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 hoangsonww/AI-Agents-Orchestrator --skill resume-taskgit clone --depth 1 https://github.com/hoangsonww/AI-Agents-OrchestratorWrote 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/hoangsonww/ai-agents-orchestrator/resume-task)<a href="https://agentmods.dev/skills/hoangsonww/ai-agents-orchestrator/resume-task"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/resume-task/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/hoangsonww/ai-agents-orchestrator/resume-task"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/resume-task.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 | $0.00032 | $0.00218 |
| Opus 5.5 | $0.00013 | $0.00087 |
| Sonnet 5 | $0.00006 | $0.00044 |
| Haiku 4.5 | $0.00003 | $0.00022 |
Grade A, and why
resume-task 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.
What it actually says
Resume Task
Use ai_collaboration.get_context for the current repository. If no active task exists, explain that clearly and offer to start one; do not infer a task from unrelated history.
Before editing:
- Compare the returned Git branch, head, and changed files with the latest captured events.
- Read the most recent checkpoint and failed test, if present.
- Inspect the actual diff and relevant files; captured history is evidence, not a substitute for current repository state.
- State the task, previous provider, important files, last test result, and intended next action in a compact update.
Search with ai_collaboration.search_history only when the initial context does not answer a specific question. Continue within the user's existing authorization and repository instructions.
If MCP is unavailable, run bin/ai-collaboration context --cwd <repository> from the plugin directory.
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.
- 2d ago First seen · 20 lines · 32 tokens per session scan A 22a22ce2983d
resume-task is a skill published in the GitHub repository hoangsonww/AI-Agents-Orchestrator (84 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 218 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 2026-09-21.
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Review a GitHub pull request with evidence-backed, multi-angle analysis and false-positive filtering. Use when the user asks to review, inspect, or check a pull request by number or URL. Not for local uncommitted changes.
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Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.
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