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 LiXin97/agora-lab --skill student-literaturegit clone --depth 1 https://github.com/LiXin97/agora-labWrote 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/lixin97/agora-lab/student-literature)<a href="https://agentmods.dev/skills/lixin97/agora-lab/student-literature"><img src="https://agentmods.dev/badge/skills/lixin97/agora-lab/student-literature/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/lixin97/agora-lab/student-literature"><img src="https://agentmods.dev/badge/skills/lixin97/agora-lab/student-literature.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 | $0.00020 | $0.00395 |
| Opus 5 | $0.00010 | $0.00198 |
| Sonnet 5 | $0.00004 | $0.00079 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
student-literature 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.
What it actually says
Student Literature
Student-specific extensions
- End with
Recommended Baselinesthat names the first baseline to implement. - Add
Reviewer concerns to pre-emptwith the two highest-risk objections. - Check
shared-references/citation-discipline.mdbefore publishing.
Purpose
Survey existing work on a given topic to establish baselines, identify gaps, and inform hypothesis formulation.
Workflow
- Define scope: What specific question or area are you surveying?
- Search: Use web search to find relevant papers, blog posts, and codebases
- Read and summarize: Extract key contributions, methods, results, and limitations
- Synthesize: Identify themes, gaps, and opportunities
- Publish: Write structured output to your canonical shared artifact directory:
{artifact_dir}/{your-name}/literature_{topic}.md
Output Format
# Literature Survey: {topic}
## Scope
What question this survey answers.
## Key Papers
### {Paper Title} ({Year})
- **Authors**: ...
- **Method**: ...
- **Key Result**: ...
- **Limitation**: ...
- **Relevance**: Why this matters to our research
### {Paper Title} ({Year})
...
## Themes
1. ...
## Gaps & Opportunities
1. ...
## Recommended Baselines
Methods we should compare against:
1. ...
## Reviewer concerns to pre-empt
1. ...
2. ...
## References
- [1] ...
Tips
- Focus on papers from the last 3 years for ML/AI topics
- Always note the evaluation metrics used — we'll need to match them
- Flag any available open-source implementations
- Note dataset availability for reproducibility
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 · 70 lines · 20 tokens per session scan A 4b520816419a
student-literature is a skill published in the GitHub repository LiXin97/agora-lab (49 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 395 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 skills, from other repositories
cw-gates
Use before claiming any Codewhale change is done, green, or ready to land: the focused-to-broad verification ladder, the budget checks CI enforces, and the rules for what counts as a passing test.
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
contributor-onboarding
Help a new contributor get productive on this checkout - inspect sync state against main, build, run the repository's exact verification gate, and produce a local what's-new digest. Never fetches, pulls, or modifies a dirty tree on its own. Explicit-only.
codew-release-qa-sweep
Use before claiming Codewhale release work is done: run the full gate sweep and list the manual QA targets.
gh-file-issue
Use when filing a new Codewhale GitHub issue: turn a bug or idea into a well-formed, actionable issue with repro, acceptance criteria, labels, and milestone.
gh-treasure-hunt
Hunt the issue/PR queue for highest value-over-risk wins: clean focused community PRs, already-implemented issues to close, safe quick-fixes.