v0.2.0 to v0.3.0

28 added, 14 removed. Audit A to A.

---

name: competitor-mindshare

- description: This skill should be used when the user wants to run the Competitor Tracker skill, or asks to "measure competitor mindshare", "track how much people talk about <brand> on X", "compare brand chatter", or wants a recurring share-of-voice measurement with a shareable dashboard. Runs on the superagnt MCP: X search + workspace database + canvas, with an optional daily hosted run.

- version: 0.2.0

+ description: This skill should be used when the user wants to run the Competitor Tracker skill, or asks to "measure competitor mindshare", "track how much people talk about <brand> on X", "compare brand chatter", or wants a recurring share-of-voice measurement with a shareable dashboard. Runs on the superagnt MCP: X search + workspace database + the workspace dashboard, with an optional daily hosted run.

+ version: 0.3.0

---

# Competitor Tracker

Measure posts-per-hour and engagement for a fixed brand set with an identical

method every day, so the trend is real. The methodology is the one from the

public superagnt research reports: identical queries, literal-match

filtering, and rates computed from the returned page's own timestamps.

## Step 0 — tools

`agnt_tools_list_enabled`; if missing:

- `agnt_tools_enable({ "families": ["data:x", "database", "canvas_share"] })`.

+ `agnt_tools_enable({ "families": ["data:x", "database"] })`.

`requires_upgrade` → hand the `confirm_url` to the user, wait, re-run.

- (The competitor-mindshare skill endpoint pre-enables these.)

+ (The competitor-mindshare skill endpoint pre-enables these. The workspace

+ dashboard's tools, `agnt_dashboards_*`, are on for every workspace.)

## 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_write`, action `insert`

- `agnt_db_apply_migration` → `agnt_db_sql`, action `apply_migration`

- - `agnt_canvas_introspect_schema` / `agnt_canvas_preview_query` → `agnt_canvas_read`, action `introspect_schema` / `preview_query`

- - `agnt_canvas_put_widget` / `agnt_canvas_set_layout` / `agnt_canvas_share_create` → `agnt_canvas_write`, action `put_widget` / `set_layout` / `share_create`

+ - `agnt_dashboards_guide` / `agnt_dashboards_preview` → `agnt_dashboards_read`, action `guide` / `preview`

+ - `agnt_dashboards_write_file` / `agnt_dashboards_publish` → `agnt_dashboards_write`, action `write_file` / `publish`

- `agnt_agents_create` → `agnt_agents_write`, action `create`

- `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 — name the brands (first run only)

The user lists brands/products to track (include their own). Record query

variants per brand — people abbreviate product names — in

`mindshare_brands(id, brand, variants text[], active)`. Create

`mindshare_daily(id, brand_id, measured_at timestamptz, posts_per_hour

numeric, median_likes numeric, sample_size int, top_post_url text)` via

`agnt_db_apply_migration`.

## Step 2 — measure

Per brand, identically: `data_x_search_get_search_search`

(section=latest, fixed like-floor, same limit for every brand). Filter the

returned page CLIENT-SIDE to posts whose text literally contains a brand

variant — the endpoint fuzzy-matches, and skipping this step inflates

everything. Rate = matching posts ÷ the span between the page's first and

last timestamps. Median likes over the matches. One `agnt_db_insert` row per

brand per day.

Method caveats to state in any summary: mindshare ≠ market share; gaps under

~1.5x are noise; generic brand names (a common word) over-count and need

tighter variants.

- ## Step 3 — the dashboard

+ ## Step 3 — the scoreboard view

- First run: `agnt_canvas_introspect_schema` →

- `agnt_canvas_preview_query` (aggregate in SQL, `group by` day and brand) →

- `agnt_canvas_put_widget`: a trend line per brand, a KPI row with today's

- rates, and a table of the latest measurements. `agnt_canvas_set_layout`,

- then — with the user's explicit OK — `agnt_canvas_share_create` for the

- public link. Later runs just insert rows; the canvas stays current on its

- own.

+ First run: `agnt_dashboards_guide` once (the files, the query grammar, the

+ `sa-*` elements and publishing). Then build one view, `mindshare`, in your

+ draft with `agnt_dashboards_write_file` (pass `intent` on the first write):

+ - `queries/mindshare_today.sql`: today's posts per hour and median likes per

+ brand, highest first.

+ - `queries/mindshare_trend.sql`: one row per day, oldest first, one column

+ per brand (pivot in SQL: `max(d.posts_per_hour) filter (where b.brand =

+ 'Acme') as acme`).

+ - `views/mindshare.html`: an `sa-chart` kind `hbar` over today's rates, an

+ `sa-chart` kind `line` over the trend (`y-fields` the brand columns,

+ `series-labels` the brand names), and an `sa-table` of the latest

+ measurements.

+ - the view's entry in `dashboard.json`.

+ `agnt_dashboards_preview` the view, fix what its report names, then

+ `agnt_dashboards_publish`. Later runs just insert rows; the view stays current

+ on its own (a new brand needs its column in the trend query, then publish).

+ To share the scoreboard, the user turns on the view's public link from the

+ superagnt app: agents can't make one.

## Step 4 — offer the daily run (a task agent)

Same pattern as every packaged skill: once one measurement pass has succeeded,

offer a daily run by building a task agent (recipe: the base `task-agents`

skill) — `agnt_agents_create` with a system prompt carrying step 2 verbatim

(brand table, query shape, insert), only the tools it uses, deploy, then

`agnt_schedules_create` (cadence confirmed; billed runs; a plan limit comes

back as `requires_upgrade` with a `confirm_url` for the user). Local-only

users just re-run the skill.

## Rules

- Never compare numbers measured with different query shapes, floors, or

limits — change the method, start a new series (add a `method_version`

column rather than mixing).

- Every published number traces to rows in `mindshare_daily`.