Borrowing it
Nothing to install: this file belongs to daloopa/investing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/daloopa/investing/main/.claude/skills/initiate/SKILL.mdgit clone --depth 1 https://github.com/daloopa/investingWrote 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/daloopa/investing/initiate)<a href="https://agentmods.dev/skills/daloopa/investing/initiate"><img src="https://agentmods.dev/badge/skills/daloopa/investing/initiate/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/daloopa/investing/initiate"><img src="https://agentmods.dev/badge/skills/daloopa/investing/initiate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.01144 |
| Opus 5 | $0.00010 | $0.00572 |
| Sonnet 5 | $0.00004 | $0.00229 |
| Haiku 4.5 | $0.00002 | $0.00114 |
Grade A, and why
initiate 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 10d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Initiate coverage on the company specified by the user: $ARGUMENTS
Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.
This is the capstone skill that produces both a research note and an Excel model from a single comprehensive data gathering pass.
Strategy
Rather than running /research-note and /build-model independently (which would duplicate data gathering), this skill gathers a superset of data once, then renders both outputs.
Phase 1 — Company Setup
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter— anchor for all period calculations (see../data-access.mdSection 1.5)latest_fiscal_quarter- Firm name for report attribution (default: "Daloopa") — see
../data-access.mdSection 4.5
Get market data (see ../data-access.md Section 2):
- Current price, market cap, shares outstanding, beta
- Trading multiples (P/E, EV/EBITDA, P/S, P/B)
- Risk-free rate (for DCF)
Phase 2 — Comprehensive Data Gathering
Follow the /build-model skill's Phase 2 data pull (the most comprehensive). Calculate 8-16 quarters backward from latest_calendar_quarter. Pull:
- Full Income Statement (Revenue through EPS, including D&A for EBITDA calc)
- Full Balance Sheet (Cash through Equity)
- Full Cash Flow Statement (OCF, CapEx, FCF, Dividends, Buybacks)
- Segment revenue and operating income breakdowns
- Geographic revenue breakdown
- All company-specific operating KPIs
- All guidance series and corresponding actuals
- Share count, buyback amounts
Phase 3 — Peer Analysis
Identify 5-8 comparable companies. Get peer trading multiples (see ../data-access.md Section 2). If consensus forward estimates are available (../data-access.md Section 3), include NTM estimates. Pull peer fundamentals from Daloopa where available (revenue growth, margins).
Phase 4 — Projections
If a projection engine is available (see ../data-access.md Section 5), use it. Otherwise project manually.
Write historical data to reports/.tmp/{TICKER}_initiate_input.json for reuse.
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.
- 10d ago First seen · 106 lines · 21 tokens per session scan A e341b2351a09
initiate is a skill published in the GitHub repository daloopa/investing (487 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 1,144 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 2026-08-30.
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