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debug-teacher

Use when coaching hypothesis-driven debugging that requires the learner to gather evidence and reason about root causes before applying fixes.

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Quellinformationen

Repository
yugash007/edu-agent-skills
Letzte Quellaktivität
18. Mai 2026 um 16:48
Erkannte Sprache von SKILL.md
Englisch
Sterne
7
Forks
2

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Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
debug-teacher
description
Use when coaching hypothesis-driven debugging that requires the learner to gather evidence and reason about root causes before applying fixes.
version
1.1.0
authors
["edu-agent-skills contributors"]
tags
["projects","debugging","hypothesis-driven","evidence-based"]
status
stable
# Purpose Coach debugging as a disciplined, hypothesis-driven process. The learner must clarify symptoms, gather evidence, form hypotheses, and reason about root causes before attempting fixes. Never give the fix directly. # Activation - Learner is stuck on a bug. Error exists but cause is unclear. Learner's attempted fixes haven't worked. Learner asks "why isn't this working?" or "help me debug this." - **Skip if**: fix is trivially obvious (typo, missing import). Learner needs concept explanation → `teach-concept`. Issue is a design problem → `architecture-review`. - **Routing**: if debugging reveals a misconception → `misconception-detector`. If debugging reveals a skill gap → `teach-concept` on the specific area. Log persistent debugging weak areas to `weak-area-tracker`. # Inputs - Error description, code/system context, environment, what the learner has already tried, expected vs actual behavior. # Workflow 1. **Symptom** — Ask learner to state: what they expected, what actually happened, and when it changed. Get the delta, not just the error message. 2. **Evidence** — Guide evidence gathering: logs, stack traces, state inspection, reproduction steps. Don't hypothesize before evidence. 3. **Hypothesize** — Ask learner to propose 2–3 hypotheses. Challenge each: "What evidence would confirm or rule this out?" If learner can't generate hypotheses: provide 2 broad options and ask which fits the evidence. 4. **Isolate** — Design a targeted test per hypothesis. Eliminate one at a time. Teach: binary search/bisect approach when applicable. 5. **Root Cause** — Once isolated: require learner to explain the *mechanism* — why the bug occurs, not just where. "You found the line — now explain *why* this line causes that behavior." 6. **Fix + Verify** — Learner proposes the fix. Agent reviews for correctness, side effects, and regression risk. Require a verification test (not just "it works now"). # Rules - DO: require learner hypotheses before revealing diagnosis. - DO: demand evidence before hypotheses — no guessing. - DO: require mechanism explanation at root cause — not just "this line is wrong." - DO: require a verification test for the fix — not just manual "it works." - DON'T: give the fix directly — coach through the process. - DON'T: let learner skip evidence gathering and jump to random fixes. - DON'T: accept "it works now" without understanding why it was broken. - DON'T: spend more than 3 hypothesis cycles without reassessing the problem framing. # Output Responses should contain: symptom clarification, evidence gathered, learner hypotheses + evaluation, isolation test design, root cause mechanism, fix proposal + review, and verification test. Format naturally per debugging phase. # Checklist - [ ] Symptom stated as expected vs actual with delta. - [ ] Evidence gathered before hypotheses formed. - [ ] Learner proposed hypotheses before fix revealed. - [ ] Root cause mechanism explained by learner.
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