using-ecosystem

using-ecosystem is a skill for Claude Code, Codex from krzysztofsurdy/code-virtuoso. It costs 96 tokens per session (1,985 once invoked), scanned A, original, MIT.

An advisor for discovering which installed skill, agent, or team fits a task.

In plain words
What is it for?
Use it when onboarding, selecting a skill, delegating work to an agent, or coordinating several agents.
Why use it?
It helps users choose available tools based on the work they need done instead of guessing from names.

Skill for Claude CodeCodex

Part of the tools-virtuoso plugin — 11 skills shipped together

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.

agentmods
npx agentmods add skills/krzysztofsurdy/code-virtuoso/using-ecosystem
Any agent
npx skills add krzysztofsurdy/code-virtuoso --skill using-ecosystem
Clone the repo
git clone --depth 1 https://github.com/krzysztofsurdy/code-virtuoso

Made for: Claude Code, Codex.

Or install tools-virtuoso, the plugin that ships this one along with the rest of its 11 skills.

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 using-ecosystem

README.md
[![agentmods](https://agentmods.dev/badge/skills/krzysztofsurdy/code-virtuoso/using-ecosystem.svg)](https://agentmods.dev/skills/krzysztofsurdy/code-virtuoso/using-ecosystem)
Your own site
<a href="https://agentmods.dev/skills/krzysztofsurdy/code-virtuoso/using-ecosystem"><img src="https://agentmods.dev/badge/skills/krzysztofsurdy/code-virtuoso/using-ecosystem.svg" alt="Measured on agentmods" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,985 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00096 $0.01985
Opus 5 $0.00048 $0.00992
Sonnet 5 $0.00019 $0.00397
Haiku 4.5 $0.00010 $0.00198

Measured 2d ago against content hash e2d5ad90acad, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

using-ecosystem 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.

skills/tools/using-ecosystem/SKILL.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Using Ecosystem

Discover the right skill, agent, or team for the situation at hand. This skill teaches a discovery PROCESS - it does not maintain a hardcoded inventory. Every recommendation comes from scanning what is actually installed.

Core Principles

Principle Meaning
Scan, don't guess Always scan installed skills/agents/teams before recommending. Never assume something is available.
Match situation, not topic Pick the skill whose description triggers match what the user is doing, not the skill whose title loosely matches.
Agents act, skills inform Skills are reference material. Agents are actors. Delegate work to an agent; consult a skill.
Teams for multi-role work If the work needs 3+ agents coordinating, check for a pre-composed team before assembling ad-hoc.
Narrower wins If two skills overlap, pick the one with the tighter trigger match.
Chain when work crosses domains Multi-step tasks often need two or three agents in sequence.

Step 1: Scan What Is Installed

Run the discovery commands from discovery-commands to build a live index of installed skills, agents, and teams. Read each frontmatter name and description field.

Do NOT skip this step. Do NOT recommend from memory. The installed set varies per user and per project.


Step 2: Classify the User's Situation

Determine what the user needs:

Signal Category
Needs reference material, patterns, or principles Knowledge skill
Needs to generate a specific output (ticket, PR message, report, rules file) Tool skill
Needs to follow a step-by-step operational procedure Playbook skill
Needs framework-specific component reference Framework skill
Needs a single focused task done (investigate, review, implement) Specialist agent
Needs ongoing domain ownership (requirements, architecture, QA) Role agent
Needs coordinated multi-agent delivery (feature, release, review cycle) Team

Read the full file on GitHub · 179 lines

Files

What ships with it

3 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. 2d ago First seen · 179 lines · 96 tokens per session scan A e2d5ad90acad

Subscribe to this mod's changes

using-ecosystem is a skill published in the GitHub repository krzysztofsurdy/code-virtuoso (20 stars, last pushed 3mo ago), licensed MIT. It adds 96 tokens to every session and 1,985 once invoked, about $0.0005 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.

Related

Other skills, from other repositories

hermes-diagnostic-review

Use when running a read-only diagnostic review of recent Hermes sessions to find recurring mistakes, failed tool calls, and repeated fixes, then propose suggestion-only improvements and reusable skills. Human-gated; never auto-applies.

AtlasOmnia/hermes-custom-pack · 49 tokens

instruction-eval

Change one condition an agent runs under (instruction text, the reference material instructions point at, MCP tools and permissions, hooks, skill files), then run the same prompts before and after, several times each, to see what actually changes. Produces an HTML report showing both arms' answers side by side. Use…

2ykwang/agent-skills · 179 tokens

worth-building

Decide how elaborate to build something (simple vs. robust) and return a concrete, PoC-shaped proposal at that level — not over- or under-engineered, but right-sized. Use whenever someone is building something and the investment level is unclear: "quick or proper?", "MVP vs. real product", "is this over-engineering?"…

2ykwang/agent-skills · 128 tokens

django-ticket-triage

Analyze a Django Trac ticket and produce a triage recommendation report — duplicate search, related PRs, forum threads, and the affected source code. Use when the user gives a Django ticket number, or asks whether a ticket is valid, a duplicate, or ready for a triage stage.

2ykwang/agent-skills · 65 tokens

gh-issues

Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5]…

SafeAI-Lab-X/ClawKeeper · 116 tokens

healthcheck

Host security hardening and risk-tolerance configuration for OpenClaw deployments. Use when a user asks for security audits, firewall/SSH/update hardening, risk posture, exposure review, OpenClaw cron scheduling for periodic checks, or version status checks on a machine running OpenClaw (laptop, workstation, Pi, VPS).

SafeAI-Lab-X/ClawKeeper · 70 tokens