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 Gerg/ai_agent_skills --skill agent-issue-trackinggit clone --depth 1 https://github.com/Gerg/ai_agent_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/gerg/ai_agent_skills/agent-issue-tracking)<a href="https://agentmods.dev/skills/gerg/ai_agent_skills/agent-issue-tracking"><img src="https://agentmods.dev/badge/skills/gerg/ai_agent_skills/agent-issue-tracking/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/gerg/ai_agent_skills/agent-issue-tracking"><img src="https://agentmods.dev/badge/skills/gerg/ai_agent_skills/agent-issue-tracking.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 | $0.00054 | $0.02196 |
| Opus 5.5 | $0.00022 | $0.00878 |
| Sonnet 5.5 | $0.00011 | $0.00439 |
| Haiku 4.5 | $0.00005 | $0.00220 |
Grade A, and why
agent-issue-tracking 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 2mo 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Issue Tracking
Track issues, findings, and tasks using lightweight, agent-friendly issue tracking tools for coordination and local work management.
When using this skill, begin by stating: "I'm using the agent-issue-tracking skill to track work with [tool name]."
Using This Skill
This skill provides universal principles for agent-based issue tracking. For tool-specific commands, see:
Tool-specific references:
- tk: See references/tk.md for tk utility commands and syntax
Default to using tk, if no other tool is specified.
Important: Use only ONE tracking tool per session/project. If tk is being used, ignore other tracking systems (like Cursor's built-in TODOs, GitHub Issues for local work, etc.). Mixing tools creates confusion and duplicate tracking overhead.
Core Concepts
Purpose
Agent-based issue tracking serves different needs than human-oriented systems (Jira, GitHub Issues):
- AI agent coordination: Track work across multiple agent sessions
- Local work management: Organize tasks without external dependencies
- Review findings: Systematically track code review issues
- Work postponement: Defer work to later sessions
- Progress visibility: Show what's done, in progress, or blocked
Key Differences from Human Issue Trackers
| Aspect | Human Trackers (Jira, GitHub) | Agent Trackers (tk, beans, beads) |
|---|---|---|
| Audience | Team members, stakeholders | AI agents, local coordination |
| Scope | Project-wide, long-lived | Session-scoped, ephemeral |
| Overhead | Rich UI, workflows, notifications | Minimal CLI, fast operations |
| Integration | CI/CD, project management | Local filesystem, version control |
| Persistence | Database, cloud | Local files, git-tracked |
Ticket Structure
Essential Fields
- ID: Unique identifier (auto-generated)
- Title: Brief, specific description
- Type: bug, feature, task, epic, chore
- Priority: P1 (critical) through P4 (low)
- Status: open, in_progress, closed
- Description: Detailed context and requirements
What ships with it
1 file 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.
- 2mo ago First seen · 337 lines · 54 tokens per session scan A 70bc9d94c961
agent-issue-tracking is a skill published in the GitHub repository Gerg/ai_agent_skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 2,196 once invoked, about $0.0002 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 2026-08-31.
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