Borrowing it
Nothing to install: this file belongs to sweeden-ttu/canvas-lms-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/sweeden-ttu/canvas-lms-mcp/main/.cursor/skills/cs-peer-reviewer-trustworthy-ai/SKILL.mdgit clone --depth 1 https://github.com/sweeden-ttu/canvas-lms-mcpWrote 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/skills/sweeden-ttu/canvas-lms-mcp/cs-peer-reviewer-trustworthy-ai)<a href="https://agentmods.dev/skills/sweeden-ttu/canvas-lms-mcp/cs-peer-reviewer-trustworthy-ai"><img src="https://agentmods.dev/badge/skills/sweeden-ttu/canvas-lms-mcp/cs-peer-reviewer-trustworthy-ai/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/skills/sweeden-ttu/canvas-lms-mcp/cs-peer-reviewer-trustworthy-ai"><img src="https://agentmods.dev/badge/skills/sweeden-ttu/canvas-lms-mcp/cs-peer-reviewer-trustworthy-ai.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 | $0.00068 | $0.00902 |
| Opus 5 | $0.00034 | $0.00451 |
| Sonnet 5 | $0.00014 | $0.00180 |
| Haiku 4.5 | $0.00007 | $0.00090 |
Grade A, and why
cs-peer-reviewer-trustworthy-ai 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 12d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CS Peer Reviewer + Trustworthy AI Presentation Builder
Provide rigorous, constructive peer review for Computer Science Masters–level work and produce multi-slide Reveal.js presentations that teach Trustworthy AI with concrete, real-world examples.
Inputs to request (if missing)
- The artifact to review (paper/draft/proposal/slides/code) and its goal
- Intended venue or rubric (course, thesis proposal, workshop paper)
- Audience level and time budget (e.g., 15/30/60 minutes)
- Any constraints (must use Reveal.js, must include Mermaid/KaTeX, etc.)
Peer review workflow (Masters level)
-
Summarize first
- 3–6 bullets capturing: problem, method, evaluation, key results/claims.
-
Assess contribution
- What is new? What is the baseline? What is the practical impact?
-
Correctness and clarity
- Identify ambiguous definitions, missing assumptions, or unjustified steps.
- Flag diagrams/figures that don’t match the text.
-
Evaluation rigor
- Are metrics appropriate? Baselines fair? Ablations present?
- Reproducibility: datasets, seeds, hyperparameters, compute budget.
-
Trustworthy AI lens
- Fairness: group/individual fairness assumptions and trade-offs.
- Privacy: threat model (membership inference, reconstruction), mitigation.
- Robustness: distribution shift, adversarial robustness, calibration.
- Security: prompt injection/model extraction/data poisoning where relevant.
- Transparency: interpretability, documentation (model cards/datasheets).
- Accountability: governance, auditing, monitoring, incident response.
-
Actionable recommendations
- Provide a prioritized fix list:
- Must-fix (blocking)
- Should-fix (strongly recommended)
- Nice-to-have
- Provide a prioritized fix list:
Review output format (default)
Return feedback as:
- Summary
- Strengths
- Weaknesses / Risks
- Questions for the author
- Concrete improvements (prioritized)
- Suggested experiments / ablations
- Trustworthy AI checklist results
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.
- 12d ago First seen · 95 lines · 68 tokens per session scan A 1bab38027b5c
cs-peer-reviewer-trustworthy-ai is a skill published in the GitHub repository sweeden-ttu/canvas-lms-mcp (0 stars, last pushed 6mo ago), licensed MIT. It adds 68 tokens to every session and 902 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
canvas-cli
Manage Canvas LMS (https://www.instructure.com/canvas) from the terminal with the canvas CLI — courses, assignments, submissions and grading, modules, pages, quizzes, discussions, announcements, users, enrollments, sections, files, and analytics. Use this whenever the user wants to list or create assignments, grade…
canvas-admin-roster
Admin skill for walking the Canvas account hierarchy: list accounts and sub-accounts, see courses and users under each, look up which canned reports are available, and enroll or remove users from a specific course — one action at a time. Trigger phrases include "admin roster", "list accounts", "sub accounts", "account…
canvas-accessibility-sweep
Educator and learning-designer skill for a pre-launch accessibility and broken-link sweep of a Canvas course. Walks the structural accessibility audit and the link audit over a course's pages, assignments, syllabus, announcements, and (optionally) quizzes, then produces a prioritised remediation list you can work…
canvas-office-hours
Educator skill for running office hours through Canvas Scheduler appointment groups. Create and publish sign-up slots for a course, list existing groups and their time slots, and see which students (or student groups) have reserved — one confirmed action at a time. Trigger phrases include "office hours", "appointment…
canvas-peer-review-tracker
Educator skill for tracking peer-review assignments in Canvas. Lists who has been asked to review whom, who has submitted versus who is still pending, and lets you assign new reviewers or send reminder messages — one student at a time. Trigger phrases include "peer reviews", "who hasn't done their peer review", "peer…
canvas-course-pulse
Educator skill for tracking week-over-week course health trends in Canvas. Surfaces assignment performance trends, login activity, engagement gaps, and struggling students across a longer time horizon than a daily check. Trigger phrases include "course pulse", "course health", "course trends", "week-over-week…