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 richardcb/oh-my-gemini --skill track-creationgit clone --depth 1 https://github.com/richardcb/oh-my-geminiWrote 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/richardcb/oh-my-gemini/track-creation)<a href="https://agentmods.dev/skills/richardcb/oh-my-gemini/track-creation"><img src="https://agentmods.dev/badge/skills/richardcb/oh-my-gemini/track-creation/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/richardcb/oh-my-gemini/track-creation"><img src="https://agentmods.dev/badge/skills/richardcb/oh-my-gemini/track-creation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00048 | $0.00681 |
| Opus 5 | $0.00024 | $0.00341 |
| Sonnet 5 | $0.00010 | $0.00136 |
| Haiku 4.5 | $0.00005 | $0.00068 |
Grade A, and why
track-creation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Track Creation Skill
Goal
Create complete Conductor tracks with properly structured spec, plan, and metadata files.
Activation Triggers
- User runs
/omg:trackwith a feature name - User asks to "start a new track", "create a feature track", or "plan a feature"
- User wants to begin a new Conductor workflow for a feature
Bundled Resources
This skill includes templates that the agent can read and use:
templates/spec.md- Track specification templatetemplates/plan.md- Implementation plan templatetemplates/metadata.json- Track metadata template
Process
1. Generate Track ID
Create a unique track ID:
FEATURE_SNAKE=$(echo "{{FEATURE_NAME}}" | tr '[:upper:]' '[:lower:]' | tr ' ' '_' | tr -cd '[:alnum:]_')
DATE=$(date +%Y%m%d)
TRACK_ID="${FEATURE_SNAKE}_${DATE}"
echo $TRACK_ID
2. Create Track Directory
mkdir -p conductor/tracks/${TRACK_ID}
3. Read and Customize Templates
Read each template from this skill's directory, replace placeholders, and write to the track directory.
Placeholders to replace:
{{FEATURE_NAME}}- User-provided feature name{{TRACK_ID}}- Generated track ID{{DATE}}- Current date (YYYY-MM-DD){{ISO_TIMESTAMP}}- Current ISO timestamp
4. Gather Requirements
Before writing the spec, ask clarifying questions:
- What problem does this solve?
- Who is the primary user?
- What are the must-have requirements?
- What's explicitly out of scope?
5. Write Files
Create three files in conductor/tracks/${TRACK_ID}/:
spec.md- Filled with user's requirementsplan.md- Phased implementation tasksmetadata.json- Track state tracking
6. Update tracks.md
Add entry to conductor/tracks.md:
## [ ] Track: {{FEATURE_NAME}}
*ID: {{TRACK_ID}}*
*Link: [./tracks/{{TRACK_ID}}/]*
*Status: New*
*Created: {{DATE}}*
7. Verify Creation
ls -la conductor/tracks/${TRACK_ID}/
cat conductor/tracks/${TRACK_ID}/metadata.json
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.
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.
- 10d ago First seen · 104 lines · 48 tokens per session scan A c0d2471f5d46
track-creation is a skill published in the GitHub repository richardcb/oh-my-gemini (16 stars, last pushed 6mo ago), licensed MIT. It adds 48 tokens to every session and 681 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
multica-goal-tracker
Track goal-driven Multica issues. Use when a user creates or maintains Multica issues by pasting a /goal prompt, wants Codex to summarize that goal into a concise issue purpose, append a normalized goal-start comment, record completion evidence from real Multica execution run messages or a supplied session transcript…
status
Show a comprehensive project status dashboard: task queue, blocked items, session state, verification, and git status.
jira-integration
Use this skill when retrieving Jira tickets, analyzing requirements, updating ticket status, adding comments, or transitioning issues. Provides Jira API patterns via MCP or direct REST calls.
project-flow-ops
Operate execution flow across GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub public-facing while Linear remains the internal execution layer. Use when the user wants backlog control, PR triage, or GitHub-to-Linear coordination.
product-lens
Product thinking validation before building features.
speckit-converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.