Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligencenpx agentmods add commands/agentii-ai/agentii-investment-intelligence/earnings-previewWrote 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/commands/agentii-ai/agentii-investment-intelligence/earnings-preview)<a href="https://agentmods.dev/commands/agentii-ai/agentii-investment-intelligence/earnings-preview"><img src="https://agentmods.dev/badge/commands/agentii-ai/agentii-investment-intelligence/earnings-preview/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/commands/agentii-ai/agentii-investment-intelligence/earnings-preview"><img src="https://agentmods.dev/badge/commands/agentii-ai/agentii-investment-intelligence/earnings-preview.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 | $0.00020 | $0.00152 |
| Opus 5 | $0.00010 | $0.00076 |
| Sonnet 5 | $0.00004 | $0.00030 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
earnings-preview 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 11d 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
Workflow
- Validate ticker argument.
- Delegate to the
earnings-previewskill bundled undermodels-and-pitches. - Return the structured deliverable produced by the skill. Output written to
{ticker}/{YYYY-MM-DD_HHMM}_earnings-preview_{affix}.md.
See Mode syntax for
--mode=/--modes=/--peers=invocation rules.
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.
- 11d ago First seen · 13 lines · 20 tokens per session scan A d84c296c61bf
earnings-preview is a command published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed today), licensed Apache-2.0. It adds 20 tokens to every session and 152 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.
Other commands, from other repositories
burn-rate
Compute the recent 7-day spend trend (burn rate) from daily sessions and per-session cost.
monitor
AML transaction monitoring and suspicious activity reporting.
financials-review
Open a financials extraction session for review and publish it. Deterministic entry into the carta-financials skill's review route.
rig-estimate
You are creating a formal cost estimate document that can be used for internal approval, accountant review, or VAT deduction purposes.
tutorial
Write a Diátaxis tutorial as Markdown in the user's repository. Use when invoked as /document-design-system:tutorial. Produce designed HTML or PDF only when asked.
checklist
Generate a custom checklist for the current feature based on user requirements.