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weekly-metrics-report

Create weekly reports from Postgres metrics, comparing current figures with recent weeks. Add plain-language explanations for notable changes, flag missing data, and post one report to Slack while keeping database access read-only.

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Weekly metrics reporting loop. Queries the metrics tables in Postgres read-only, compares this week against recent weeks, writes plain-language commentary on what moved and why, and posts one report to {{report_channel}}.

Works withSlackPostgreSQL
See how to install

Good for

  • Preparing a weekly metrics report for Slack
  • Reviewing weekly changes and recent trends
  • Explaining notable changes and flagging data gaps

Files included (1)

  • SKILL.md4.6 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

<skill name="weekly-metrics-report"> <overview> Build the weekly metrics report without a person spending their Monday on it. A weekly cron spawns a fresh session with read-only access to the Postgres database and permission to post to one Slack channel. This skill turns raw metric rows into a report: the queries to run, the comparison window, what counts as a notable move, and the layout to post. Every run recomputes from scratch — there is no report state carried over from the prior week. </overview> <when-to-load> - The weekly cron fires the report run. - A human asks for the metrics report on demand, or asks why a specific number moved. - The set of tracked metrics or their definitions changes. </when-to-load> <workflow>

Step 1 — Confirm the metric definitions

Metric definitions, the source tables/columns, and what counts as a notable move live in project memory (memory/weekly-report.md if present) or this skill's defaults below. Treat that as the source of truth for exactly which metrics to report — no more, no less. If a definition is missing or ambiguous, query the obvious candidate table and note the assumption in the report rather than guessing silently.

Step 2 — Query this week's numbers (read-only)

Run each metric's query against the read-only role, scoped to the metrics tables:

-- This week's window: Monday 00:00 through now
SELECT metric_name, SUM(value) AS value
FROM metrics
WHERE recorded_at >= date_trunc('week', now())
GROUP BY metric_name;

Adapt the table/column names to what the schema actually exposes (e.g. events, subscriptions, invoices) — the shape above is illustrative, not literal. The connection is read-only: SELECT only, nothing else is reachable through this role.

Step 3 — Query the prior weeks for comparison

Pull the same metrics for a trailing window (default: the prior 4 weeks) so a single-week blip can be told apart from a trend:

SELECT date_trunc('week', recorded_at) AS week, metric_name, SUM(value) AS value
FROM metrics
WHERE recorded_at >= date_trunc('week', now()) - interval '4 weeks'
  AND recorded_at < date_trunc('week', now())
GROUP BY 1, 2
ORDER BY 1;

Step 4 — Compute the deltas

For each metric, compute week-over-week change and the trend against the trailing average. Flag as notable:

SignalCriteria
Notable move≥15% change week-over-week, or a break from a 3+ week trend
SteadyWithin normal week-to-week noise for that metric
Missing dataThe query returned nothing for the current or a prior week — report the gap, don't fill it with a guess

Step 5 — Write the commentary

For every notable move, write one or two plain-language sentences: what changed, the likely driver if it's inferable from the data (a launch, a known outage, a seasonal pattern), and whether it's worth the team's attention. Steady metrics get the number with no commentary — don't manufacture a narrative for noise.

Step 6 — Assemble and post the report

One message to {{report_channel}} per run, in this shape:

  1. Header — the week's date range.
  2. The numbers — every tracked metric with its value and week-over-week delta.
  3. Commentary — the notable moves, each with its one-line read.
  4. A closing note if any metric had missing or suspect data.

Post exactly once. This is a fresh session with nothing to diff against directly — the deltas come from the Step 3 query, not from any file state — so there is nothing else to update before finishing.

</workflow> <guardrails> - **Read-only, always.** The Postgres role can `SELECT` and nothing else — no insert, update, or delete — and it's scoped to the metrics tables. The report can never change the data it reports on. - **One output.** The Slack post to {{report_channel}} is the only thing that leaves the sandbox. No writes back to Postgres, no other messages. - **No memory between runs.** Each run is a fresh session; recompute this week's numbers and the trailing comparison from the current database state rather than assuming anything from a prior report. - **Scoped secrets.** Postgres and Slack access are brokered server-side through connectors; no raw credential is ever pasted into chat. - **Report, don't act.** Notable moves get called out with plain-language commentary; deciding what to do about them belongs to the team reading the report, not the agent. </guardrails> </skill>

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