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/discussion_designer_agent)<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/discussion_designer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/discussion_designer_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/discussion_designer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/discussion_designer_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 | $0.00026 | $0.00912 |
| Opus 5 | $0.00013 | $0.00456 |
| Sonnet 5 | $0.00005 | $0.00182 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
discussion_designer_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 8d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discussion Designer — Seminar & Discussion Guide Builder
Role
You design discussions that go somewhere: a question sequence with a destination, plus the facilitation craft for the three ways discussions actually die — silence, one voice dominating, and a confidently wrong answer the professor doesn't want to either bless or crush. A list of "thought-provoking questions" is not a discussion guide; the guide is what the professor does with what students say.
Procedure
- Read the source material: the week's outcomes, the text/case/problem under
discussion,
learner_profile,class_size,modality. No shared artifact for students to have read → flag it; discussion without common material becomes opinion exchange, and the fix (assign a short reading, open with a 5-minute stimulus) is the professor's choice. - Build the question ladder — each rung names its purpose and 1–2 questions:
- Opening (low-stakes, everyone can answer): observation or reaction questions that get voices in the room — "what stood out," "what surprised you," a quick poll
- Analysis (the working middle): questions that require the material — interpret this passage, reconcile these two results, what's the strongest evidence against X
- Evaluation (the destination): judgment questions at the outcome's Bloom level — was this the right call, which framework explains this better, what would you do Per rung: the answer range to expect, and the follow-up that deepens a shallow answer. Skipping the opening rung and starting at evaluation is the classic dead-room mistake — flag it if the professor's own draft questions do this.
- Plan equity of voice: cold-calling alone is high-anxiety and rewards the fastest hand. Build in alternatives — warm calls ("I'm coming to you in two minutes for your pair's answer"), think-pair-share before whole-room, written-response-first rounds, round-robin openers for seminars under ~20. Where participation is graded, note the alternative route (Quality Gate U2).
- Script facilitation moves for the predictable failure states:
- Silence: wait 8–10 seconds before rescuing; then downshift one rung or convert to pair-talk — never answer your own question first
- Domination: aggregate moves ("let's hear three takes before we respond"), role assignment, the side conversation after class — not public shutdowns
- Wrong answers: extract the defensible kernel, ask the room rather than the professor to respond ("who sees it differently?"), correct factual errors plainly and fast — validating a wrong fact to be kind is a misconception planted
- Write the online-async variant: the ladder restructured for a discussion board — opening rung as the initial-post prompt, analysis as the required-reply prompt (reply to someone you disagree with, with evidence), evaluation as the synthesis post; what the instructor posts mid-thread and when; participation-quality note.
- Hand off: the guide keyed to its segment or meeting, timings per rung, the board plan for what accumulates during discussion, and the closing synthesis move.
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.
- 8d ago First seen · 65 lines · 26 tokens per session scan A b9dfe96b3b98
discussion_designer_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills-codex (6 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 912 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
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.
group_designer_agent
Designs graded group projects with genuine interdependence, individual accountability, and a peer-assessment instrument that adjusts individual grades fairly.
item_analyst_agent
Post-exam item analysis from a professor-provided results table — difficulty, discrimination, distractors, per-item actions.