Borrowing it
Nothing to install: this file belongs to itallstartedwithaidea/gemini-cli-googleadsagent. 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/itallstartedwithaidea/gemini-cli-googleadsagent/main/.gemini/commands/prompt-suggest.tomlgit clone --depth 1 https://github.com/itallstartedwithaidea/gemini-cli-googleadsagentWrote 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/itallstartedwithaidea/gemini-cli-googleadsagent/prompt-suggest)<a href="https://agentmods.dev/commands/itallstartedwithaidea/gemini-cli-googleadsagent/prompt-suggest"><img src="https://agentmods.dev/badge/commands/itallstartedwithaidea/gemini-cli-googleadsagent/prompt-suggest/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/itallstartedwithaidea/gemini-cli-googleadsagent/prompt-suggest"><img src="https://agentmods.dev/badge/commands/itallstartedwithaidea/gemini-cli-googleadsagent/prompt-suggest.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 | $0.00263 |
| Opus 5.5 | $0.00000 | $0.00105 |
| Sonnet 5.5 | $0.00000 | $0.00053 |
| Haiku 4.5 | $0.00000 | $0.00026 |
Grade A, and why
prompt-suggest 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 10d 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.
This is a copy
100% identical to prompt-suggest — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
description = "Analyze agent behavior and suggest high-level improvements to system prompts." prompt = """
Prompt Engineering Analysis
You are a world-class prompt engineer and an expert AI engineer at the top of your class. Your goal is to analyze a specific agent behavior or failure and suggest high-level improvements to the system instructions.
Observed Behavior / Issue: {{args}}
Reference Context:
- System Prompt Logic: @packages/core/src/core/prompts.ts
Task
- Analyze the Failure: Review the provided behavior and identify the underlying instructional causes. Use the
/introspectcommand output if provided by the user. - Strategic Insights: Share your technical view of the issue. Focus on the "why" and identify any instructional inertia or ambiguity.
- Propose Improvements: Suggest high-level changes to the system instructions to prevent this behavior.
Principles
- Avoid Hyper-scoping: Do not create narrow solutions for specific scenarios; aim for generalized improvements that handle classes of behavior.
- Avoid Specific Examples in Suggestions: Keep the proposed instructions semantic and high-level to prevent the agent from over-indexing on specific cases.
- Maintain Operational Rigor: Ensure suggestions do not compromise safety, security, or the quality of the agent's work. """
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.
- 10d ago First seen · 23 lines · 0 tokens per session scan A 6771323f1f87
prompt-suggest is a command published in the GitHub repository itallstartedwithaidea/gemini-cli-googleadsagent (6 stars, last pushed 11d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 263 tokens. A static security scan graded it A with 0 findings. It is 100% identical to prompt-suggest, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
maestro-companion
Quick execution for small tasks — minimal run lifecycle (start + done) with evidence recording. Full LLM capability, scoped to mechanically clear tasks.
maestro-fork
Create or sync session worktree for parallel dev.
maestro-guard
Manage editing boundary restrictions.
maestro-issue
A command for managing issues, which are tracked problems or tasks, through their full lifecycle.
maestro-spec
A command for recording project rules and constraints, such as coding standards, architecture decisions, or quality requirements. It turns a plain-language statement into a recorded specification.