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 hamzabellouch/agent-skills --skill agent-platform-prompt-managementgit clone --depth 1 https://github.com/hamzabellouch/agent-skillsWrote 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/hamzabellouch/agent-skills/agent-platform-prompt-management)<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/agent-platform-prompt-management"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/agent-platform-prompt-management/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/hamzabellouch/agent-skills/agent-platform-prompt-management"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/agent-platform-prompt-management.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 | $0.00055 | $0.01596 |
| Opus 5 | $0.00028 | $0.00798 |
| Sonnet 5 | $0.00011 | $0.00319 |
| Haiku 4.5 | $0.00006 | $0.00160 |
Grade A, and why
agent-platform-prompt-management 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 11d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Platform Prompt Management
Usage Guide
To use this skill effectively:
-
Generate Code: Provide the Python snippets below to the user to help them manage prompts in Agent Platform.
-
No File System Search: Do not try to find Python files or scripts on the file system for these operations.
Safety & Confirmation Tiers (CRITICAL)
Before executing any commands or scripts on behalf of the user, you must adhere to the following safety tiers based on the action requested, to prevent accidental mutation or permanent deletion of prompt resources:
- Tier R: Read-only (
list,get)- No confirmation needed. Execute immediately to gather information.
- Tier M: Mutating & Reversible (
create)- Requires interactive confirmation with 'Yes'/'No' options before executing prompt creation, to prevent unintended resource proliferation or misconfiguration. The confirmation prompt must clearly explain the proposed prompt creation and its key parameters (e.g., display name, template text, target model). Natural-language paraphrases without specifying the parameters are not sufficient.
- Same-turn restriction: Do not execute the creation code in the same turn as presenting the confirmation prompt. Stop and wait for the user's reply; only execute after explicit 'Yes' / approval.
- Gold Standard Example:
I will create a prompt in Agent Platform with the following parameters. Please confirm this information before I proceed:
- Display Name:
Customer Support Greeting - Target Model:
gemini-2.5-pro - Template Text: "Hello {{user_name}}, how can I help..." Do you confirm? [Yes/No]
- Display Name:
- Tier D: Destructive & Irreversible (
delete)- Requires explicit typed confirmation (e.g. "I confirm" or "Yes, delete it") before executing prompt deletion, to prevent accidental permanent loss of production prompt assets. Ask for confirmation before any pre-flight checks.
- Same-turn restriction: NEVER execute in the same turn as asking for typed confirmation. Wait for the user to reply in a new turn.
- Gold Standard Example:
I will permanently delete the following prompt from Agent Platform. This action is irreversible. Please explicitly type your confirmation (e.g., "I confirm") before I proceed:
- Prompt ID:
prompt_12345abc - Display Name:
Legacy Outdated PromptPlease type your confirmation to proceed.
- Prompt ID:
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.
- 11d ago First seen · 177 lines · 55 tokens per session scan A 7f91ac3ebbb8
agent-platform-prompt-management is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,596 once invoked, about $0.0003 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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