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.
npx skills add WALKERKILLER/Look-Tongji-Notes --skill listgit clone --depth 1 https://github.com/WALKERKILLER/Look-Tongji-NotesWrote 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/walkerkiller/look-tongji-notes/list)<a href="https://agentmods.dev/skills/walkerkiller/look-tongji-notes/list"><img src="https://agentmods.dev/badge/skills/walkerkiller/look-tongji-notes/list/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/walkerkiller/look-tongji-notes/list"><img src="https://agentmods.dev/badge/skills/walkerkiller/look-tongji-notes/list.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 | $0.00054 | $0.00645 |
| Opus 5.5 | $0.00022 | $0.00258 |
| Sonnet 5.5 | $0.00011 | $0.00129 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
list 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 1mo 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.
List
Discover and select courses from Tongji Look.
When to Use
- User says
/listor "show my courses" or "find a course". - Before transcribing or taking notes, to discover available course IDs and names.
- User wants to search courses by keyword in title or teacher name.
Workflow
- List recent courses (default, fast):
python "<SKILL_DIR>/../../scripts/look_tongji.py" list
- Search with keyword filter:
python "<SKILL_DIR>/../../scripts/look_tongji.py" list --query "<KEYWORD>"
- Show all courses (slower but complete):
python "<SKILL_DIR>/../../scripts/look_tongji.py" list --all
Options
| Flag | Description |
|---|---|
--all |
List all courses (slower but more complete) |
--limit LIMIT |
Number of courses to show (0 = all) |
--query QUERY |
Filter by keyword in title/teacher (server-side, case-insensitive) |
--choose CHOOSE |
Auto-select course # (1-based) for non-interactive use |
--force-login |
Ignore cached JWT and login again |
⚠️ Important: Chinese Query Limitation
--query is a server-side keyword search and may not match Chinese course names reliably. If --query "课程名关键词" returns empty:
Workaround: Use --all to fetch all courses, then filter locally:
python "<SKILL_DIR>/../../scripts/look_tongji.py" list --all 2>&1 | grep "课程名关键词"
Non-Interactive Usage
When --choose is set, the CLI auto-selects the course and saves its ID — no input() prompt. Combine with --all for scripted workflows:
python "<SKILL_DIR>/../../scripts/look_tongji.py" list --all --choose 1
Interactive Selection
When run without --choose, the CLI prints a numbered list of courses and prompts the user to select one. The selected course's ID is then available for use with /trans, /note, and other commands.
Where <SKILL_DIR> Points
<SKILL_DIR> is the directory containing this SKILL.md. Shared scripts (look_tongji.py, timeline_tools.py, tongji_backend/) and references live two levels up in the repository root (<SKILL_DIR>/../../scripts/ and <SKILL_DIR>/../../references/).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 74 lines · 54 tokens per session scan A f66e33ad4cc2
list is a skill published in the GitHub repository WALKERKILLER/Look-Tongji-Notes (50 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 645 once invoked, about $0.0002 per session on Opus 5.5. 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.
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