SkillNet is infrastructure for finding, creating, evaluating, combining, and coordinating reusable capabilities for AI agents. Agent developers use it as a searchable and installable library of skills and as a system for selecting skills for particular tasks. The catalogue contains skills that can be discovered, installed, or used with SkillNet.
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/zjunlp/skillnet/task-completion-focusnpx skills add zjunlp/SkillNet --skill task-completion-focusgit clone --depth 1 https://github.com/zjunlp/SkillNetWrote 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/zjunlp/skillnet/task-completion-focus)<a href="https://agentmods.dev/skills/zjunlp/skillnet/task-completion-focus"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/task-completion-focus.svg" alt="Measured on agentmods" 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 | $0.00060 | $0.00261 |
| Opus 5 | $0.00030 | $0.00130 |
| Sonnet 5 | $0.00012 | $0.00052 |
| Haiku 4.5 | $0.00006 | $0.00026 |
Grade A, and why
task-completion-focus 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
Skill: Task Completion Focus
When to Use
The final required object (e.g., grown banana, crafted item) is visibly present and you need to formally signal task completion. Do not use for intermediate steps.
Procedure
look around— confirm the target object is visible in the scene.focus on <OBJECT>— signal task completion.- Ambiguity handling: If the environment returns "Ambiguous request" with numbered options, respond with the option number (e.g.,
0) for the target most directly associated with your task goal.
Example
Task: "Grow a banana." After successful cultivation:
look around— observation: "On the banana tree you see: a banana, a flower."focus on banana on banana tree- If ambiguous prompt appears listing multiple bananas, select
0(first instance). - Observation confirms task completion.
What ships with it
2 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.
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 · 21 lines · 60 tokens per session scan A cb20bb71f4e9
task-completion-focus is a skill published in the GitHub repository zjunlp/SkillNet (1,253 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 261 once invoked, about $0.0003 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 2026-09-03.
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