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 skills/agiflow/ai-plugin/run-tasknpx skills add AgiFlow/ai-plugin --skill run-taskgit clone --depth 1 https://github.com/AgiFlow/ai-pluginWhat 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 | $0.00056 | $0.02162 |
| Opus 5 | $0.00028 | $0.01081 |
| Sonnet 5 | $0.00011 | $0.00432 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
run-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.
This is a copy
100% identical to run-task — 0 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Invoked as
/agiflow:run-task. In hosts without slash-prompts, this skill is triggered by matching intent and drives AgiFlow via its MCP tools.
Usage:
/agiflow:run-task <task-slug-or-id>- Execute specific task/agiflow:run-task- List and select from available tasks
Examples:
/agiflow:run-task DXX-2(using slug)/agiflow:run-task 01K8FABMNEJG1XTA9JGHSNFV40(using ID)/agiflow:run-task(interactive selection)
Guardrails
- Favor straightforward, minimal implementations first and add complexity only when it is requested or clearly required.
- Keep changes tightly scoped to the requested outcome within the task scope.
- A task represents a single, focused unit of work that can be completed in one session.
If a task slug/id is provided, load it with get_task; otherwise list available tasks with list_tasks for selection.
AgiFlow Project Management Guidelines
Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and transitions, work-unit best practices, and the tags strategy apply to this workflow.
Task Status Workflow
Tasks move through these statuses in order:
Planning → Todo → In Progress → Testing → Review → Done
Exception paths: Blocked (requires human intervention), Cancelled (terminal).
IMPORTANT: Planning Status Guard
This skill ONLY executes tasks in "Todo" or later status. Tasks in "Planning" have NOT been groomed and are NOT ready for execution. Use backlog-grooming to promote Planning tasks to Todo first.
Steps Track these steps as TODOs and complete them one by one.
1. Task Selection & Loading
If task slug/id NOT provided:
- Use
list_tasksMCP tool to show available tasks:- For the ready queue, filter by
status: "Todo"(sorted by priority automatically) - Do NOT pick up tasks in "Planning" status — they have not been groomed yet
- Display: slug, title, priority, assignee, acceptance criteria count
- For the ready queue, filter by
- Ask user to select which task to work on.
- Once user selects, proceed with the selected task slug/id.
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 · 230 lines · 56 tokens per session scan A 8307409e41d2
run-task is a skill published in the GitHub repository AgiFlow/ai-plugin (2 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 2,162 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to run-task, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
run-task
Execute a single Todo task through In Progress to Review, meeting every acceptance criterion with tests and vibe-lint checks. Refuses Planning-status tasks. Invoked as /agiflow:run-task . Uses gettask, updatetask, createtaskcomment.
run-work
Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress. Use to deliver a complete feature in one session. Invoked as /agiflow:run-work . Uses getworkunit, listtasks, updatetask, getworkunitprogress.
trulens-notebook-execution
Execute and display Jupyter notebooks for TruLens demos and quickstarts.
dispatch
Use when a task file exists in .hyperflow/tasks/ and workers need dispatching. Fans out parallel workers under per-batch Reviewers, runs a final integration review, and commits per sub-task. Endpoint of the auto-chain — no auto-deploy. Trigger with /hyperflow:dispatch, "run the plan", "execute the task", "build it"…
review-work
Quality gate: verify each acceptance criterion of a completed task/work unit, run quality checks, and create follow-up tasks for gaps. Use before merging or to audit delivered work. Invoked as /agiflow:review-work . Uses getworkunit, gettask, updatetask, createtask, createtaskcomment.
state-trees
Create, inspect, and edit StateTree assets — states, tasks, transitions, conditions, considerations, and property bindings for AI behavior and game logic (StateTreeService). Use when the user asks to build a StateTree, add states/tasks/transitions, bind task properties, set up Utility AI considerations, or wire…