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 agentmods add skills/techymt/claude-code-superpowers/tool-definitionnpx skills add TechyMT/claude-code-superpowers --skill tool-definitiongit clone --depth 1 https://github.com/TechyMT/claude-code-superpowersWhat 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 | $0.00097 | $0.01777 |
| Opus 5 | $0.00048 | $0.00889 |
| Sonnet 5 | $0.00019 | $0.00355 |
| Haiku 4.5 | $0.00010 | $0.00178 |
Grade A, and why
tool-definition 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Definition
The pattern
A Tool is defined by calling buildTool({ ... }), which fills in safe defaults for isEnabled, isConcurrencySafe, isReadOnly, isDestructive, checkPermissions, and other housekeeping methods. The Input is a Zod schema exposed via a get inputSchema() getter. The Output is the TypeScript type of data inside the result. These compose: the Zod schema drives runtime validation AND TypeScript types simultaneously, eliminating a class of bugs where validation and types diverge.
The key insight: buildTool factory + checkPermissions method + typed throw for errors. Permissions are not checked inside call() — the framework calls checkPermissions(input, context) before dispatching to call(). Errors are thrown (not returned), and the framework formats them for the LLM.
Why this matters
The LLM produces tool calls as JSON objects. Claude Code must: (1) validate the JSON against a schema, (2) check if the user permits this call, (3) execute the tool, (4) return a structured result back to the LLM. These four steps must be explicit and in order.
If a tool checked permissions after execution (or not at all), security would be broken. If validation happened after permission checking, the LLM could construct inputs that bypass validation for permitted tools. The pattern enforces the correct order: schema validation happens automatically when the framework calls the tool; checkPermissions is called by the framework before call() is ever reached; call() can assume permission is already granted.
Using Zod as the schema source of truth means the LLM's JSON schema (shown in the system prompt) and the runtime validator are the same artifact. When you change one, you change both.
How to apply it
- Define
inputSchemausinglazySchema(() => z.strictObject({ ... })). Add.describe()to each field — these become the LLM's parameter documentation. - Implement
isConcurrencySafe(input)andisReadOnly(input). These are called with the actual input, so you can make them input-dependent (e.g., a bash tool is concurrent-safe only for read commands). - Implement
checkPermissions()for side-effect tools — the framework calls it beforecall(). Return aPermissionDecisionindicating whether execution is allowed. - Return
{ data: result }fromcall()on success; throw for errors (the framework formats thrown errors for the LLM). - Use
onProgressto stream partial results to the UI. Call it with typed progress objects as work proceeds.
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.
- 2d ago First seen · 150 lines · 97 tokens per session scan A fbef9d2b472d
tool-definition is a skill published in the GitHub repository TechyMT/claude-code-superpowers (5 stars, last pushed 5mo ago), licensed MIT. It adds 97 tokens to every session and 1,777 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 2026-08-31.
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