verb-domain-task

verb-domain-task is a skill for Claude Code, Codex from aAAaqwq/AGI-Super-Team. It costs 44 tokens per session (223 once invoked), scanned A, original, MIT.

A template for documenting a domain-specific task workflow, including boundaries, deliverables, validation, and references. The supplied text still contains placeholders rather than a real task definition.

In plain words
What is it for?
Use it as a starting point for writing a task skill once the workflow steps, constraints, outputs, and validation rules are filled in.
Why use it?
It provides a structure for describing how an agent should work, but it does not contain enough detail to explain a particular domain or capability.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the agi-super-team plugin — 193 skills, 1 agent shipped together

Good fit Use it as a starting point for writing a task skill once the workflow steps, constraints, outputs, and validation rules are filled in.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aaaaqwq/agi-super-team/starter-kit
Install

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.

Any agent
npx skills add aAAaqwq/AGI-Super-Team --skill starter-kit
Clone the repo
git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team

Made for: Claude Code, Codex.

Or install agi-super-team, the plugin that ships this one along with the rest of its 193 skills, 1 agent.

Wrote 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.

agentmods badge for verb-domain-task

README.md
[![agentmods](https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/starter-kit/github.svg)](https://agentmods.dev/skills/aaaaqwq/agi-super-team/starter-kit)
Your own site
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/starter-kit"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/starter-kit/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.

agentmods 80×15 button for verb-domain-task

Your own site · 80×15
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/starter-kit"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/starter-kit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 223 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.00223
Opus 5 $0.00022 $0.00112
Sonnet 5 $0.00009 $0.00045
Haiku 4.5 $0.00004 $0.00022

Measured 4d ago against content hash 252194255926, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

verb-domain-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 4d 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.

skills/author-agent-suite/assets/starter-kit/SKILL.md · 30 lines

What it actually says

{{SKILL_TITLE}}

{{ONE_PARAGRAPH_OBJECTIVE_AND_CRITICAL_BOUNDARY}}

Workflow

  1. {{STEP_1_NAME}}. {{STEP_1_ACTION_AND_EVIDENCE}}
  2. {{STEP_2_NAME}}. {{STEP_2_ACTION_AND_EVIDENCE}}
  3. {{STEP_3_NAME}}. {{STEP_3_ACTION_AND_EVIDENCE}}
  4. Validate. {{VALIDATION_AND_SUCCESS_CRITERIA}}

Non-negotiable boundaries

  • {{SAFETY_OR_IDENTITY_INVARIANT}}
  • {{SIDE_EFFECT_OR_AUTHORIZATION_RULE}}
  • {{FAILURE_REPORTING_RULE}}

Deliverables

{{EXPECTED_OUTPUTS_AND_HANDOFF}}

References

  • Read references/{{REFERENCE_FILE}} ({{REFERENCE_NAME}}) when {{READ_CONDITION}}.
Files

What ships with it

6 files 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.

Changes

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.

  1. 4d ago First seen · 30 lines · 44 tokens per session scan A 252194255926

Subscribe to this mod's changes

verb-domain-task is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed 2d ago), licensed MIT. It adds 44 tokens to every session and 223 once invoked, about $0.0002 per session on Opus 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 2026-09-05.

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