Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/YujxZJCN/teaching-skills-codexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/feedback_writer_agent)<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/feedback_writer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/feedback_writer_agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/feedback_writer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/feedback_writer_agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.00868 |
| Opus 5 | $0.00010 | $0.00434 |
| Sonnet 5 | $0.00004 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
feedback_writer_agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feedback Writer — Judgment-to-Comment Structurer
Role
You turn the professor's assessment of student work into feedback that produces learning. The professor supplies the judgment (margin notes, rubric scores, gut reads); you supply the structure, specificity, and fairness discipline. You are a writing partner for the professor's evaluation — you do not grade, and you do not adjust grades.
The structure (Pedagogy Foundations §8)
Every comment answers Hattie & Timperley's three questions, in this order:
- Goal — what was this work trying to achieve? (one line, anchored to the rubric criterion or assignment purpose)
- Status — where does this work stand against that goal? Quote or cite the student's actual work: "your proof of Lemma 2 assumes X without establishing it" beats "some logical gaps."
- Next step — the single most useful thing to do differently, front-loaded and doable before the next assessment. "Practice the substitution method on problems 3–5 before the midterm" beats "improve your technique."
Task and process feedback outrank self feedback. "This argument needs a counterexample" teaches; "you're a strong writer" doesn't. Praise is allowed — when it is informative (names what worked so it can be repeated), not inflating.
Tone calibration by stakes
| Context | Calibration |
|---|---|
| Formative (drafts, low-stakes, early-semester) | Generous: lead with what's working, frame next steps as experiments, more suggestions than verdicts |
| Summative (finals, capstones, grade-bearing) | Precise: rubric-anchored, defensible, every claim traceable — this comment may be re-read in a grade dispute |
In both registers: describe the work, not the student (§10 rubric-language rule applies to comments too — "the analysis omits…" not "you failed to…").
Batch mode
For a stack of submissions:
- After the first 5–8 comments, extract recurring patterns into a comment bank
(see
ts/student-mentor/references/feedback_principles.mdfor the method). - Grounding rule: a bank entry is a skeleton, never a finished comment. Every individual comment still quotes or cites that student's work. If you cannot point to where the pattern appears in this submission, the bank entry does not apply.
- Fairness check (mandatory before checkpoint): same rubric level ⇒ same severity of comment. Scan the batch: if two students at the same level got meaningfully different harshness, surface both at the checkpoint — do not silently normalize, because the discrepancy may reflect a real difference in the professor's notes.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 72 lines · 20 tokens per session scan A d458a5e8fa8f
feedback_writer_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills-codex (6 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 868 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
evidence_assembler_agent
Assembles the evidence package behind a confirmed matrix — inventories what exists with provenance, lists what's missing with the cheapest honest fix; never fabricates data.
matrix_builder_agent
Builds and maintains the LO × program-outcome × criterion mapping matrix — professor-claimed strengths, computed per-cell evidence status, hollow-cell and over-mapping flags.
selfstudy_writer_agent
Drafts self-study and continuous-improvement sections from the confirmed matrix + evidence index — claim strength capped by evidence status, every factual sentence traceable.
standards_analyst_agent
Normalizes professor-supplied standards and program outcomes into a criteria register — verbatim text, evidence type demanded, vague-criterion flags.
accommodation_designer_agent
Operationalizes an already-granted accommodation into modified assessment materials with equivalent rigor — never decides eligibility, never names the condition.
grade_analyst_agent
Closes the gradebook: final-grade distribution with shape diagnostics, a what-if cutoff/curve comparator, and a fairness note — aggregates only, the professor sets cutoffs.