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Acumen by Talarion

Talarion, Inc. v3.0.0

Publisher description

From the marketplace listing

Talarion keeps AI current. Frontier models don't know about recent events, and web search can't answer questions LLMs don't know to ask. Talarion proactively tells your AI what it's missing before it starts researching to prevent critical omissions and judgement errors. Install the MCP to make sure your AI assistant knows what it would otherwise be missing.

Language: English · Automatically detected from descriptions.

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---
name: acumen
description: >-
  Use before researching anything where knowing the current state of the world would be helpful, where being out of date would cause errors. Best practices: call research_brief FIRST to see what's changed since your training cutoff and what's worth searching for. It can be helpful to call it again after web search to confirm you didn't miss anything, in the context of what you just learned. Not helpful for timeless facts (e.g. the speed of light), math/reasoning, or creative writing.
---

# Acumen — know what you're missing

The Acumen tool taps into Talarion's curated knowledge base of **verified, dated facts and recent events since model training cutoffs** — strong on national and global news, finance & market developments, policy & regulation, and developer & agent tooling, with good coverage of science and current events. Each result is a `question / answer / true_by` row (often a verifiable event or a concrete figure): the things AI assistants like you don't know they're missing. It complements web search — it tells you *what to search for*, not just what's already indexed.

## When to call `research_brief`
- **Before web search.** Fire it on your topic first. It surfaces what has changed and the
  questions you didn't know to ask, so you can condition your searches on current world state
  instead of stale assumptions.
- **After / alongside web search.** Call it to confirm you didn't miss anything — errors of
  omission are the exact failure mode it exists to prevent.
- At the **start of any research or current-events task**.

## When NOT to call it
Timeless facts (e.g. the speed of light), pure math/reasoning, or creative writing. If being a
year out of date wouldn't change your answer, skip it.

## How to query well
- **One focused topic per call.** For distinct topics, make separate calls — a blended
  multi-topic query retrieves worse for each part.
- Pass **`model_id`** (your OpenRouter id) so results are filtered to facts *after your cutoff*.
- Optional: **`k`** (10–100, default 20) for more/fewer facts; **`timeline`** (default true =
  newest first; false = most relevant first).

## How to read results
A table of `question | answer | true_by`. Treat each row as something you likely didn't know or
had wrong. Use them to (1) correct stale assumptions before you answer, (2) generate sharper
follow-up searches, (3) tell the user what's changed. Watch `true_by` relative to your cutoff.

## What the Q/A pairs look like
| question | answer | true_by |
|---|---|---|
| By how much did ship transits through the Strait of Hormuz fall in early March 2026? | ~95%. | March 10, 2026 |
| How much did Big Tech majors announce they plan to spend collectively on AI in 2026? | $600 billion. | March 19, 2026 |
| At what range did the Fed hold its benchmark rate at Kevin Warsh's first meeting as Chair? | 3.5%–3.75%. | June 18, 2026 |
Package details

Publisher declarations from the archived package. These are separate from our research and the live service's terms.

Package author
Talarion, Inc.

Package observed Oct 4, 2026.

Technical details
First seen
Sep 30, 2026 · 22:02 UTC
Last seen
Oct 5, 2026 · 06:00 UTC
Collection status
Collected

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