tool-selection

A review skill that checks whether an agent chose suitable MCP tools instead of shell commands.

In plain words
What is it for?
It is used to evaluate traces containing Bash calls and assess tool-selection efficiency.
Why use it?
It helps identify inefficient tool choices when a connected tool could have handled the task directly.

Skill for Claude CodeCodex

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/databricks-solutions/ai-dev-kit/tool-selection
Any agent
npx skills add databricks-solutions/ai-dev-kit --skill tool-selection
Clone the repo
git clone --depth 1 https://github.com/databricks-solutions/ai-dev-kit

Made for: Claude Code, Codex.

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 537 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin unknown 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 $0.00041 $0.00537
Opus 5 $0.00020 $0.00269
Sonnet 5 $0.00008 $0.00107
Haiku 4.5 $0.00004 $0.00054

Measured 2d ago against content hash ef38c9c55f4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tool-selection scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Job management → `mcp__databricks__create_job`, `mcp__databricks__run_job` (not REST API via curl)
.test/eval-criteria/tool-selection/SKILL.md · 50 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

1 file 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 · 50 lines · 41 tokens per session scan A ef38c9c55f4a

Subscribe to this mod's changes

tool-selection is a skill published in the GitHub repository databricks-solutions/ai-dev-kit (1,882 stars, last pushed 20d ago), with no licence file. It adds 41 tokens to every session and 537 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.