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 agentmods add skills/ankitforcode/medify-mcp-server/medify-ucat-analysisnpx skills add ankitforcode/medify-mcp-server --skill medify-ucat-analysisgit clone --depth 1 https://github.com/ankitforcode/medify-mcp-serverWrote 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/ankitforcode/medify-mcp-server/medify-ucat-analysis)<a href="https://agentmods.dev/skills/ankitforcode/medify-mcp-server/medify-ucat-analysis"><img src="https://agentmods.dev/badge/skills/ankitforcode/medify-mcp-server/medify-ucat-analysis.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 | $0.00072 | $0.00936 |
| Opus 5 | $0.00036 | $0.00468 |
| Sonnet 5 | $0.00014 | $0.00187 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
medify-ucat-analysis 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 3d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Medify UCAT analysis
Use the medify-ucat MCP server. Call tools for live account data — do not invent scores.
Full parameter reference: tools-reference.md.
Workflow
check_connection— ifokis false, tell the user to setMEDIFY_EMAIL+MEDIFY_PASSWORDorMEDIFY_SESSION_COOKIE, rebuild/restart MCP, retry.refresh_scoreswhen they just finished a mock or data looks stale.- Gather evidence in parallel (pick what the ask needs):
analyze_score_trends—{ "kind": "full" }for totals / section trendsanalyze_section_performance—{ "kind": "full" }for VR/DM/QR rankinganalyze_topic_performance—{ "includeSj": false }for subtype vs population (default already excludes SJ)analyze_question_timing—{ "limit": 10 }for clock use, thirds, time sinks, fast guesses
recommend_focus_areas:{ "kind": "full", "includeSj": false, "targetTotal": 2250 }when they set a cognitive goal / ignore SJ- omit
targetTotal/ setincludeSj: trueonly if they want SJ advice
- Optional:
list_completed_mocks,get_mock_details,compare_mocks.
Reporting rules
- Cognitive total = VR + DM + QR only (about 900–2700). Never add SJ bands into the total.
- If
targetTotalis set, lead with gap to target and ~points per section. - Name question subtypes from topic/timing tools (e.g. “logic puzzles”, “tables”, “full Q without keywords”) — not just “work on VR”.
- Separate time sinks (slow zeros) from fast guesses (sub-budget zeros) — different fixes.
- Prefer a Cursor canvas for multi-mock charts/tables; keep chat to verdict + priorities.
- Empty
mocks/ failed auth → say so and stop. No fabricated history.
Tool map
| Need | Tool | Key args |
|---|---|---|
| Auth health | check_connection |
— |
| Refresh cache | refresh_scores |
— |
| Raw mock list | list_completed_mocks |
kind, forceRefresh |
| One mock | get_mock_details |
id |
| Score history | analyze_score_trends |
kind |
| Section rank | analyze_section_performance |
kind |
| Subtype accuracy | analyze_topic_performance |
includeSj, minN |
| Timing / sinks | analyze_question_timing |
limit, minN |
| Practice plan | recommend_focus_areas |
kind, includeSj, targetTotal |
| Diff two sits | compare_mocks |
idA, idB |
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.
- 3d ago First seen · 65 lines · 72 tokens per session scan A 30e7540dfcb7
medify-ucat-analysis is a skill published in the GitHub repository ankitforcode/medify-mcp-server (1 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 936 once invoked, about $0.0004 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
article-writing
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
ljg-learn
Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy) and compresses insights into an epiphany. Use when user asks to explain, dissect, or deeply understand a concept, term, or…
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
code-documenter
Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.
deck-course-module
暖纸背景 + Playfair, 左侧学习目标常驻, 含 MCQ 自测页.
grid-ctf-ops
Operational knowledge for the gridctf scenario including strategy playbook, lessons learned, and resource references. Use when generating, evaluating, coaching, or debugging gridctf strategies.