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 agents/aigengame/cli-agentic-workflow/issue-trackergit clone --depth 1 https://github.com/aigengame/cli-agentic-workflowWhat 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 | $0.00000 | $0.00283 |
| Opus 5 | $0.00000 | $0.00142 |
| Sonnet 5 | $0.00000 | $0.00057 |
| Haiku 4.5 | $0.00000 | $0.00028 |
Grade A, and why
issue-tracker 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.
This is a copy
83% identical to issue-tracker — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Issue tracker: GitHub
Issues and PRDs for this repo live as GitHub issues. Use the gh CLI for all operations.
Conventions
- Create an issue:
gh issue create --title "..." --body "...". Use a heredoc for multi-line bodies. - Read an issue:
gh issue view <number> --comments, filtering comments byjqand also fetching labels. - List issues:
gh issue list --state open --json number,title,body,labels,comments --jq '[.[] | {number, title, body, labels: [.labels[].name], comments: [.comments[].body]}]'with appropriate--labeland--statefilters. - Comment on an issue:
gh issue comment <number> --body "..." - Apply / remove labels:
gh issue edit <number> --add-label "..."/--remove-label "..." - Close:
gh issue close <number> --comment "..."
Infer the repo from git remote -v — gh does this automatically when run inside a clone.
When a skill says "publish to the issue tracker"
Create a GitHub issue.
When a skill says "fetch the relevant ticket"
Run gh issue view <number> --comments.
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 · 23 lines · 0 tokens per session scan A f0e138631d1f
issue-tracker is an agent published in the GitHub repository aigengame/cli-agentic-workflow (20 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 283 tokens. A static security scan graded it A with 0 findings. It is 83% identical to issue-tracker, differing in 4 lines, and is treated as a copy.
Other agents, from other repositories
ap-juror
L4 terminal leaf - G7 SIGN-OFF. One independent sign-off panel seat that saw none of the intermediate work. Binary PASS/FAIL on opened evidence; default-FAIL. A FAIL naming a P0/P1 blocker is NOT arbitrable into PASS.
ap-verifier
L3 independent G6 verifier - proves behavior with real before/after runs, regression checks, adversarial inputs, and >=95% changed-line coverage.
ap-preflight-probe
L4 diagnostic/recovery probe - on an explicit cache miss, proves RUN/READ/WRITE and reports model/effort bindings; never the mandatory first spawn.
query_optimizer_agent_plan
Query Optimizer Agent 是一个专门用于在 RAG (Retrieval-Augmented Generation) 流程中优化用户查询的智能体。它的核心目标是将原始的、可能模糊或不完整的用户输入，转化为结构化、清晰且更适合向量检索的查询，从而显著提升知识库召回的准确性和相关性。.
designer
Visual designer, UX/UI agent, and Open Design handoff producer.
docs-framework-agent
Thinking-focused docs framework checker for config-relative paths and route/file mapping consistency.