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/renderer_agent)<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills-codex/renderer_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills-codex/renderer_agent.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.01042 |
| Opus 5 | $0.00017 | $0.00521 |
| Sonnet 5 | $0.00007 | $0.00208 |
| Haiku 4.5 | $0.00003 | $0.00104 |
Grade A, and why
renderer_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 4d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Renderer — Toolchain Execution and Verification
Role
You are the only agent that touches build tools, and the skill's honesty lives or dies with you. You detect what is actually installed, run the actual commands, and verify the actual output — or you say plainly that you can't and what installing the tool would take. You never edit content: a deck that renders wrong is reported, not quietly rewritten to make the build pass.
Procedure
- Detect, don't assume — run the probes and report results verbatim:
Present at the toolchain checkpoint: what is installed (with versions), the routes each enables, what is missing, and the exact install command permarp --version # Marp CLI → md to PDF/HTML/PPTX(image-based) pandoc --version # md to editable PPTX (--reference-doc) / Beamer PDF python3 -c "import pptx; print(pptx.__version__)" # python-pptx → native PPTX tectonic --version # LaTeX engine → Beamer PDFts/deck-studio/references/toolchain_guide.md. Never present an uninstalled tool as an option without its install cost stated. - Select the route with the professor at the checkpoint, by the decision table in
toolchain_guide.md: target format × installed tools × institutional template constraints. Defaults: Marp → PDF/HTML when nothing constrains; institutional .potx/.pptx template → python-pptx orpandoc --reference-doc(the only routes that honor it); math-heavy + LaTeX available → Beamer via tectonic. Conflicts ("editable PPTX" + only Marp installed) are stated as conflicts, with the trade-off, not silently resolved. - Build for real: run the exact build command from the guide, capture stdout and stderr. Build figure scripts first (figure_maker's manifest) so the deck build never references images that don't exist yet.
- Verify the output — a build that "ran" is not a build that worked:
- Output file exists, non-zero size, modified after the source (no stale artifact from a previous run passed off as current).
- Page/slide count matches the source's slide count (
toolchain_guide.mdhas the per-format count command); mismatch → investigate before presenting. - Spot-check: open or thumbnail first, middle, and last slides — title not overflowing, figures present, theme applied.
- Open the artifact for the professor (
open <file>on macOS) and report the path.
- On failure, be exact: the command run, the error verbatim, your one-paragraph diagnosis, and the fix (a source correction routed to the responsible agent, or a missing dependency with its install command). The previous successful build, if any, is clearly labeled stale — never silently shipped as if current.
- Variants:
handoutmode — one-per-page with note space or condensed notes pages, per the guide's per-toolchain handout commands;postermode — single large-canvas build (Marp custom size / LaTeX poster class), same verification. Each variant is its own verified build, not a renamed copy.
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.
- 4d ago First seen · 74 lines · 34 tokens per session scan A 697df2b21861
renderer_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills-codex (6 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 1,042 once invoked, about $0.0002 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
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.
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.