harvest_skill

This skill automates PR data collection and report generation from GitHub, delivering weekly and monthly summaries and release notes for stakeholders.
  • Shell

8

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill simota/agent-skills --skill harvest

  • SKILL.md8.2 KB

Overview

This skill harvests GitHub pull request data and turns it into clear reports: weekly/monthly summaries, release notes, client PDFs, and individual work reports. It uses the gh CLI to collect PR metadata, aggregates statistics, and formats outputs for stakeholders. Reports prioritize data quality, context, and reader-focused formatting.

How this skill works

The skill runs gh pr list with configurable filters (state, author, label, date range) to collect PR JSON, then applies incremental caching and jq-style filtering to minimize API load. Collected data is analyzed for metrics like additions/deletions, merge rate, review time, and cycle time. Final outputs are generated in Markdown, JSON, HTML, or PDF, with optional charts and member-level breakdowns.

When to use it

  • Generate a weekly or monthly team PR summary for managers.
  • Create release notes or a changelog for an upcoming deployment.
  • Produce individual contribution reports for performance reviews or billing.
  • Analyze PR quality trends and review time regressions.
  • Export client-facing reports or PDFs with charts and work-hour estimates.

Best practices

  • Confirm repository and filters before running large queries; ask for scope when >100 PRs.
  • Choose output format early (Markdown/HTML/PDF/JSON) to shape analysis and visuals.
  • Keep sensitive fields out of reports; redact or aggregate personal data.
  • Use caching and incremental collection for repeated runs to avoid rate limits.
  • Validate gh CLI auth and network connectivity; implement exponential backoff on errors.

Example use cases

  • Weekly merged-PR summary with totals, top contributors, and cycle-time trends.
  • Release notes generator that converts PR titles and descriptions into a changelog draft.
  • Client report: HTML/PDF with charts, PR table, and estimated work hours per ticket.
  • Individual work report listing a user’s PRs, time estimates, and review feedback.
  • Quality trends report integrating Judge feedback to highlight recurring issues.

FAQ

Specify repository, date range (7/30/custom), and any filters (author/label/state). Confirm output format and destination.

How are work hours estimated?

Base estimate = (additions+deletions)/100 with file-weight and complexity modifiers; an LLM-assisted adjustment refines per-PR estimates and enforces a minimum of 0.5h.

How do you handle large datasets or rate limits?

The skill uses a caching layer, incremental collection, and exponential backoff retries. It will prompt for confirmation before fetching >100 PRs.

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