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 jamespud/yahoo-stock-mcp --skill earnings-event-researchgit clone --depth 1 https://github.com/jamespud/yahoo-stock-mcpWrote 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/jamespud/yahoo-stock-mcp/earnings-event-research)<a href="https://agentmods.dev/skills/jamespud/yahoo-stock-mcp/earnings-event-research"><img src="https://agentmods.dev/badge/skills/jamespud/yahoo-stock-mcp/earnings-event-research/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/jamespud/yahoo-stock-mcp/earnings-event-research"><img src="https://agentmods.dev/badge/skills/jamespud/yahoo-stock-mcp/earnings-event-research.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 | $0.00076 | $0.01183 |
| Opus 5.5 | $0.00030 | $0.00473 |
| Sonnet 5.5 | $0.00015 | $0.00237 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
earnings-event-research 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 13d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings and event research
Answer earnings questions from stored data: when the next report is due, how the last one landed, which way estimates and analyst actions have moved, and what the market has had time to price in.
Read references/data-policy.md first, then the event checklist for the pre/post workflow and the reporting shape.
MCP tools used
get_company_events- forward-looking calendar: next earnings date, earnings call, ex-dividend and dividend datesget_earnings- reported history: EPS and revenue, actual vs estimate, per reportget_earnings_trend- quarterly estimates with growth and 7/30/60/90-day revision historyget_analyst_actions- dated upgrades, downgrades, and price-target changes with the firm namedget_recommendation_trend- monthly rating distribution (strong buy through strong sell)get_analyst_forecast- consensus snapshot: buy/hold/sell counts and price targetsget_quote- the price anchor used to date-stamp any market reaction referencesync_stock- when these tables are empty or stale
Workflow
- Place the symbol in time. Call
get_company_eventsfor the next scheduled events, thenget_earningsfor what has actually been reported. The first gives the calendar; the second gives history. Both are needed before any "beat/miss" statement. - Anchor the price. Call
get_quotefor the latest stored bar and its date. The reaction to an earnings report only exists if stored bars span the report date; check that before describing one. - Read the revision trend. Call
get_earnings_trendand compareeps_currentagainsteps_7d_ago,eps_30d_ago,eps_60d_ago, andeps_90d_ago, alongside theup_*/down_*analyst counts. This is where estimate momentum lives; report the direction and the horizon, not just the latest number. - Add analyst actions when the user asks about ratings or targets. Call
get_analyst_actionsfor dated firm-level changes, andget_recommendation_trendorget_analyst_forecastfor the aggregate. Distinguish a survey of ratings from individual actions. - Write it up. Follow the checklist's pre-earnings and post-earnings layouts.
What ships with it
2 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.
- 13d ago Changed 82b8b32b03b3
- 17d ago First seen · 73 lines · 76 tokens per session scan A 493f37122a86
earnings-event-research is a skill published in the GitHub repository jamespud/yahoo-stock-mcp (0 stars, last pushed 5d ago), licensed MIT. It adds 76 tokens to every session and 1,183 once invoked, about $0.0003 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 2026-09-28.
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