team-weekly-report

team-weekly-report is a skill for Claude Code from opendatahub-io/ai-helpers. It costs 75 tokens per session (1,407 once invoked), scanned A, original, Apache-2.0.

A tool that checks whether upstream bug fixes have already been transferred into a downstream Git branch. It compares commit records and merged pull-request titles to find matches.

In plain words
What is it for?
Use it after filtering backport candidates to update their records with an already-backported status.
Why use it?
It prevents duplicate backport work and marks each candidate clearly as already transferred or still needing attention.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the odh-team plugin — 3 skills shipped together

Good fit Use it after filtering backport candidates to update their records with an already-backported status.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opendatahub-io/ai-helpers/team-weekly-report
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add opendatahub-io/ai-helpers --skill team-weekly-report
Clone the repo
git clone --depth 1 https://github.com/opendatahub-io/ai-helpers

Made for: Claude Code.

Or install odh-team, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for team-weekly-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/team-weekly-report/github.svg)](https://agentmods.dev/skills/opendatahub-io/ai-helpers/team-weekly-report)
Your own site
<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/team-weekly-report"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/team-weekly-report/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for team-weekly-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/team-weekly-report"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/team-weekly-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,407 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.01407
Opus 5 $0.00037 $0.00704
Sonnet 5 $0.00015 $0.00281
Haiku 4.5 $0.00007 $0.00141

Measured 8d ago against content hash d6039f8488fe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

team-weekly-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/fetch_team_github.sh, scripts/fetch_team_jira.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/odh-team/skills/team-weekly-report/SKILL.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Team Weekly Report

Generate a comprehensive weekly status report for an engineering team by combining JIRA issue data and GitHub PR activity.

Prerequisites

  • acli must be installed and authenticated (acli jira auth)
  • gh CLI must be installed and authenticated (gh auth login)
  • jq and yq must be installed and available in PATH
  • A team config YAML file (see Config Format below)

Config Format

Create a YAML file with your team's details:

team:
  name: "My Team"
  jira:
    url: "https://mycompany.atlassian.net"
    project: "PROJ"
    component: "MyComponent"  # optional
  github:
    repositories:
      - "org/repo1"
      - "org/repo2"
  members:
    - name: "Engineer One"
      jira_username: "712020:account-id-here"
      github_username: "eng1"
    - name: "Engineer Two"
      jira_username: "712020:account-id-here"
      github_username: "eng2"
defaults:
  jira_lookback_days: 7
  github_lookback_days: 7
  stale_threshold_days: 7

Finding JIRA account IDs: In Jira Cloud, go to a user's profile page. The account ID is the long string in the URL after /people/.

Implementation

Step 1: Determine Config Path

Parse $ARGUMENTS for the --config flag and optional --days flag.

If no --config is provided, ask the user:

"Which team config file should I use? Provide the path to your YAML config file (e.g., ~/team-config.yaml)."

Validate the config file exists before proceeding.

Step 2: Fetch JIRA Data

Run the JIRA fetch script to collect closed, open, stale, and blocked issues for every team member:

"${CLAUDE_SKILL_DIR}/scripts/fetch_team_jira.sh" --config <CONFIG_PATH> --days <N>

The script outputs JSON to stdout with a members array. Each member entry contains closed_issues, open_issues, stale_issues, and blocked_issues arrays. Capture the full JSON output for analysis.

If the script fails, display the error and stop.

Step 3: Fetch GitHub Data

Run the GitHub fetch script to collect open and merged PRs for every team member across the configured repositories:

Read the full file on GitHub · 201 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 201 lines · 75 tokens per session scan A d6039f8488fe

Subscribe to this mod's changes

team-weekly-report is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 4d ago), licensed Apache-2.0. It adds 75 tokens to every session and 1,407 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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