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 Haochenhust/ch-skills --skill valuation-calculatorgit clone --depth 1 https://github.com/Haochenhust/ch-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/haochenhust/ch-skills/valuation-calculator)<a href="https://agentmods.dev/skills/haochenhust/ch-skills/valuation-calculator"><img src="https://agentmods.dev/badge/skills/haochenhust/ch-skills/valuation-calculator/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/haochenhust/ch-skills/valuation-calculator"><img src="https://agentmods.dev/badge/skills/haochenhust/ch-skills/valuation-calculator.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 | $0.00092 | $0.00895 |
| Opus 5 | $0.00046 | $0.00447 |
| Sonnet 5 | $0.00018 | $0.00179 |
| Haiku 4.5 | $0.00009 | $0.00089 |
Grade A, and why
valuation-calculator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Valuation Calculator
Quantitative, relative valuation for investment decisions (PE/PB percentiles + peer comparison + target price). For absolute DCF-style intrinsic value, use the intrinsic-value-analysis skill instead.
When to Use
- During stock analysis (the valuation step)
- When deciding a target price for a trade
- When comparing multiple candidates in the same sector
Prerequisites
Uses the sibling tushare-data / stock-market-data skills. Set once per shell:
export TUSHARE_TOKEN=<your Tushare Pro token> # never hard-code; see the tushare-data skill
PY=python3 # a python3 with tushare/pandas/akshare (e.g. stock-market-data/.venv/bin/python3)
SKILLS=~/.claude/skills # where you installed these skills
TS=$SKILLS/tushare-data/scripts/fetch_tushare.py
AK=$SKILLS/stock-market-data/scripts
Methods
1. Historical Percentile
Use Tushare daily_basic for direct PE/PB/PS time series (no manual calculation needed):
# Get 3-year PE/PB/PS history for percentile calculation
$PY $TS --mode daily_basic --symbols {CODE}.SZ --start 20230101
From the returned data:
- Calculate PE_TTM percentile over available history
- Calculate PB percentile over available history
- Identify current position in historical range
2. Peer Comparison
# Tushare: valuation + financial ratios for each peer
$PY $TS --mode daily_basic --symbols {code1}.SZ --start 20260301
$PY $TS --mode fina_indicator --symbols {code1}.SZ
# Repeat for each peer...
# Fallback: AKShare (batch)
$PY $AK/fetch_financial_data.py --mode stock --symbols {code1},{code2},{code3}
Compare: PE, PB, ROE, revenue growth, net margin across peers. Identify: who is cheapest relative to growth? (PEG ratio)
Supplement with WebSearch for analyst consensus (券商一致预期), forecasts, and cross-sector peer comparison data:
WebSearch: "{stock name} 一致预期 估值 目标价"
3. Target Price Derivation
Methods available:
- PE-based: Target PE × Expected EPS = Target Price
- PB-based: Target PB × Book Value = Target Price
- DCF-simplified: skip here; use the
intrinsic-value-analysisskill for a proper DCF-style approach
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.
- 12d ago First seen · 100 lines · 92 tokens per session scan A c4394bcaf6aa
valuation-calculator is a skill published in the GitHub repository Haochenhust/ch-skills (9 stars, last pushed 2mo ago), licensed MIT. It adds 92 tokens to every session and 895 once invoked, about $0.0005 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.
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