# Imagine AI Benchmark

> LinkedIn content benchmark for 900+ B2B companies and their teams, with an open scoring method.

- name: ai.useimagine/benchmark
- version: 0.1.0
- connection class: R0 (autonomous)
- trust: 83/100 flags: no-repository
- quality: 85/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/ai.useimagine%2Fbenchmark
- tools: https://api.protogrid.dev/v1/servers/ai.useimagine%2Fbenchmark/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "benchmark": {
      "type": "http",
      "url": "https://benchmark.useimagine.ai/api/mcp",
      "headers": {
        "Authorization": "Bearer ${BENCHMARK_TOKEN}"
      }
    }
  }
}
```

Placeholders to fill: `${BENCHMARK_TOKEN}`.

## Trust

- hygiene: 80
- liveness: 100
- freshness: 100
- provenance: 55
- drivers: +dns-namespace +website +reachable +uptime-100% +updated-10d-ago -no-repository
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 85/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-06-18; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 86 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 5 of 5 tools declare readOnlyHint or destructiveHint
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: list_companies (destructiveHint, idempotentHint, openWorldHint); company_fit_summary (destructiveHint, idempotentHint, openWorldHint); industry_landscape (destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 1,212 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: 5 tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 5, about 1,212 tokens to load them all
- tool set hash: 3d9587936ac9ea03d7537c19fbc4a29e
- tools last changed: 2026-10-17T17:58:58.200Z
- badge: [![protogrid quality](https://protogrid.dev/badge/ai.useimagine/benchmark.svg)](https://protogrid.dev/servers/ai.useimagine/benchmark)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-17 `company_fit_summary` changed (description)
  - before: A company's page fit plus the distribution of its people's geometric means (median, baseline band), top people and who is under the 18-post floor. Company score = median of its 5 most active fitted people (by original posts in the last 90 days) plus the company page. With exactly one fitted account (a person or the page) the company ranks on that account's own fit, flagged "1 account"; it is held back while teammates still await their history pull. people.counted / countedPersonIds say who is in. Use for 'how is X doing on LinkedIn'.
  - after: A company's page fit plus the distribution of its people's geometric means (median, baseline band), top people and who is under the 18-post floor. Company typical post = median over up to 5 counted fitted people plus the company page: founders, CEO and C-suite who posted in the last 90 days first, then the most active fitted people (by original posts in that window). With exactly one fitted account (a person or the page) the company ranks on that account's own fit, flagged "1 account"; it is held back while teammates still await their history pull. people.counted / countedPersonIds say who is in. Use for 'how is X doing on LinkedIn'.
- 2026-10-15 `industry_landscape` changed (description)
  - before: Every account in an industry (or a custom company set): per-company rollup (page fit + people median over the 5 most active fitted people (peopleCounted), preliminary = "Few posts" under 40 team posts), population vs the research baseline, and category lift with the author effect removed (which post types beat each author's own typical post). Public callers get bands and pooled lifts, the same as Discover. Use for "what works in fintech" or "where does X sit in its market".
  - after: Every account in an industry (or a custom company set): per-company rollup (page fit + people median over the 5 most active fitted people (peopleCounted), preliminary = "Few posts" under 40 team posts, solo = "1 account" when one fitted account carries the company), population vs the research baseline, and category lift with the author effect removed (which post types beat each author's own typical post). Public callers get bands and pooled lifts, the same as Discover. Use for "what works in fintech" or "where does X sit in its market".
- 2026-10-15 `company_fit_summary` changed (description)
  - before: A company's page fit plus the distribution of its people's geometric means (median, baseline band), top people and who is under the 18-post floor. Company score = median of its 5 most active fitted people (by original posts in the last 90 days) plus the company page; needs 2+ fitted accounts. people.counted / countedPersonIds say who is in. Use for 'how is X doing on LinkedIn'.
  - after: A company's page fit plus the distribution of its people's geometric means (median, baseline band), top people and who is under the 18-post floor. Company score = median of its 5 most active fitted people (by original posts in the last 90 days) plus the company page. With exactly one fitted account (a person or the page) the company ranks on that account's own fit, flagged "1 account"; it is held back while teammates still await their history pull. people.counted / countedPersonIds say who is in. Use for 'how is X doing on LinkedIn'.
- 2026-10-13 `industry_landscape` changed (inputSchema)
- 2026-10-13 `list_companies` changed (inputSchema)

Full history: https://api.protogrid.dev/v1/servers/ai.useimagine%2Fbenchmark/changes

## Remotes

- https://benchmark.useimagine.ai/api/mcp (streamable-http, auth none, reachable true, uptime30d 1)

## Packages

_none_

## Tools (5)

- `category_breakdown`: Post counts and engagement per content category (product update, hiring, personal story, industry insight, ...) for companies or people.
- `company_fit_summary`: A company's page fit plus the distribution of its people's geometric means (median, baseline band), top people and who is under the 18-post floor. Company typical post = median over up to 5 counted fitted people plus the company page: founders, CEO and C-suite who posted in the last 90 days first, then the most active fitted people (by original posts in that window). With exactly one fitted account (a person or the page) the company ranks on that account's own fit, flagged "1 account"; it is held back while teammates still await their history pull. people.counted / countedPersonIds say who is in. Use for 'how is X doing on LinkedIn'.
- `industry_landscape`: Every account in an industry (or a custom company set): per-company rollup (page fit + people median over the 5 most active fitted people (peopleCounted), preliminary = "Few posts" under 40 team posts, solo = "1 account" when one fitted account carries the company), population vs the research baseline, and category lift with the author effect removed (which post types beat each author's own typical post). Public callers get bands and pooled lifts, the same as Discover. Use for "what works in fintech" or "where does X sit in its market".
- `list_companies`: List companies in the benchmark catalog (customers, competitors, industry peers). Filter by name substring, industry, or tracking. Returns ids you pass to every other tool.
- `methodology`: Imagine AI research rules (log-normal engagement, geometric means, research baseline 49/77/130). Call once before interpreting any numbers.