# Spot Review Trends

> >-

- **Type:** Skill
- **Install:** `agentstack add skill-feedspace-feedspace-cookbook-spot-review-trends`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Feedspace](https://agentstack.voostack.com/s/feedspace)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Feedspace](https://github.com/Feedspace)
- **Source:** https://github.com/Feedspace/Feedspace-Cookbook/tree/main/plugins/feedspace-reviews/skills/spot-review-trends
- **Website:** https://feedspace.io

## Install

```sh
agentstack add skill-feedspace-feedspace-cookbook-spot-review-trends
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Spot review trends

Show how a batch of reviews changes over time: how many arrive per period, whether ratings are
climbing or slipping, how the sentiment mix shifts, and which themes are rising, steady, or fading.
Every trend is backed by the real per-period counts - no invented movement, no guessed causes. The
reviews can come from a Feedspace account through the Feedspace MCP, a CSV, or pasted text.

The full method lives in [references/trends-method.md](references/trends-method.md). Follow it
exactly. It runs entirely in this session and needs no API key; pulling reviews from the Feedspace
MCP is a separate, read-only connection.

## Steps

1. **Get the reviews - with their dates.** Trends need a date on every review.
   - Feedspace MCP: first check whether it is already connected (are Feedspace tools like
     `list_workspaces` available?). If yes, use them. The MCP has **no date filter**, so to build a
     timeline you fetch the reviews and read each one's own date (`reviewed_at`, falling back to
     `created_at`). See [references/mcp-source.md](references/mcp-source.md) for the fetching strategy
     and the import-date caveat. Only if the tools are not available, point the user to setup there.
   - Otherwise read a CSV that has a date column (see [references/csv-format.md](references/csv-format.md))
     or ask the user to paste reviews with dates. Reviews with no date cannot be placed on a timeline.

2. **Snapshot, then choose the period.** Give a 1 to 3 line snapshot: how many dated reviews (and how
   many undated ones were dropped), the date span covered, and whether it is one business or several
   mixed. Pick a bucket size that fits the span (weekly, monthly, or quarterly) and say which. If the
   span is too short or there are too few dated reviews for a reliable trend, say so and offer a plain
   overview instead.

3. **Run the trends** by following [references/trends-method.md](references/trends-method.md): volume
   over time, average rating over time, sentiment mix over time, and theme movements - each with a
   per-period count you can see. Or run just the one the user asked for.

4. **Offer one sensible next step, then stop.** Zoom into a single period or a single theme's
   trajectory, or narrow by review type or rating and re-run. If the reviews came from the Feedspace
   MCP, offer to pull a specific segment over the live connection.

## Guardrails

- Every trend claim must be backed by the actual per-period numbers. Show the small period table so
  the movement is visible, not asserted.
- Do not guess causes. A volume spike from an import batch is visible (many reviews sharing one import
  date) - flag that. A marketing or seasonal cause is not visible in the data - do not claim it.
- Small samples are noise, not trends. If a period has only a handful of reviews, label the movement
  as noise and say so.
- Prefer the review's own date (`reviewed_at`) over its import date (`created_at`), and say which you
  used. Imports can cluster on one date and distort volume - flag it when it happens.
- If the workspace mixes several businesses, cluster the trends or say so. Detect the reviews'
  language and write in it.
- The Feedspace MCP path is read-only. Never modify or delete anything.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Feedspace](https://github.com/Feedspace)
- **Source:** [Feedspace/Feedspace-Cookbook](https://github.com/Feedspace/Feedspace-Cookbook)
- **License:** MIT
- **Homepage:** https://feedspace.io

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-feedspace-feedspace-cookbook-spot-review-trends
- Seller: https://agentstack.voostack.com/s/feedspace
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.