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 ciaransaunders/Skills-Public --skill prompt-architectgit clone --depth 1 https://github.com/ciaransaunders/Skills-PublicWrote 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/ciaransaunders/skills-public/prompt-architect)<a href="https://agentmods.dev/skills/ciaransaunders/skills-public/prompt-architect"><img src="https://agentmods.dev/badge/skills/ciaransaunders/skills-public/prompt-architect/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/ciaransaunders/skills-public/prompt-architect"><img src="https://agentmods.dev/badge/skills/ciaransaunders/skills-public/prompt-architect.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 | $0.00198 | $0.08990 |
| Opus 5 | $0.00099 | $0.04495 |
| Sonnet 5 | $0.00040 | $0.01798 |
| Haiku 4.5 | $0.00020 | $0.00899 |
Grade A, and why
prompt-architect 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 12d 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 — 591 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Architect
Create reusable prompt templates optimised for modern LLMs and autonomous agents. You are NOT completing the task — you are writing instructions another AI will execute.
Step 0: Determine Execution Mode and Target Model
Before anything else, determine two things. Ask the user OR infer from context:
A. Execution Mode
| Mode | Signal | Design Strategy |
|---|---|---|
| Chat | Single-turn or back-and-forth; human in the loop; quick iteration | Minimise specification. Over-specification penalty applies. |
| Autonomous | Agent runs unattended; multi-step; no mid-run correction; Cowork, Claude Code, coding agents, LangChain, etc. | Maximise specification. Completeness is the bottleneck. Under-specification causes silent failure. |
B. Target Model
| Model Family | Key Prompt Characteristics |
|---|---|
| Claude Fable 5 / Mythos 5 | Effort high default; xhigh for capability-sensitive workloads; medium/low for routine/interactive; adaptive thinking only — no extended thinking budgets; summarized-only thinking output; individual turns can run for many minutes — adjust client timeouts and streaming before deploying; one brief instruction steers an entire behaviour pattern (no need to enumerate); can over-elaborate at high/xhigh — use a brevity instruction; parallel subagents dispatched more readily than prior models; safety classifiers cover offensive cybersecurity + biology → stop_reason: "refusal" — configure fallback to Opus 4.8; do NOT instruct to reproduce/echo internal reasoning (triggers reasoning_extraction refusal); older prescriptive prompts often degrade output — review and prune; vision substantially improved |
| Claude Opus 4.8 (and Opus 4.7/4.6, Sonnet 4.6, Haiku 4.5) | Thinking OFF by default — set thinking: {type: "adaptive"} to enable; effort parameter now spans low/medium/high/xhigh/max (start xhigh for coding/agentic, min high for intelligence-sensitive); literal instruction-following — state scope explicitly, it won't generalise one instruction to other items; favours reasoning over tool calls (raise effort to get more tool use); spawns fewer subagents; length scales to task complexity; strong cream/serif design house-style that must be broken explicitly; 1M context default (200k on Microsoft Foundry); no prefill on last assistant turn |
| GPT-5.5 | Shorter, outcome-first prompts beat process-heavy stacks; reasoning effort knob (none/low/medium/high/xhigh) — re-evaluate low/medium before escalating; avoid unnecessary absolute rules (ALWAYS/NEVER/must) — use decision rules for judgment calls; explicit stopping conditions + retrieval budgets; phase param (commentary/final_answer) for long-running Responses agents; personality + collaboration-style split; text.verbosity control |
| Gemini 3.5 Flash (and 3.1 Pro, 3.1 Flash-Lite) | thinking_level minimal/low/medium/high — default is now medium (was high); low much improved for code/agentic; remove temperature/top_p/top_k (use defaults); thought preservation automatic across turns — pass full unmodified history with thought signatures; strict function-response matching (id + name + count); put multimodal content and inline instructions INSIDE function responses; negative constraints + question placed LAST, after data; no Computer Use (use Gemini 3 Flash Preview for that) |
| Unknown/Generic | Constraint-based, minimal scaffolding, XML structure |
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.
- 12d ago First seen · 591 lines · 198 tokens per session scan A ae60f81683b4
prompt-architect is a skill published in the GitHub repository ciaransaunders/Skills-Public (2 stars, last pushed 2mo ago), licensed MIT. It adds 198 tokens to every session and 8,990 once invoked, about $0.0010 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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