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 bikeread/promethos --skill design-agent-toolsgit clone --depth 1 https://github.com/bikeread/promethosWrote 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/bikeread/promethos/design-agent-tools)<a href="https://agentmods.dev/skills/bikeread/promethos/design-agent-tools"><img src="https://agentmods.dev/badge/skills/bikeread/promethos/design-agent-tools/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/bikeread/promethos/design-agent-tools"><img src="https://agentmods.dev/badge/skills/bikeread/promethos/design-agent-tools.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00026 | $0.00699 |
| Opus 5.5 | $0.00010 | $0.00280 |
| Sonnet 5.5 | $0.00005 | $0.00140 |
| Haiku 4.5 | $0.00003 | $0.00070 |
Grade A, and why
design-agent-tools 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 2mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
Define a tool contract that is easy for an agent to use correctly and hard to misuse silently.
Inputs
- Tool purpose
- Upstream caller expectations
- Expected failure conditions and side effects
Non-Goals
- Implementing the tool runtime
- Designing the entire agent around a single tool
- Choosing the approval or autonomy policy that governs the tool
Workflow
Trigger signals
- Agent calls a tool with wrong arguments repeatedly
- Tool errors are vague and the agent cannot recover
- User says "it keeps misusing this tool"
- A new tool is being added without a documented contract
1. State the job the tool owns
Describe the single job the tool performs and the caller state it expects before invocation. Success criteria: The tool has one clear purpose and is not acting as a generic escape hatch.
2. Define input and output invariants
Specify what the tool accepts, what shape it returns, and what fields the caller may depend on every time. Success criteria: The contract is explicit enough to implement and consume without guessing field meanings.
3. Define error classes and retry behavior
Separate validation errors, environmental failures, permission denials, and transient faults. State what is safe to retry and what is not. Success criteria: The calling agent can distinguish recoverable from terminal failure paths.
4. Decide idempotency and replay behavior
State whether repeated calls with the same intent are safe, unsafe, or conditionally safe, and describe what the caller must do before retrying a mutating operation. Success criteria: Retry behavior and idempotency expectations are explicit, especially for writes and external side effects.
5. Make side effects and governing permission references visible
Document whether the tool reads, writes, mutates state, triggers external effects, and which existing permission or autonomy class the caller should apply when invoking it. Success criteria: The tool's risk profile is obvious from the contract without making the tool contract itself the owner of approval policy.
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.
- 2mo ago First seen · 91 lines · 26 tokens per session scan A 458ab67a1511
design-agent-tools is a skill published in the GitHub repository bikeread/promethos (33 stars, last pushed 7mo ago), licensed MIT. It adds 26 tokens to every session and 699 once invoked, about $0.0001 per session on Opus 5.5. 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.
design-agent-tools compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| design-agent-toolsbikeread/promethos | Skill | 33 | 7mo ago | MIT | A | 26 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |