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.
npx agentmods add skills/mpaarating/ai-workflow-kit/checkinnpx skills add mpaarating/ai-workflow-kit --skill checkingit clone --depth 1 https://github.com/mpaarating/ai-workflow-kitWhat 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 | $0.00023 | $0.00834 |
| Opus 5 | $0.00012 | $0.00417 |
| Sonnet 5 | $0.00005 | $0.00167 |
| Haiku 4.5 | $0.00002 | $0.00083 |
Grade A, and why
checkin 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 2d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Midday Check-in
Trigger Phrases
- "checkin"
- "midday checkin"
- "midday check-in"
- "afternoon checkin"
- "how's my day going"
Workflow
Step 1: Read Today's Daily Page
Fetch today's daily page from {{notes}}.
- If no daily page exists, tell the user and offer to run morning-kickoff first.
- Extract the Focus Areas section (the morning plan).
- Read any Working Notes added during the morning.
Step 2: Assess Progress on Focus Areas
For each item in the morning Focus Areas, determine status:
- Done: Completed since the morning.
- In Progress: Actively being worked on.
- Not Started: Hasn't been touched yet.
Present as a checklist so the user can quickly confirm or correct.
Step 3: Detect Pivots
Compare the morning plan to the Working Notes content and ask the user what they've actually been doing.
If work doesn't align with morning priorities, flag it neutrally:
"Looks like you spent the morning on [X] instead of [planned item]. Intentional pivot or got pulled in?"
Pivots aren't bad — they just need to be acknowledged so the afternoon can be re-planned.
Step 4: Show Remaining Schedule
Query {{calendar}} for events in the remainder of today.
- List upcoming meetings with times.
- Calculate remaining deep work hours: time left in the workday minus remaining meeting time.
If {{calendar}} is not configured, ask the user how many meetings they have left.
Step 5: Collect Reflection
Ask the user for a brief midday reflection. Prompt with one of these:
- "How's your energy? Anything you want to adjust for the afternoon?"
- "What's the one thing you want to make sure gets done before EOD?"
- "Anything blocking you right now?"
Keep it lightweight — one or two sentences is fine.
Step 6: Update the Daily Page
Add a timestamped midday note to the Working Notes section of today's page in {{notes}}.
Format:
### Midday Check-in ([time])
**Progress:**
- [x] [Focus item 1] — done
- [ ] [Focus item 2] — in progress
- [ ] [Focus item 3] — not started
**Pivot:** [description, if any]
**Afternoon plan:** [adjusted priorities based on remaining time]
**Note:** [user's reflection]
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.
- 2d ago First seen · 117 lines · 23 tokens per session scan A de6091846596
checkin is a skill published in the GitHub repository mpaarating/ai-workflow-kit (2 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 834 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 2026-08-31.
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