QVeris
Skill Hub/x-founder-operations
OfficialVerifiedOperations / Daily workflow

Founder content operations

by QVeris

Use this when founders or growth teams need an agent that can monitor content platforms, analyze public signals, and help plan posts with evidence instead of guesses.

Task value

Research topics, monitor platform signals, and turn social data into founder-ready content workflows.

Best for

Operators, monitors, and team briefing agents

Expected output

A structured brief with evidence, missing data, and follow-up checks.

Supported agents3
Workflow cases2
Estimated credits3-80 credits
SocialContentTikHubGrowth
Source repoManifest

Case Workflows

Each article or tutorial is treated as a reusable workflow source: content, copied prompt, QVeris API recipe, and expected output.

Content source

Product article

TikHub content platform signals

Understand platform momentum across short video, social, commerce, and local life content.

Copied prompt

Research how AI agent infrastructure is being discussed across short-video and social platforms. Find evidence, summarize recurring narratives, and propose three founder posts grounded in the data.

QVeris API calls
DiscoverInspectCall
Expected result

Workflow brief · Markdown brief

Open case
Content source

Use case

Map stories from public data

Turn scattered public information into structured storytelling input.

Copied prompt

Scan public content signals for three competitors in our category. Identify their strongest narratives, most repeated user objections, and opportunities for our next post.

QVeris API calls
DiscoverInspectCall
Expected result

Execution checklist · Checklist

Open case

Prompt Templates

Starter prompts that turn the skill into executable agent work.

Platform signal report

Use public content-platform signals to explain what is gaining traction.

Research how AI agent infrastructure is being discussed across short-video and social platforms. Find evidence, summarize recurring narratives, and propose three founder posts grounded in the data.

Competitor content scan

Turn competitor activity into actionable content planning.

Scan public content signals for three competitors in our category. Identify their strongest narratives, most repeated user objections, and opportunities for our next post.

Expected Outputs

The formats an agent should return after the workflow runs, with enough structure for reuse and auditing.

Markdown brief

Workflow brief

Combine the task, sources, result, and limitations into a reusable output.

Sections
  • Scope
  • Source evidence
  • Result
  • Limitations
Checklist

Execution checklist

Show the agent and user what has been done and what still needs verification.

Sections
  • Completed steps
  • Called sources
  • Open questions
Trace

Usage record

Record QVeris actions, paid-call count, and estimated credits.

Sections
  • API actions
  • Calls
  • Estimated credits

QVeris API Recipe

The concrete Discover, Inspect, and Call sequence this skill expects the agent to run.

Recipe step 01DiscoverPOST /search

Find content platform capabilities

Search for short-video, social, creator, post, comment, product, or local-life platform data capabilities.

Sample query: short video platform content signal API

TikHubsocial platform data providers
Recipe step 02InspectPOST /tools/by-ids

Inspect platform schemas

Confirm whether a capability supports accounts, posts, videos, comments, product data, or trend search.

TikHub capability schemas
Recipe step 03CallPOST /tools/execute

Call signal sources

Execute selected platform capabilities and turn raw signals into a founder-ready content brief.

TikHub

QVeris Usage & Cost

A planning estimate before execution. Discover and Inspect are free; successful Call execution follows the selected provider billing rule.

Typical paid calls3-8
Estimated credits3-80 credits
Free actions
DiscoverInspect
Paid action
Call

Content signal workflow

Content research typically calls search, account, post, or trend capabilities after free discovery and inspection.

Cost scales with the number of platforms, accounts, competitors, and result pages the agent requests.

Installation

Install the skill in the target agent environment. Agents must ask before running commands or changing local configuration.

Official GitHub source

This is the source of record for QVeris skills. Inspect or fork the skill folder before installing it in an agent environment.

Open source
Source pathQVerisAI/open-qveris-skills/x-founder-operations
git clone https://github.com/QVerisAI/open-qveris-skills.git && cd open-qveris-skills/x-founder-operations
Install skillOpenClaw
openclaw skills install x-founder-operations

Agent Execution Flow

The visible chain the agent should expose after the user copies a prompt.

01

Describe the job

The agent turns a user request into capability-oriented search intent.

02

Discover candidates

QVeris returns ranked capabilities with quality, latency, and pricing signals.

03

Inspect and choose

The agent checks parameters, examples, and provider signals before calling.

04

Call and compose

The selected capability is executed and the agent turns results into the final workflow output.

Install policy

Read manifest and agent.md first. Explain the install command, API actions, and possible credit usage. Wait for explicit approval before making local changes.

Founder content operations — Skill Hub | QVeris