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 skills add glebis/claude-skills --skill trail-checkingit clone --depth 1 https://github.com/glebis/claude-skillsWrote 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/skills/glebis/claude-skills/trail-checkin)<a href="https://agentmods.dev/skills/glebis/claude-skills/trail-checkin"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/trail-checkin/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.
<a href="https://agentmods.dev/skills/glebis/claude-skills/trail-checkin"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/trail-checkin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.00805 |
| Opus 5 | $0.00044 | $0.00402 |
| Sonnet 5 | $0.00018 | $0.00161 |
| Haiku 4.5 | $0.00009 | $0.00081 |
Grade A, and why
trail-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 9d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Base directory for this skill: ~/.Codex/skills/trail-checkin
Trail Check-in Skill
Interactive trail review and update process. Lists available trails, lets you select which to check in with, then walks through structured questions for each trail to capture progress, update markers, and reflect on direction.
Prerequisites
- Obsidian vault at
~/Brains/brain - Trails located in
~/Brains/brain/Trails/ - Trail files follow naming pattern
Trail - *.md
Usage
Run the skill to start an interactive check-in:
/trail-checkin
Or invoke directly:
python3 ~/.Codex/skills/trail-checkin/scripts/trail_checkin.py
How It Works
Step 1: List Trails
Script scans Trails/ folder and extracts:
- Trail name
- Status (active/paused/completed)
- Last updated date
- Objective (first line summary)
Returns JSON with trail list.
Step 2: Select Trails
Codex uses AskUserQuestion with multiSelect to let you choose which trails to check in with.
Step 3: Check-in Questions (per trail)
For each selected trail, Codex asks:
- Progress made - What happened since last check-in?
- Markers to add - Any new milestones reached?
- Tasks completed - Which tasks can be marked done?
- New tasks - What needs to be added?
- Metrics update - Any numbers to update?
- Open questions - New questions or resolved ones?
- Status change - Still active? Paused? Completed?
- Next review date - When to check in again?
Step 4: Update Trails
Codex updates each trail file with:
- New progress markers
- Updated metrics
- Task status changes
- New open questions
- Updated
last_updateddate - Next review date
Output
Returns summary of updates made to each trail.
Example Session
User: /trail-checkin
Codex: Found 5 trails. Which would you like to check in with?
[multiSelect: Mental Health Tech, Codex Lab, Telegram Agent, Salience, Voice Codex]
User: [selects Mental Health Tech, Voice Codex]
Codex: Let's check in with Trail: Mental Health Tech
What progress have you made since last update (2026-01-19)?
[short answer input]
User: Published Vastaamo hack post, drafted privacy ethics analysis
Codex: Should we add any progress markers?
[yes/no]
[continues through questions...]
Codex: Updated Trail: Mental Health Tech
- Added marker: Vastaamo hack post published
- Updated posts metric: 78
- Marked task complete: Publish privacy post
- Updated last_updated: 2026-01-19
Now checking in with Trail: Voice Codex...
What ships with it
2 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.
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.
- 9d ago First seen · 125 lines · 88 tokens per session scan A 49df400cd96a
trail-checkin is a skill published in the GitHub repository glebis/claude-skills (375 stars, last pushed 10d ago), licensed MIT. It adds 88 tokens to every session and 805 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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