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 ololand-ai/ololand-plugins --skill merger-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/skills/ololand-ai/ololand-plugins/merger-analysis)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/merger-analysis"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/merger-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 | $0.00065 | $0.00941 |
| Opus 5 | $0.00032 | $0.00470 |
| Sonnet 5 | $0.00013 | $0.00188 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
merger-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 4d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Merger Analysis (third-party perspective)
OloLand's third_party_merger perspective treats both the target and the acquirer as first-class entities. The user is an outside observer — never a principal — and every output frames evidence from both sides.
Triggering phrases
Invoke /dd-merger-analyze "<their phrasing>" whenever the user says any of:
- "examine the acquisition of X by Y"
- "analyze the X-Y merger"
- "is the [deal] accretive?"
- "what's the premium on [deal]?"
- "what's the HHI on [deal]?"
- "could [deal] survive antitrust review?"
If the phrasing is ambiguous about which company is the target vs. acquirer, ask back; do not guess.
What the deal looks like
/dd-merger-analyze creates a deal stamped perspective=third_party_merger and dispatches three ingestion lanes in parallel:
- Lane A — target-side ingestion (10-K, 10-Q, target market intel)
- Lane B — acquirer-side ingestion (same)
- Lane C — combined-entity artifacts (announcement 8-K, S-4 proxy if filed, antitrust filings)
Each side then carries a per-side data-readiness tier: high, medium, low, or missing. The four deterministic engines (premium, accretion/dilution, antitrust HHI, combined DCF) refuse to run when required inputs are missing — they never impute.
Cockpit hero tiles
After ingestion, direct the user to the cockpit (view_url). It exposes five hero tiles plus per-side risk and financial tiles:
- Deal terms — offer mix (cash / stock / mixed), enterprise value, exchange ratio.
- Premium analysis — premium vs unaffected price, 52wk high, 30d VWAP, percentile within sector precedents.
- Accretion / dilution — Year 1/2/3 EPS impact + breakeven synergy threshold.
- Antitrust HHI — pre/post HHI per market definition, DOJ presumptive-challenge flag.
- Combined-entity DCF — pro-forma valuation with synergy delta block.
Engine usage discipline
- Engines before prose. Quote engine outputs; do not state premium / EPS impact / HHI from your own reasoning.
- Cite per side. Every numeric claim ends in a citation. Use
[T:N],[A:N],[C:N]prefixes per the merger-mechanics skill (target / acquirer / combined-entity document). - Surface insufficiency. When a
run_*engine returnsINSUFFICIENT_DATA, tell the user which fields are missing and where they would typically come from (e.g., "target unaffected price is unavailable — typically pulled from the 8-K Item 1.01 filing window"). - Two-sided risk. Scope every taxonomy-classified risk to a side; never lump "merger risk" without saying whose.
- Don't pick a side. Frame "should X have done this deal?" answers as "evidence for/against from each side's perspective." You are not advocating for either principal.
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.
- 4d ago First seen · 59 lines · 65 tokens per session scan A 4a841f5deb0d
merger-analysis is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 65 tokens to every session and 941 once invoked, about $0.0003 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 2026-09-03.
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