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Audience Radar

ASecurity

This skill should be used when the user wants to run the Content Ideas Engine skill, or asks to "find out what my audience talks about", "mine X for content ideas", "research what's working in my niche on X/Twitter", or wants a recurring content-research sweep with a cited ideas report. Runs on the superagnt MCP: X search + workspace database, with an optional nightly hosted run.

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  • Added September 23, 2026
ai-agentssqlgitdatabase

Works with

  • mcp

Security analysis

A100/100

Scanned October 5, 2026

npx -y skills add superagnt/leverage --skill audience-radar --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: audience-radar
description: This skill should be used when the user wants to run the Content Ideas Engine skill, or asks to "find out what my audience talks about", "mine X for content ideas", "research what's working in my niche on X/Twitter", or wants a recurring content-research sweep with a cited ideas report. Runs on the superagnt MCP: X search + workspace database, with an optional nightly hosted run.
version: 0.2.0
---

# Content Ideas Engine

Mine X for what the user's audience actually talks about; file the signal;
write a cited ideas report. The recipe compounds: every sweep builds on the
tables the last one left.

## Step 0 — tools

`agnt_tools_list_enabled`; if `data:x` or `database` families are missing,
`agnt_tools_enable({ "families": ["data:x", "database"] })`. A
`requires_upgrade` result carries a `confirm_url` — give it to the user and
wait, then re-run. (Connecting through the audience-radar skill endpoint
pre-enables these.)

## Tool names on grouped servers

This skill writes flat (per-operation) tool names. New superagnt servers list
grouped tools instead: one tool per resource with an `action` argument. Flat
names still resolve there but are not listed, so call the grouped form:

- `data_x_search_get_search_search` → `data_x_discover`, action `search`
- `agnt_db_insert` / `agnt_db_upsert` → `agnt_db_write`, action `insert` / `upsert`
- `agnt_db_select` → `agnt_db_read`, action `select`
- `agnt_db_apply_migration` → `agnt_db_sql`, action `apply_migration`
- `agnt_agents_create` / `agnt_agents_deploy` → `agnt_agents_write`, action `create` / `deploy`
- `agnt_schedules_create` → `agnt_schedules_write`, action `create`
- `agnt_tools_enable` → `agnt_tools_write`, action `enable`

On a grouped server every data source is already on, so skip the `data:*`
part of Step 0 (enable any other family with `agnt_tools_write`, action
`enable`). Grouped data calls return a compact markdown view: pass
`response_format: "json"` for every view field, or `"raw"` for the full
payload, when a step needs a field the table leaves out.

## Step 1 — define the radar (first run only)

Ask the user for their niche, audience, and 3–5 accounts they rate. Derive
8–12 standing searches: topic phrases, "how do I"-shaped questions, tool
names, and the rated accounts' handles. Sensible engagement floors (10–50
likes; higher for noisy topics). Store them:

- `radar_queries(id, query, min_likes, active, created_at)` — via
  `agnt_db_apply_migration` then `agnt_db_insert`.
- `radar_posts(post_id primary key, query_id, author, text, likes, replies,
  url, posted_at timestamptz, seen_at timestamptz)`.

## Step 2 — sweep

For each active query: `data_x_search_get_search_search` (section=top, the
query's like floor). Upsert results into `radar_posts` on `post_id`
(`agnt_db_upsert`) so re-runs never duplicate. Pull reply threads only for
standout posts — replies are where unmet needs hide, and thread pulls cost
more credits than searches.

## Step 3 — report

From `radar_posts` since the last sweep (`agnt_db_select`): the patterns that
repeated, 3–5 posts worth replying to today, and 3–5 post ideas — EVERY idea
cites the post that earned its place (author + link + likes). No cite, no
idea. Keep the report under a page.

## Step 4 — offer the night shift (a task agent)

Once one sweep has succeeded end to end, offer to make it nightly by
building a task agent — the full recipe is the base `task-agents` skill.
Short form: `agnt_agents_create` with a system prompt carrying steps 2–3
verbatim (tables, queries, report shape), add ONLY the tools those steps use
(`agnt_tools_search` for the config refs), `agnt_agents_deploy`, then
`agnt_schedules_create` — cadence confirmed with the user first; every
firing is a billed run. The `lifecycle` and `schedules` families are on
every plan, and plans cap agents and schedules; `requires_upgrade` →
`confirm_url` → wait.
If the user prefers local-only, skip this and tell them to re-run the skill
whenever.

## Rules

- Never fabricate engagement numbers or post text — everything reported
  comes from a tool result or the table.
- This skill reads X; it never posts, replies, or DMs.

<!-- skill_id: audience-radar · source: https://github.com/superagnt/plugins -->

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