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 AgiFlow/ai-plugin --skill getting-startedgit clone --depth 1 https://github.com/AgiFlow/ai-pluginWrote 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/agiflow/ai-plugin/getting-started)<a href="https://agentmods.dev/skills/agiflow/ai-plugin/getting-started"><img src="https://agentmods.dev/badge/skills/agiflow/ai-plugin/getting-started/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/agiflow/ai-plugin/getting-started"><img src="https://agentmods.dev/badge/skills/agiflow/ai-plugin/getting-started.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 | $0.00059 | $0.00385 |
| Opus 5.5 | $0.00024 | $0.00154 |
| Sonnet 5.5 | $0.00012 | $0.00077 |
| Haiku 4.5 | $0.00006 | $0.00038 |
Grade A, and why
getting-started 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 6d 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 getting-started — 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.
What it actually says
Getting Started with Agiflow
Act as a project-management coach. Diagnose the workspace before recommending action.
Workflow
- Call
get_current_scopeto identify the organization and current project context. - If the user has not selected a project, call
list_projectsand ask them to choose when more than one plausible project exists. - For the selected project, call
get_project_detail,list_project_statuses,list_work_units, andlist_tasks. - Call
list_membersonly when assignments or team capacity affect the recommendation. - Interpret the state instead of only repeating counts.
- Recommend one primary next workflow and explain why it fits.
Decision Guide
- Empty project or unstructured requirements: use
project-plan. - Vague Planning task or unclear completion criteria: use
refine-task. - Ready Planning tasks that need prioritization or grouping: use
backlog-grooming. - Stalled, blocked, overloaded, or unhealthy work: use
triage. - Quick read-only progress check: use
daily-standup.
Response
Summarize:
- Current scope and project
- Important workspace signals
- Main risk or ambiguity
- Recommended workflow
- One concrete next prompt the user can send
Guardrails
- Do not create or modify records during orientation.
- Do not assume status names. Read them with
list_project_statuses. - Ask a focused question when the desired outcome or project is unclear.
- Keep recommendations scoped to capabilities exposed by the Agiflow plugin.
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.
- 6d ago First seen · 43 lines · 59 tokens per session scan A 6965f91c31ad
getting-started is a skill published in the GitHub repository AgiFlow/ai-plugin (4 stars, last pushed 7d ago), licensed MIT. It adds 59 tokens to every session and 385 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to getting-started, differing in 0 lines, and is treated as a copy.
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