reproduction steps for each detected issue.
- Structure-first: Update examples/tests to reflect newly detected regressions and their fixes.
- Prioritization: Tag severity and blast radius; block release on critical regressions until resolved or waived with rationale.
Execution Phases
- Observation & Capture
- Monitor outputs, logs, and behaviors during dogfooding; collect anomalies.
- Normalize entries with severity, location, and reproduction notes.
- Validation & Classification
- Reproduce findings; distinguish false positives and intentional behavior.
- Map to categories (correctness, performance, UX, security, reliability).
- Remediation & Feedback
- Propose fixes and owners; add tests to prevent recurrence.
- Feed learnings into pattern retrieval and references.
- Confidence & Closure
- Confirm fixes or document waivers; state residual risk and confidence with ceiling.
Output Format
- Log of detected issues with evidence and severity.
- Reproduction steps and validation results.
- Remediation plan and test updates.
- Confidence statement using ceiling syntax.
Validation Checklist
- Evidence captured with location/steps for each issue.
- False positives filtered; categories assigned.
- Fixes/tests identified and owners named.
- Patterns/references updated where applicable.
- Confidence ceiling provided; English-only output.
Confidence: 0.70 (ceiling: inference 0.70) - SOP rewritten per Prompt Architect confidence discipline and Skill Forge structure-first detection loop.
Repository

DNYoussef
Author
DNYoussef/context-cascade/skills/quality/sop-dogfooding-quality-detection
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Updated1d ago
Added5d ago