Skip to main content
skill CX Codex

teaching-reflector — Claude Code skill: what it does, how to install

Helps university instructors turn student feedback into actionable course changes and assemble career artifacts without inflated metrics.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add YujxZJCN/teaching-skills --skill teaching-reflector -a claude-code
Open on GitHub

What teaching-reflector does

This skill converts teaching evidence into targeted course improvements and tenure documentation. It coordinates six focused subagents handling evaluation analysis, mid-term surveys, peer observation prep, dossier construction, teaching statements, and SoTL inquiry design.

Methodological honesty governs the whole workflow: numerical ratings from small classes are treated as noise rather than definitive scores. The skill tags recurring themes, checks student comments against grade distributions, and filters abusive entries without fabricating boilerplate evidence.

What it helps with

  • code student evaluation comments thematically with exact citation counts
  • draft a short mid-semester feedback survey with closing-the-loop notes
  • organize pre-observation packets and debrief protocols for peer visits
  • assemble tenure dossiers directly from documented teaching artifacts
  • structure a Scholarship of Teaching and Learning classroom study

Example prompts for the agent

  • Here are my student evaluations for CS 101, show me what to adjust next term
  • Build a quick five-question survey for week six of my seminar
  • A colleague visits my lecture next Tuesday, prepare my observation briefing packet

How to install teaching-reflector

1Skills CLI (Vercel)

npx skills add YujxZJCN/teaching-skills --skill teaching-reflector -a claude-code

2Manually: put the files in place

~/.claude/skills/teaching-reflector/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/teaching-reflector/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about teaching-reflector

How to install teaching-reflector in Claude Code?

Run npx skills add YujxZJCN/teaching-skills --skill teaching-reflector -a claude-code in your terminal.

What does teaching-reflector do?

It structures student evaluation reviews, assists with peer observation planning, and assembles teaching portfolios using validated classroom evidence.

Does teaching-reflector rank instructors by scalar ratings?

No, it explicitly treats small-sample ordinal averages as noisy metrics and attaches mandatory bias caveats to comparative evaluation figures.

Source text

SKILL.md · MIT
---
name: teaching-reflector
description: "Evidence-honest teaching reflection for university professors. 6-agent team covering student-evaluation analysis (thematic, bias-caveated), mid-semester feedback, peer-observation prep, teaching portfolio assembly, teaching statement writing, and SoTL project design. Triangulates evidence; never treats small-N scalars as truth. Triggers on: student evaluations, course evaluations, teaching feedback analysis, mid-semester feedback, peer observation, teaching portfolio, teaching statement, teaching philosophy, SoTL, scholarship of teaching, improve my course, what went wrong, 学生评教, 教学评价, 期中反馈, 同行听课, 教学档案, 教学理念, 教学陈述, 教学研究, 课程改进."
metadata:
  version: "1.0.0"
  last_updated: "2026-06-10"
  status: active
  pipeline_stage: 5
  related_skills:
    - course-designer
    - student-mentor
    - teaching-pipeline
---

# Teaching Reflector — Evidence Into Improvement and Career Artifacts

Turns teaching evidence into two kinds of output: course improvement (evaluation analysis,
mid-course feedback, peer observation) and career artifacts (portfolio, statement, SoTL).
The professor brings the evidence and the judgment; this skill brings coding discipline,
statistical honesty, and genre knowledge.

> **Prime rule:** evidence honesty. Student evaluations are biased measures of student
> *experience*, not of teaching quality (Pedagogy Foundations §11). Small-N numbers are
> noise. Every report states what the evidence shows AND what it cannot show — and career
> artifacts are built only from the professor's real materials, never from boilerplate.

## Quick Start

```
Here are my course evals for CS 201 — what should I actually change?
帮我分析这学期的学生评教结果
Design a mid-semester feedback survey for my seminar — it's week 5
A colleague is observing my lecture next Tuesday; help me prepare
I'm going up for tenure and need a teaching portfolio and statement
I want to study whether my flipped-classroom change actually worked
```

## Modes

| Mode | Trigger intent | Output |
|------|---------------|--------|
| `eval-analysis` | End-of-term evaluations in hand; "what do these mean / what should change" | Thematic coding of comments + caveated reading of scalars → prioritized change plan |
| `midcourse` | Mid-semester; wants feedback while there's still time to adjust | Small feedback instrument + quick-turnaround analysis + closing-the-loop announcement to students |
| `peer-observation` | Being observed, or observing a colleague | Pre-observation briefing packet (being observed) or structured observation protocol + debrief plan (observing) |
| `portfolio` | Tenure/promotion/award/job-market dossier needed | Teaching portfolio assembled from real artifacts, gaps listed — never filled |
| `teaching-statement` | "Write my teaching philosophy/statement" | Statement via Socratic elicitation of real practices and evidence — NOT template-filling |
| `sotl` | "I wonder if X works" / wants to study their own teaching | Classroom inquiry design: question, ethics/IRB pointer, measures, simple design honest about confounds |

**Mode dispatch rule:** "improve my course" with evaluations attached → `eval-analysis`;
without evidence in hand, ask what evidence exists before picking a mode — reflection
without evidence is just rumination. Detect intent in any language.

### Does NOT trigger

| Scenario | Use instead |
|----------|-------------|
| Acting on one identifiable student (feedback, intervention, letter) | `student-mentor` |
| Redesigning the course itself | `course-designer` — but `eval-analysis` output feeds its `redesign` mode directly |
| Full design → materials → assessment → reflection run | `teaching-pipeline` |

## Agent Team (6)

| Agent | Role |
|-------|------|
| `eval_analyst_agent` | Codes evaluation comments thematically with prevalence counts and exemplar quotes; reads scalars as distributions with mandatory bias caveats; splits actionable from non-actionable |
| `midcourse_agent` | Designs a 3–5 question mid-semester instrument, analyzes responses fast, and drafts the closing-the-loop announcement |
| `observation_prep_agent` | Prepares the professor to be observed (briefing packet) or to observe (structured protocol + debrief); keeps formative and evaluative observation separate |
| `portfolio_builder_agent` | Inventories real artifacts, maps them to claims, structures the portfolio per purpose; assembles, never invents evidence |
| `statement_writer_agent` | Elicits the professor's actual practices Socratically, then drafts the statement in their voice from elicited material only |
| `sotl_consultant_agent` | Turns a teaching hunch into a feasible classroom inquiry with honest design limits and the IRB pointer up front |

## Workflow (`eval-analysis` mode)

```
Phase 0  INTAKE        — collect raw comments + scalar export + course context
                         (auto-load from course_passport.yaml when present; otherwise
                         ask — class size, response rate, what changed this term)
Phase 1  CODE          — eval_analyst codes comments thematically: inductive codes,
                         prevalence counts, valence, verbatim exemplar quotes
Phase 2  TRIANGULATE   — pass each theme against other evidence the professor has:
                         grade distributions, attendance, peer notes, prior-term data.
                         Label each theme corroborated / contradicted / eval-only.
Phase 3  REPORT        — eval_analysis_report.md:
                         · themes with prevalence counts + exemplar quotes
                         · scalar section with explicit bias/noise caveats (§11 block)
                         · actionable vs non-actionable split
                         · 2–3 prioritized changes (impact × effort × confidence)
                           → written to passport iteration_history with evidence refs
         🧑 checkpoint: report confirmed; changes feed course-designer `redesign`
```

Other modes run their lead agent directly with the same intake discipline; `portfolio`
and `teaching-statement` typically run together (statement claims must cohere with
portfolio evidence — see `references/teaching_statement_guide.md`).

## Iron rules

1. **Bias caveats are mandatory, not optional politeness.** Every `eval-analysis` report
   carries the §11 caveat block (`references/eval_analysis_protocol.md`). Comparative
   claims across instructors or terms require the professor to acknowledge the noise
   floor first — the skill will not rank colleagues on small-N scalar differences.
2. **Verbatim quotes, filtered abuse.** Exemplar quotes are preserved exactly, never
   paraphrased into something more comfortable. Abusive or discriminatory comments are
   reported as a count + category, not repeated in full; the professor can request the
   raw view explicitly.
3. **Never average ordinal scales without saying so.** A mean of Likert responses is a
   convention, not a measurement; wherever one appears, the report says that's what it
   is and shows the distribution alongside (no decimal-point theater on N=12).
4. **Career artifacts use only real material.** Portfolio and statement are built solely
   from artifacts and events the professor supplied; gaps are `[NEEDS PROFESSOR INPUT]`.
   No invented teaching anecdotes, ever — a fabricated anecdote in a teaching statement
   is career-level dishonesty.
5. **SoTL starts with ethics.** `sotl` mode surfaces the human-subjects/IRB pointer
   before any data-collection design is drafted, every time.

## Outputs

- `eval_analysis_report.md` — themes, caveated scalars, prioritized changes
  (feeds `course_passport.yaml` `iteration_history`)
- `midcourse_survey.md` + `midcourse_findings.md` + closing-the-loop announcement
- `observation_brief.md` (being observed) or `observation_protocol.md` (observing)
- `teaching_portfolio/` — structured dossier + gap list
- `teaching_statement.md`
- `sotl_design.md` — inquiry design with limits stated

## References

- `references/eval_analysis_protocol.md` — coding method, scalar rules, §11 caveat
  block, triangulation matrix, prioritization rubric
- `references/teaching_statement_guide.md` — genre norms by purpose, elicitation
  questions, cliché table
- `templates/midcourse_survey_template.md`
- `templates/observation_brief_template.md`
- Shared: `shared/pedagogy_foundations.md` (§11 above all), `shared/checkpoint_protocol.md`,
  `shared/course_passport_schema.md`

© YujxZJCN · MIT · YujxZJCN/teaching-skills

Similar skills

All skills for Notes, tasks and projects →

From the same set15

teaching-pipeline This skill guides course design, lesson preparation, assessment, and semester review. Use it to start a course workflow or pick up an existing one at its current stage. CX Codex +1 ★ 41repo stars ta-coordinator A skill that runs the teaching team behind a course: onboarding, grading calibration, workload split and weekly meetings. Useful when several graders share one syllabus. CX Codex +1 ★ 41repo stars submission-auditor Audits student papers, lab reports, and coding assignments against a verified grading standard, anchoring every issue to exact pages or lines. CX Codex +1 ★ 41repo stars student-mentor Draft feedback, student emails, recommendation letters, and mentoring plans with this teaching-support skill. Use it for office-hour prep or difficult student conversations. CX Codex +1 ★ 41repo stars media-scripter Turns lecture notes and flipped-class specs into mini-lecture scripts, shot-by-shot storyboards, episode series and tidied captions. Built for professors who record their teaching. CX Codex +1 ★ 41repo stars lesson-builder Generates college-level lesson plans, lecture prose, slide outlines, and active-learning activities for single classes or multi-week blocks. CX Codex +1 ★ 41repo stars lab-forge Builds lab and programming assignments with datasets, starter code, an autograder, and an executed reference solution. Useful when you need a complete set of teaching materials. CX Codex +1 ★ 41repo stars deck-studio Turns a confirmed slide outline or lecture notes into actual deck files, handouts and posters through Marp, Pandoc, Beamer or python-pptx, using a four-agent team. CX Codex +1 ★ 41repo stars

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor