grooming-report

grooming-report is a skill for Claude Code, Codex from bmbouter/redhat-agents. It costs 27 tokens per session (978 once invoked), scanned A, original, Apache-2.0.

A guide for recording changes made during backlog grooming and producing a Markdown report. Backlog grooming, also called backlog refinement, is the process of reviewing and updating a team's list of planned work.

In plain words
What is it for?
Use it during or after grooming sessions to append actions to an audit log and generate a readable summary for the product owner and team.
Why use it?
It creates a durable record of what changed and when, rather than relying on memory or scattered ticket history. The report makes the session easier to review and audit.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it during or after grooming sessions to append actions to an audit log and generate a readable summary for the product owner and team.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bmbouter/redhat-agents/grooming-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 bmbouter/redhat-agents --skill grooming-report
Clone the repo
git clone --depth 1 https://github.com/bmbouter/redhat-agents

Made for: Claude Code, Codex.

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 grooming-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/bmbouter/redhat-agents/grooming-report/github.svg)](https://agentmods.dev/skills/bmbouter/redhat-agents/grooming-report)
Your own site
<a href="https://agentmods.dev/skills/bmbouter/redhat-agents/grooming-report"><img src="https://agentmods.dev/badge/skills/bmbouter/redhat-agents/grooming-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 grooming-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/bmbouter/redhat-agents/grooming-report"><img src="https://agentmods.dev/badge/skills/bmbouter/redhat-agents/grooming-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 978 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.
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 $0.00027 $0.00978
Opus 5.5 $0.00011 $0.00391
Sonnet 5.5 $0.00005 $0.00196
Haiku 4.5 $0.00003 $0.00098

Measured 1mo ago against content hash 06fa1a0d288c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

grooming-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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (generate-md-report.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.

module/skills/grooming-report/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to Use

During and after a backlog grooming session. Use this alongside grooming-prep and backlog-health-check: those decide what to do, this one keeps a durable record of what was done so sessions are auditable and reviewable.

Why

Grooming touches many tickets across a session. Without a record, there is no way to answer "what changed last Tuesday?", to review automated actions after the fact, or to hand a summary to the team. This skill maintains a machine-readable audit trail and turns it into a report the PO and team can read.

Where the Files Live

Keep the audit trail in the gitignored local/ directory so it stays with the user's workflow config and out of version control:

  • local/grooming_log.jsonl — append-only audit trail (one JSON object per line)
  • local/grooming_report.md — generated report (do not edit by hand)

Instructions

Read local/jira-workflow.md first to understand the project's conventions (issue types, hierarchy, required fields, status names).

1. Mark the start of the session

Before making any changes, append a session marker to local/grooming_log.jsonl:

{"session_start": "YYYY-MM-DD", "groomer": "Name", "total_issues": N, "analyzed": M, "note": "what this session focused on"}
  • total_issues — how many issues matched the grooming query
  • analyzed — how many you actually reviewed this session

2. Log every action as you go

Append one line per action. Use a small, consistent set of action values so the report stays scannable. Common actions:

{"issue": "KEY-123", "action": "updated", "changes": ["added_label_X", "assigned_to_parent_KEY-100"], "notes": "context", "timestamp": "ISO8601"}
{"issue": "KEY-456", "action": "postponed_for_team_review", "reason": "needs_team_input_on_priority", "timestamp": "ISO8601"}
{"action": "created_epic", "issue": "KEY-789", "summary": "Epic title", "parent": "PARENT-KEY", "timestamp": "ISO8601"}
{"action": "created_feature", "issue": "KEY-790", "summary": "Feature title", "parent": "PARENT-KEY", "timestamp": "ISO8601"}

Read the full file on GitHub · 96 lines

Files

What ships with it

1 file 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. 1mo ago First seen · 96 lines · 27 tokens per session scan A 06fa1a0d288c

Subscribe to this mod's changes

grooming-report is a skill published in the GitHub repository bmbouter/redhat-agents (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 978 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.