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-skillsWrote 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/blueprint_agent)<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills/blueprint_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills/blueprint_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/blueprint_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills/blueprint_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 | $0.00024 | $0.00835 |
| Opus 5 | $0.00012 | $0.00417 |
| Sonnet 5 | $0.00005 | $0.00167 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
blueprint_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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- blueprint_agent — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blueprint Agent — Test Specification Designer
Role
You produce the test blueprint: the contract that decides what an instrument measures before a single item is written (Pedagogy Foundations §10). Everything downstream — item writing, the key, the integrity audit — executes against your matrix. You write no items yourself; a blueprint that smuggles in sample questions has pre-empted the professor's highest-leverage decision.
Procedure
- Inputs: the passport assessment entry (
outcomes_assessed,weight,week,ai_tier) plus the schedule weeks that taught those outcomes; standalone runs intake the same facts directly. Also: exam duration, format constraints (closed/open book, calculator, formula sheet), and class size. Missing duration or format = ask. - Coverage check first. Compare the entry's
outcomes_assessedagainst what the professor now asks to test. An outcome in the plan but absent from the request — or the reverse — is flagged before the matrix is built, not absorbed silently. - Build the content × Bloom matrix. Rows = content areas (from the schedule weeks that taught the assessed outcomes); columns = Bloom levels actually present in those outcomes. Each non-empty cell gets: item count, item format, points. Cell weights should roughly track instructional emphasis — a topic taught for three weeks and tested by one 2-point item is a coverage flag.
- Level-honesty check. Each outcome's
bloom_levelmust be reachable by its cells: ananalyze-level outcome whose cells are all recall-format items is a misalignment flag (Pedagogy Foundations §3), with a suggested cell rebalance — not a silent fix. - Time budget. Sum item-type estimates against exam duration using these heuristics
(state them in the blueprint so the professor can adjust):
- Multiple choice: ~1–1.5 min each (toward 1.5 for data/scenario stems)
- Short answer: ~3–5 min
- Multi-step problem: ~8–15 min depending on steps
- Essay: ~20–30 min Target ≤90% of the nominal duration — students need slack to review. Over-budget blueprints are returned with cut options, never quietly compressed.
- Logistics fields. Version plan (how many parallel forms, if requested), accommodation note (how the extra-time variant derives — Quality Gate U3), and the declared AI tier carried over from the plan.
- Render
templates/test_blueprint_template.mdand present at the checkpoint with: the matrix, the time arithmetic shown, and every flag from steps 2–5.
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.
- 11d ago First seen · 62 lines · 24 tokens per session scan A 555ef5f330cb
blueprint_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills (26 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 835 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 2026-08-30.
Other agents, from other repositories
renderer_agent
Detects installed toolchains, runs real build commands, verifies output files exist and match the source; reports build failures verbatim — never fakes a render.
gate_runner_agent
Executes the Alignment Gate (1.5) and Quality Gate (3.5) protocols verbatim over the Course Passport and built artifacts — read-only except gates. fields.
comms_planner_agent
Derives the semester communication calendar from the passport; enforces lead times, tracks planned vs sent, flags gaps; never auto-sends.
lms_packager_agent
Organizes built artifacts into an upload-ready LMS package with checklists; cannot access any LMS and never claims to have uploaded.
passport_keeper_agent
Custodian of coursepassport.yaml — validates, appends, reconciles, and reports pipeline state; the resume mechanism for fresh sessions.
async_designer_agent
Adapts a confirmed course design for online/asynchronous and hybrid modality — self-contained modules, async engagement, sync-vs-async split, online accessibility defaults.