Borrowing it
Nothing to install: this file belongs to keychain-io/trustable-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/keychain-io/trustable-ai/main/.claude/commands/agent-spawn-example.mdgit clone --depth 1 https://github.com/keychain-io/trustable-aiWrote 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/commands/keychain-io/trustable-ai/agent-spawn-example)<a href="https://agentmods.dev/commands/keychain-io/trustable-ai/agent-spawn-example"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/agent-spawn-example/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/commands/keychain-io/trustable-ai/agent-spawn-example"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/agent-spawn-example.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 | $0.00000 | $0.00865 |
| Opus 5.5 | $0.00000 | $0.00346 |
| Sonnet 5.5 | $0.00000 | $0.00173 |
| Haiku 4.5 | $0.00000 | $0.00086 |
Grade A, and why
agent-spawn-example 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Example: Agent Spawning Pattern
This document demonstrates how workflows should instruct Claude Code to spawn specialized agents using the Task tool.
Step X: Create Specification (Spawn Senior Engineer)
YOU MUST USE THE TASK TOOL FOR THIS STEP.
Do not perform this work yourself. Instead, spawn a specialized agent:
Task Tool Parameters
Tool: Task
Parameters:
subagent_type: "general-purpose"
model: "opus"
description: "Create feature specification"
prompt: [SEE BELOW]
Prompt to Send to Agent
Copy the contents of .claude/agents/senior-engineer.md and append this task:
YOUR TASK
Create a detailed specification for Feature {feature_id}.
Input Materials:
- Epic: {epic_title}
- Feature: {feature_title}
- Acceptance Criteria: {acceptance_criteria}
Required Output:
- API Contract with:
- Function signatures with types
- Input constraints
- Output guarantees
- Error conditions
- Test scenarios covering:
- Happy path
- Edge cases
- Error handling
- Implementation notes
IMPORTANT: You have a fresh context dedicated to this task. Focus entirely on creating a precise, unambiguous specification.
After the agent completes: Save the output to docs/specifications/.
Step Y: Spec-Driven Testing (Spawn QA Tester - NO CODE ACCESS)
YOU MUST USE THE TASK TOOL FOR THIS STEP.
CRITICAL - Information Asymmetry: This agent must NOT see the implementation.
Task Tool Parameters
Tool: Task
Parameters:
subagent_type: "general-purpose"
model: "sonnet"
description: "Generate spec-driven tests"
prompt: [SEE BELOW - SPEC ONLY, NO CODE]
Prompt to Send to Agent
Copy the contents of .claude/agents/tester.md and append:
YOUR TASK
Generate comprehensive tests from this specification ONLY.
Specification: {specification_content}
API Contract: {api_contract}
YOU DO NOT HAVE ACCESS TO:
- The implementation code
- The developer's tests
- Any hint about how the code was written
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 · 170 lines · 0 tokens per session scan A ab0ea5ef067d
agent-spawn-example is a command published in the GitHub repository keychain-io/trustable-ai (2 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 865 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.