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 cimomo/intrinsic --skill analyzegit clone --depth 1 https://github.com/cimomo/intrinsicWrote 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/cimomo/intrinsic/analyze)<a href="https://agentmods.dev/skills/cimomo/intrinsic/analyze"><img src="https://agentmods.dev/badge/skills/cimomo/intrinsic/analyze.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 5.1 | $0.00011 | $0.00306 |
| Opus 5 | $0.00005 | $0.00153 |
| Sonnet 5 | $0.00002 | $0.00061 |
| Haiku 4.5 | $0.00001 | $0.00031 |
Grade A, and why
analyze 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 7d 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
Perform a comprehensive stock analysis for ticker symbol $ARGUMENTS by orchestrating the sub-skills in sequence.
Orchestration Steps:
1. Fetch Data
- Display: "Step 1/5: Fetching data..."
- Invoke
/fetch {ticker}to fetch all sources with fresh data (including current quote price)
2. Research
- Display: "Step 2/5: Researching..."
- Invoke
/research {ticker}
3. Calibrate Assumptions
- Display: "Step 3/5: Calibrating assumptions..."
- Invoke
/calibrate {ticker}— walks through each assumption with research context and data-driven recommendations
4. Valuation
- Display: "Step 4/5: Running valuation..."
- Invoke
/value {ticker}
5. Report
- Display: "Step 5/5: Generating report..."
- Invoke
/report {ticker}
Important Notes:
- Each sub-skill handles its own data loading, saving, and display
- This skill is a thin orchestrator — all logic lives in the sub-skills
- If any sub-skill fails, stop and report the error rather than continuing
- Pipeline: fetch → research → calibrate → value → report. Each step depends on the prior step's output.
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.
- 7d ago First seen · 35 lines · 11 tokens per session scan A 490ea75c3955
analyze is a skill published in the GitHub repository cimomo/intrinsic (4 stars, last pushed 4mo ago), licensed MIT. It adds 11 tokens to every session and 306 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 2026-08-31.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
vectorbt
High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics.