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 HHFinAi/claude-equity-research-skills --skill earnings-analysisgit clone --depth 1 https://github.com/HHFinAi/claude-equity-research-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/hhfinai/claude-equity-research-skills/earnings-analysis)<a href="https://agentmods.dev/skills/hhfinai/claude-equity-research-skills/earnings-analysis"><img src="https://agentmods.dev/badge/skills/hhfinai/claude-equity-research-skills/earnings-analysis/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/hhfinai/claude-equity-research-skills/earnings-analysis"><img src="https://agentmods.dev/badge/skills/hhfinai/claude-equity-research-skills/earnings-analysis.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 | $0.00187 | $0.05311 |
| Opus 5.5 | $0.00075 | $0.02124 |
| Sonnet 5.5 | $0.00037 | $0.01062 |
| Haiku 4.5 | $0.00019 | $0.00531 |
Grade A, and why
earnings-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 — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Analysis: Institutional-Quality Quarterly Review Framework
Overview
This skill transforms raw earnings materials (filings, releases, transcripts) into structured investment-grade analysis. It moves beyond simple beat/miss reporting to diagnose why results deviated, what matters for the forward thesis, and what action follows — the way a senior buyside analyst processes a quarter.
Philosophy: The market doesn't pay for knowing what happened. It pays for knowing what changed, whether it's repeatable, and what's mispriced. Every earnings analysis must answer: "So what? What do I do now?"
Two-part architecture. The skill is a four-layer analytical framework (Parse → Compare → Diagnose → Decide) anchored by a Python scoring engine at scripts/score_earnings.py that produces a mechanical composite verdict, flag inventory, and expectations regime classification. The scorer runs at the end of Step 2 and anchors the judgment work in Steps 3 and 4 — it is an input to the diagnosis, not a replacement for it.
Input Types & Parsing Priority
The skill handles these inputs, in priority order:
| Input Type | What to Extract | How to Access |
|---|---|---|
| User-uploaded files | Full filing/transcript content | Read from /mnt/user-data/uploads/ using pdf-reading or file-reading skills |
| Earnings release / 8-K | Headline KPIs, segment data, guidance, non-GAAP reconciliation | Parse uploaded file or search web |
| 10-Q / 10-K filing | Revenue detail, margin breakdown, balance sheet, cash flow, MD&A | Parse uploaded file or search web |
| Earnings call transcript | Management tone, forward commentary, Q&A signals, guidance language | Parse uploaded file or search web |
| Consensus estimates | Revenue, EPS, margin expectations, whisper numbers | Web search (Yahoo Finance, Visible Alpha, Seeking Alpha) |
| Historical quarter data | Sequential and YoY comparison base | Web search or user-provided |
What ships with it
3 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.
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 · 420 lines · 187 tokens per session scan A c4995eff7938
earnings-analysis is a skill published in the GitHub repository HHFinAi/claude-equity-research-skills (10 stars, last pushed 6d ago), licensed MIT. It adds 187 tokens to every session and 5,311 once invoked, about $0.0007 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 2026-08-31.
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