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 agentmods add commands/ololand-ai/ololand-plugins/earnings-analysisgit clone --depth 1 https://github.com/ololand-ai/ololand-pluginsWrote 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/ololand-ai/ololand-plugins/earnings-analysis)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/earnings-analysis"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/earnings-analysis.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00397 |
| Opus 5 | $0.00012 | $0.00198 |
| Sonnet 5 | $0.00005 | $0.00079 |
| Haiku 4.5 | $0.00002 | $0.00040 |
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 6d 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
Earnings Analysis
Run the deal-scoped earnings-call workbench. Use this for public-company targets, public comps, or any target with management-call transcripts that should feed diligence.
Usage
/earnings-analysis <deal_id> <transcript_or_segments>
Arguments
deal_id(required) - The deal to analyze.segments(required) - Transcript segments. Accept a pasted transcript, a local file path, or structured segment objects.company_name(optional) - Company name to display in the analysis.call_date(optional) - Call date.
Execution
- If the user provides a file path, read the transcript and split it into speaker-aware segments when possible.
- Call
analyze_earnings_call(deal_id, segments, company_name, call_date). - Use the returned
view_urlfor web app handoff.
Output
Render:
- Management tone - sentiment, vocal/tone stress where available, and notable topic shifts.
- Guidance deltas - changed revenue, EBITDA, margin, cash-flow, or capex expectations.
- Risk signals - evasive answers, customer concentration, pricing pressure, churn, regulatory, liquidity, covenant, or working-capital flags.
- Follow-up asks - documents or management questions that should enter the diligence request list.
Guardrails
- Do not overstate vocal stress as deception. Treat it as a diligence signal that needs corroborating evidence.
- Preserve citations or transcript timestamps for any quote or numerical claim.
Output URL Conventions
Use the tool-returned view_url. Canonical surface:
- Earnings analysis:
https://app.ololand.ai/deals/{deal_id}/analysis/earnings
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.
- 6d ago First seen · 47 lines · 23 tokens per session scan A e5cd410a6641
earnings-analysis is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 397 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 2026-08-31.
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