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 itseffi/agentic-os --skill issue-syncgit clone --depth 1 https://github.com/itseffi/agentic-osWrote 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/itseffi/agentic-os/issue-sync)<a href="https://agentmods.dev/skills/itseffi/agentic-os/issue-sync"><img src="https://agentmods.dev/badge/skills/itseffi/agentic-os/issue-sync/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/itseffi/agentic-os/issue-sync"><img src="https://agentmods.dev/badge/skills/itseffi/agentic-os/issue-sync.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 | $0.00024 | $0.00399 |
| Opus 5.5 | $0.00010 | $0.00160 |
| Sonnet 5.5 | $0.00005 | $0.00080 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
linear-issue-sync 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.
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.
What it actually says
Linear Issue Sync
Check Linear for assigned issues and sync with local task management.
Instructions
Step 1: Fetch Assigned Issues
Call linear_list_issues filtered to:
- Assigned to current user
- Status not "Done" or "Canceled"
Step 2: Compare with Local Tasks
Check Tasks/ for existing files with Linear references:
- Look for
linear_idin YAML frontmatter - Identify new issues not yet in Tasks/
Step 3: Present Summary
Linear Issues (5 active):
**High Priority**
- LIN-123: Fix authentication timeout [In Progress]
- LIN-124: Update API documentation [Todo]
**Normal Priority**
- LIN-125: Refactor user service [Backlog]
2 issues not yet in local Tasks. Create them?
Step 4: Sync Options
| Option | Description |
|---|---|
| Create all | Add all new issues as local tasks |
| Select specific | Choose which to sync |
| Skip | Continue without syncing |
Step 5: Create Local Tasks
For each issue to sync, create task file:
---
title: [Issue title]
category: technical
priority: [Map from Linear priority]
status: n
linear_id: LIN-XXX
---
Example Flow
User: "What should I work on today?"
Agent:
- Fetches Linear issues
- Compares with local tasks
- "You have 3 new Linear issues..."
- Offers to create local tasks
- Continues with planning
Notes
- Map Linear priorities to P0-P3
- Keep
linear_idin frontmatter for bidirectional sync - Update Linear status when local task completes
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.
- 1mo ago First seen · 77 lines · 24 tokens per session scan A da35d261f2fc
linear-issue-sync is a skill published in the GitHub repository itseffi/agentic-os (117 stars, last pushed 14d ago), licensed MIT. It adds 24 tokens to every session and 399 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 2026-08-30.
Other skills, from other repositories
reviewcourt
A review tool for completed Tencent Meeting requirements or technical-plan meetings. It turns the meeting notes and transcript into a verdict, such as approved, conditionally approved, rejected, or lacking enough information.
pm-requirement-review-simulator
A rehearsal for reviewing a product requirements document, or PRD—a written description of what a product or feature should do. Five cross-functional roles challenge the requirements before the real meeting.
parallel-feature-development
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system…
bazel-build-optimization
Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
track-management
Use this skill when creating, managing, or working with Conductor tracks - the logical work units for features, bugs, and refactors. Applies to spec.md, plan.md, and track lifecycle operations.
mission-control
Interact with Mission Control — AI agent orchestration dashboard. Use when registering agents, managing tasks, syncing skills, or querying agent/task status via MC APIs.