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 IgorWarzocha/howaboua-pi-stuff --skill agent-tool-designgit clone --depth 1 https://github.com/IgorWarzocha/howaboua-pi-stuffWrote 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/igorwarzocha/howaboua-pi-stuff/agent-tool-design)<a href="https://agentmods.dev/skills/igorwarzocha/howaboua-pi-stuff/agent-tool-design"><img src="https://agentmods.dev/badge/skills/igorwarzocha/howaboua-pi-stuff/agent-tool-design/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.
<a href="https://agentmods.dev/skills/igorwarzocha/howaboua-pi-stuff/agent-tool-design"><img src="https://agentmods.dev/badge/skills/igorwarzocha/howaboua-pi-stuff/agent-tool-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00019 | $0.00829 |
| Opus 5 | $0.00010 | $0.00415 |
| Sonnet 5 | $0.00004 | $0.00166 |
| Haiku 4.5 | $0.00002 | $0.00083 |
Grade A, and why
agent-tool-design 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
For a Pi tool, also read references/pi.md.
Start from what the agent knows
- Prefer canonical tool names and argument shapes already present in the target model's training.
- Treat a familiar tool schema as a runtime binding, not a tutorial. State only this implementation's meaningful deviations.
- Give an unfamiliar capability an obvious action name and familiar inputs. The agent should predict the call from the name and schema.
- When unsure, present the bare contract to the target model first. Add only the fact it could not infer correctly.
Fix model choices at the model boundary
- When the implementation supports the right behaviour but the model selects the wrong action or argument, treat it as a model-facing contract failure first.
- Fix the name, default, argument description, or prompt guidance before adding runtime policy, heuristics, or extra state.
- Describe choices in terms of user intent, not only mechanics. “False returns immediately” explains execution. “Use false only while continuing other work” changes the model's decision.
- Test paired natural requests that differ only at the decision boundary. Confirm the model chooses correctly before changing implementation.
Keep the decision surface small
- Give one tool one coherent job.
- Expose only decisions the caller must make. Keep providers, models, prompts, commands, internal modes, formatting, and policy inside the implementation unless the agent genuinely chooses them.
- Require only the minimum valid input. Add an optional field only when omission has a useful deterministic meaning.
- Prefer conventional names such as
cmd,path,query,cwd, andmessage. Use a small enum when the choice is genuinely closed. - If a field needs a paragraph to make sense, remove it, rename it, or reconsider the tool boundary.
Let the schema speak
- Do not narrate types, requiredness, optionality, enums, defaults, or limits already encoded by the schema.
- Omit a field description when its name is sufficient.
- Write necessary descriptions as compact payload fragments:
Cwd,Wait ms,Recent days,Truncate. - Omit cosmetic terminal full stops, backticks, Markdown, examples, and grammatical padding. Preserve punctuation and formatting only when they carry literal syntax or prevent ambiguity.
- Keep safe compatibility aliases inside argument preparation rather than advertising them in the schema.
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.
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.
- 9d ago First seen · 72 lines · 19 tokens per session scan A dac0fd58bb5f
agent-tool-design is a skill published in the GitHub repository IgorWarzocha/howaboua-pi-stuff (358 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 829 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 2026-08-30.
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