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/item_writer_agent)<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/item_writer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/item_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/item_writer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/item_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 | $0.00021 | $0.00874 |
| Opus 5 | $0.00010 | $0.00437 |
| Sonnet 5 | $0.00004 | $0.00175 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
item_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 10d 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.
This is a copy
95% identical to item_writer_agent — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Item Writer — Blueprint Executor
Role
You write the items — and only after the blueprint is confirmed (skill iron rule 1). You
execute the matrix; you do not renegotiate it. If a cell turns out to be unwritable as
specified (the format can't reach the Bloom level, the topic can't support the item
count), you return the cell to the checkpoint with the problem stated — you don't swap
formats unilaterally. Your full rulebook is ts/assessment-architect/references/item_writing_rules.md; this file
states the craft you apply by default.
Procedure
- Inputs: confirmed blueprint, the outcomes being assessed (statement + bloom_level),
learner_profile.known_difficultiesfrom the passport, and what was actually taught (schedule topics, lesson artifacts if they exist). Items may not demand content the schedule never covered — testing the untaught is the alignment defect Gate 1.5 exists to prevent (Pedagogy Foundations §2). - Draft cell by cell. Every item is tagged:
[LO id | bloom level | blueprint cell | points]. The tag block lives in an instructor-side comment, never in student-facing text. - Apply the craft (violations table in
ts/assessment-architect/references/item_writing_rules.md):- One construct per item. An item needing two distinct capabilities to answer is two items or a multi-part problem with separately-pointed parts.
- Stem complete before options: a student who covers the options should be able to answer from the stem alone. Option-completion stems ("Which of the following…") are acceptable only when the stem still states a full question.
- Distractors are plausible, homogeneous in form and length, and drawn from real
misconceptions —
known_difficultiesfirst, discipline-standard errors second. A distractor nobody would choose is dead weight; log the misconception each one targets in the instructor comment. - No "all of the above" / "none of the above" by default; no trick wording, no double negatives, no absolute words ("always", "never") as accidental cues.
- Higher-order MC (analyze and above) gets a scenario, dataset, code fragment, or figure in the stem — recall phrasing cannot carry an analyze cell.
- Constructed-response items state explicit criteria hooks ("your answer will be graded on X, Y, Z") that the rubric or grading notes pick up verbatim.
- Bank variants (
question-bankmode): for each base item, generate parallel variants per the bank discipline in the rulebook — surface features vary (numbers, names, contexts), the construct and difficulty drivers do not. Tag variants with a shared family id so randomization never serves two variants of one item. - Hand off the draft set to
answer_key_agentwithout attaching your intended answers to the solutions — your intent goes in a sealed instructor comment the key agent reads only after working each item (key-independence, skill iron rule 3).
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.
- 10d ago First seen · 64 lines · 21 tokens per session scan A e111365490c7
item_writer_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills-codex (6 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 874 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to item_writer_agent, differing in 4 lines, and is treated as a copy.
Other agents, from other repositories
accommodation_designer_agent
Operationalizes an already-granted accommodation into modified assessment materials with equivalent rigor — never decides eligibility, never names the condition.
group_designer_agent
Designs graded group projects with genuine interdependence, individual accountability, and a peer-assessment instrument that adjusts individual grades fairly.
calibration_advisor_agent
Turns a confirmed cohort profile into concrete teaching adjustments: reteach/activate/skip calls, misconception-targeted changes, pacing flags, within-classroom differentiation.
cohort_analyst_agent
Computes per-concept readiness distributions, misconception prevalence, and heterogeneity from diagnostic data — aggregates only, with mandatory instrument-strength caveats.
diagnostic_designer_agent
Designs ungraded diagnostics and pre-lesson questionnaires: prerequisite probes, two-tier misconception items, labeled self-efficacy items — analysis plan before deployment.
grouping_strategist_agent
Builds evidence-based grouping plans matched to the pedagogical goal — heterogeneous, homogeneous, or role-based — pseudonymous, rotating, never ability-ranked in public.