Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/openshift-eng/ai-helpersnpx agentmods add commands/openshift-eng/ai-helpers/catch-me-upWrote 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.
[](https://agentmods.dev/commands/openshift-eng/ai-helpers/catch-me-up)<a href="https://agentmods.dev/commands/openshift-eng/ai-helpers/catch-me-up"><img src="https://agentmods.dev/badge/commands/openshift-eng/ai-helpers/catch-me-up.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.01752 |
| Opus 5 | $0.00007 | $0.00876 |
| Sonnet 5 | $0.00003 | $0.00350 |
| Haiku 4.5 | $0.00001 | $0.00175 |
Grade A, and why
catch-me-up 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 3d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Name
jira:catch-me-up
Synopsis
/jira:catch-me-up [14] [--days 7] [--no-cache]
Description
Fetches recent activity on Jira issues where you are assignee or watcher, then classifies each event into three tiers: needs attention, unsure, or noise. Uses a map/reduce approach — fast model classifies batches in parallel, then a review pass catches cross-event patterns.
Prerequisites
JIRA_API_TOKENandJIRA_USERNAMEenvironment variables setuv(astral.sh/uv) — the gather script is run viauv run --with aiohttpJIRA_URLdefaults tohttps://redhat.atlassian.net
Implementation
Step 1: Parse arguments
Default --days to 7 if not specified. The user may pass a number directly (e.g., /jira:catch-me-up 14 means 14 days).
Step 2: Check subagent permissions
Read .claude/settings.local.json. If the file exists, check whether Read(.work/catch-me-up/**) is in the permissions.allow array.
If present, continue silently.
If missing (or the file doesn't exist), append Read(.work/catch-me-up/**) to the permissions.allow array. Preserve all existing content — only add this one entry. Tell the user:
Added
Read(.work/catch-me-up/**)to.claude/settings.local.json— subagents need this to read batch files.
Step 3: Gather data
Run the data gathering script. Use uv run to handle the aiohttp dependency automatically.
uv run --with aiohttp plugins/jira/skills/catch-me-up/scripts/gather.py --days <N> -v --output-dir .work/catch-me-up/runs
If the user passed --no-cache, append --no-cache to the command above.
Check the output stats. If there are 0 events, tell the user and stop. Read the output file path from stderr.
Step 4: Split into batches
python3 plugins/jira/skills/catch-me-up/scripts/split_batches.py .work/catch-me-up/runs/<date>-<days>d/events.json 5
This creates batch files and prints a JSON manifest with batch_files paths.
Step 5: Classify batches in parallel
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.
- 3d ago First seen · 172 lines · 14 tokens per session scan A 53db8c335a14
catch-me-up is a command published in the GitHub repository openshift-eng/ai-helpers (116 stars, last pushed 2d ago), licensed Apache-2.0. It adds 14 tokens to every session and 1,752 once invoked, about $0.0001 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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