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 with-geun/alive-analysis --skill cursorgit clone --depth 1 https://github.com/with-geun/alive-analysisWrote 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/with-geun/alive-analysis/cursor)<a href="https://agentmods.dev/skills/with-geun/alive-analysis/cursor"><img src="https://agentmods.dev/badge/skills/with-geun/alive-analysis/cursor/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/with-geun/alive-analysis/cursor"><img src="https://agentmods.dev/badge/skills/with-geun/alive-analysis/cursor.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 | $0.00025 | $0.03392 |
| Opus 5.5 | $0.00010 | $0.01357 |
| Sonnet 5.5 | $0.00005 | $0.00678 |
| Haiku 4.5 | $0.00003 | $0.00339 |
Grade A, and why
alive-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 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 — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.
alive-analysis Skill (Cursor Edition)
Data analysis workflow kit based on the ALIVE loop. Optimized for Cursor's batch-oriented agent model.
Cursor-Specific Behavior
State management: Read .analysis/status.md and .analysis/config.md at the start of EVERY command. Write updates back to .analysis/status.md after EVERY action.
Question style: Present ALL questions at once in a structured form. Do NOT ask questions one by one — Cursor agents work best with batch input.
File-based context: There is no session memory. Always read state from files before acting.
Overview
alive-analysis structures data analysis using the ALIVE loop: Ask → Look → Investigate → Voice → Evolve
Two personas:
- Data analysts: Deep, systematic analysis with full ALIVE flow (5 files)
- Non-analyst roles (PM, engineers, marketers): Quick analysis with guided framework (1 file)
ALIVE Loop Summary
Stage 1: ASK
What do we want to know — and WHY?
- Define the problem clearly; confirm the requester's REAL goal
- Frame: causation ("Why did X happen?") vs correlation ("Are X and Y related?")
- Build a hypothesis tree before touching data
- Set success criteria and scope boundaries
- Use the Structured Data Request:
[Period] + [Subject] + [Condition] + [Metric] + [Output Format]
Stage 2: LOOK
What does the data ACTUALLY show — and what's missing?
- Review data quality (missing values, outliers, date ranges)
- Segment before averaging — never trust aggregates alone
- Check for confounding variables and external factors
- Map cross-service dependencies
- Validate data access methods
Stage 3: INVESTIGATE
Why is it REALLY happening — can we prove it?
- Eliminate hypotheses systematically (not just confirm the first one)
- Apply multi-lens analysis: macro → meso → micro
- Test causation vs correlation rigorously
- Perform sensitivity analysis for robustness
- Assign confidence levels to findings
Stage 4: VOICE
So what — and now what?
What ships with it
28 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.
- commands/analysis-agent.md 1.4 KB
- commands/analysis-archive.md 3.1 KB
- commands/analysis-dr.md 3.1 KB
- commands/analysis-init.md 9.4 KB
- commands/analysis-learn-hint.md 880 B
- commands/analysis-learn-next.md 2.0 KB
- commands/analysis-learn-review.md 2.4 KB
- commands/analysis-learn.md 2.6 KB
- commands/analysis-list.md 2.6 KB
- commands/analysis-new.md 26 KB
- commands/analysis-next.md 10 KB
- commands/analysis-promote.md 5.4 KB
- commands/analysis-retro.md 5.2 KB
- commands/analysis-search.md 5.5 KB
- commands/analysis-status.md 1.8 KB
- commands/analysis-wiki.md 2.7 KB
- commands/experiment-archive.md 2.9 KB
- commands/experiment-new.md 10 KB
- commands/experiment-next.md 14 KB
- commands/model-register.md 4.7 KB
- commands/monitor-check.md 6.1 KB
- commands/monitor-list.md 2.8 KB
- commands/monitor-setup.md 6.3 KB
- hooks/hooks-cursor.json 146 B
- hooks/post-analysis-action.sh 634 B runs code
- rules/alive-agents.mdc 12 KB
- rules/alive-analysis.mdc 2.6 KB
- rules/alive-decisions.mdc 3.1 KB
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 · 384 lines · 25 tokens per session scan A 80f46e5c14e1
alive-analysis is a skill published in the GitHub repository with-geun/alive-analysis (41 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 3,392 once invoked, about $0.0001 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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