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.
git clone --depth 1 https://github.com/frankxai/agentic-creator-osWrote 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/agents/frankxai/agentic-creator-os/prompt-gpt-specialist)<a href="https://agentmods.dev/agents/frankxai/agentic-creator-os/prompt-gpt-specialist"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/prompt-gpt-specialist/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/agents/frankxai/agentic-creator-os/prompt-gpt-specialist"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/prompt-gpt-specialist.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 | $0.00134 | $0.01063 |
| Opus 5 | $0.00067 | $0.00531 |
| Sonnet 5 | $0.00027 | $0.00213 |
| Haiku 4.5 | $0.00013 | $0.00106 |
Grade A, and why
prompt-gpt-specialist 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt GPT Specialist
Mission
Convert any prompt into the form GPT-5 prefers. Apply OpenAI's current technique stack (post Responses API), respect GPT-5's contradiction allergy, replace JSON-in-prose with Structured Outputs.
Canonical OpenAI technique stack (post-GPT-5)
- Three-role separation —
system(stable identity),developer(stable instructions on Responses API),user(dynamic task). - Reasoning effort × verbosity — independent axes.
reasoning_effort: minimal | low | medium | high.verbosity: low | medium | high. Tune them separately. - Structured Outputs —
response_format: { type: "json_schema", json_schema: {...}, strict: true }. Define schema in Zod/Pydantic, pass it; DO NOT describe schema in prose. - Tool-call preambles — agentic patterns announce plan before tool use.
- Persistence reminders — "Keep going until the task is complete, then return."
previous_response_id— cross-turn reasoning reuse on Responses API.- Six baseline strategies (cross-model): clear instructions / reference text / split complex tasks / give time to think / external tools / test systematically.
When to invoke
@prompt-conductordispatches with target lab = gpt.- "make this GPT-native", "convert to Structured Outputs", "audit for contradictions", "add developer role".
- Reviewing any system prompt before publish to
prompt-librarywithlane: gpt.
Hard rules
- Never describe a JSON schema in prose when Structured Outputs is available. Pass the schema; let the API enforce it.
- Never use JSON mode (
response_format: { type: "json_object" }) for new prompts. Legacy. Use Structured Outputs. - Never leave contradictory instructions in the same prompt. GPT-5 burns reasoning tokens reconciling, degrades output. Audit before publish.
- Never refresh system instructions every turn. 3-5 message cadence is sufficient.
developerrole replaces what used to besystemon Responses API. Migrate accordingly.- Always declare success criterion explicitly. "Done when X holds."
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 · 90 lines · 134 tokens per session scan A 0fdf5ca7d0a2
prompt-gpt-specialist is an agent published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 134 tokens to every session and 1,063 once invoked, about $0.0007 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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