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 voidful/academic-skills --skill professor-fit-analysergit clone --depth 1 https://github.com/voidful/academic-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/skills/voidful/academic-skills/professor-fit-analyser)<a href="https://agentmods.dev/skills/voidful/academic-skills/professor-fit-analyser"><img src="https://agentmods.dev/badge/skills/voidful/academic-skills/professor-fit-analyser/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/voidful/academic-skills/professor-fit-analyser"><img src="https://agentmods.dev/badge/skills/voidful/academic-skills/professor-fit-analyser.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 | $0.00168 | $0.10173 |
| Opus 5.5 | $0.00067 | $0.04069 |
| Sonnet 5.5 | $0.00034 | $0.02035 |
| Haiku 4.5 | $0.00017 | $0.01017 |
Grade A, and why
professor-fit-analyzer 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 — 733 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Professor Fit Analyzer
Build an evidence-based dossier for a professor and convert that dossier into an application, advising, or collaboration strategy.
This skill is platform-agnostic, discipline-agnostic, and level-agnostic. It serves PhD applicants, master's students seeking thesis advisors, and undergraduate students looking for capstone/thesis/independent-study supervisors — across all academic fields. Use the browsing, search, and file-reading tools available in the current agent. Prefer public academic sources first. If browsing is unavailable, ask the user for links, PDFs, or a publication list and continue with partial coverage rather than guessing.
Input Specification
Required inputs
- Professor name.
- At least one of: Google Scholar URL, personal website URL, lab website URL.
Optional but recommended inputs
- User education background (current degree, field, institution).
- User research experience (past projects, publications, technical skills).
- Application type: PhD student, master's student (thesis-track or coursework-track), undergraduate researcher (capstone/thesis/independent study/專題), RA, postdoc, visiting scholar, or research collaborator.
- User strengths and distinctive capabilities.
- Nationality, language proficiency, and whether scholarship or visa sponsorship is needed.
- Target timeline (e.g., Fall 2027 PhD application, this summer for internship, immediate contact).
Input handling rules
- If the user provides only a professor name with no URL, ask for at least one URL or publication source before proceeding.
- If user background is missing, produce conditional advice by applicant type and level rather than generic praise.
- If target timeline is missing, assume general exploration and skip urgency-dependent advice.
- If application type is missing, ask the user to specify their level (PhD / master's / undergraduate / other). The analysis depth and advice framing differ significantly by level.
- If the user provides a CV or publication list, use it to strengthen fit analysis.
What ships with it
5 files 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 · 733 lines · 168 tokens per session scan A b4e9167f3f82
professor-fit-analyzer is a skill published in the GitHub repository voidful/academic-skills (139 stars, last pushed 6mo ago), licensed MIT. It adds 168 tokens to every session and 10,173 once invoked, about $0.0007 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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