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 vikasudasi/skill-vault --skill agent-tool-usegit clone --depth 1 https://github.com/vikasudasi/skill-vaultWrote 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/vikasudasi/skill-vault/agent-tool-use)<a href="https://agentmods.dev/skills/vikasudasi/skill-vault/agent-tool-use"><img src="https://agentmods.dev/badge/skills/vikasudasi/skill-vault/agent-tool-use.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 | $0.00025 | $0.00407 |
| Opus 5 | $0.00013 | $0.00204 |
| Sonnet 5 | $0.00005 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00041 |
Grade A, and why
agent-tool-use 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 7d 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
Designing Agents that Use Tools
Use when an LLM should take actions via tools rather than just generate text.
Core loop
user -> plan -> [tool call] -> observe -> next step -> ... -> answer
Maintain an explicit state of what the agent has done and what it knows; don't let it freewheel.
Tool schema design
- Narrow + typed tools; the schema is the contract the model reads.
- One action per tool; compose complex behavior from small tools.
- Return structured, machine-readable results the agent can act on
(Skill Vault returns lightweight
SkillCards, then a fetch tool for the body).
Error handling
Tools fail. Surface structured errors ({"error": "...", "code": "..."}) so the
agent can react, retry, or report — never let a raised exception end the whole
turn without a path forward. Add retry limits to prevent infinite loops.
Grounding
The agent's tool results are its ground truth — never let it assert a result it
didn't observe. When a skill/registry returns content, have it verify integrity
before trusting (Skill Vault's verify_skill + content hashes).
Pitfalls
- Broad "do everything" tools encourage sloppy calls — split them.
- Guard against loops: cap tool calls per turn, require progress each step.
- Validate tool arguments before execution, not just after.
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.
- 7d ago First seen · 50 lines · 25 tokens per session scan A c618e3f60fea
agent-tool-use is a skill published in the GitHub repository vikasudasi/skill-vault (0 stars, last pushed 22d ago), licensed Apache-2.0. It adds 25 tokens to every session and 407 once invoked, about $0.0001 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 2026-08-31.
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