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 JoshuaRamirez/advanced-prompting-engine --skill prompt-refinergit clone --depth 1 https://github.com/JoshuaRamirez/advanced-prompting-engineWrote 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/joshuaramirez/advanced-prompting-engine/prompt-refiner)<a href="https://agentmods.dev/skills/joshuaramirez/advanced-prompting-engine/prompt-refiner"><img src="https://agentmods.dev/badge/skills/joshuaramirez/advanced-prompting-engine/prompt-refiner/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/joshuaramirez/advanced-prompting-engine/prompt-refiner"><img src="https://agentmods.dev/badge/skills/joshuaramirez/advanced-prompting-engine/prompt-refiner.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 | $0.00101 | $0.08570 |
| Opus 5 | $0.00051 | $0.04285 |
| Sonnet 5 | $0.00020 | $0.01714 |
| Haiku 4.5 | $0.00010 | $0.00857 |
Grade A, and why
Prompt Refiner 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.
How it starts
The opening of the file, as written. The whole thing — 462 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Refiner
Iteratively refine a prompt using the Advanced Prompting Engine (APE) MCP server v0.8.0. Takes raw intent, measures it across 12 philosophical faces via a BGE-large-en-v1.5 semantic bridge (1024d, full-sentence encoding), interprets deficiencies using the interpret_basis tool, rewrites to address gaps, and repeats until the prompt achieves dimensional coverage appropriate for its purpose.
The 12 Faces
Each face is a 12x12 grid with named axis polarities. Position on each axis carries meaning.
| Face | X Axis (0→11) | Y Axis (0→11) | Core Question |
|---|---|---|---|
| Ontology | Particular → Universal | Static → Dynamic | What entities and relationships fundamentally exist? |
| Epistemology | Empirical → Rational | Certain → Provisional | How do we know domain states and conditions are true? |
| Axiology | Absolute → Relative | Quantitative → Qualitative | By what criteria is worth determined? |
| Teleology | Immediate → Ultimate | Intentional → Emergent | What ultimate purposes does each interaction serve? |
| Phenomenology | Objective → Subjective | Surface → Deep | How are experiences represented and realized? |
| Ethics | Deontological → Consequential | Agent → Act | What obligations and moral warrants govern right action? |
| Aesthetics | Autonomous → Contextual | Sensory → Conceptual | What qualities of form and significance constitute recognition? |
| Praxeology | Individual → Coordinated | Reactive → Proactive | How are actions, behaviors, and intentions structured? |
| Methodology | Analytic → Synthetic | Deductive → Inductive | What processes govern construction and evolution? |
| Semiotics | Explicit → Implicit | Syntactic → Semantic | How are signals and data meaningfully communicated? |
| Hermeneutics | Literal → Figurative | Author-intent → Reader-response | What frameworks govern interpretation and understanding? |
| Heuristics | Systematic → Intuitive | Conservative → Exploratory | What practical strategies guide handling of complexities? |
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 · 462 lines · 101 tokens per session scan A 5856c4ef0822
Prompt Refiner is a skill published in the GitHub repository JoshuaRamirez/advanced-prompting-engine (0 stars, last pushed 14d ago), licensed MIT. It adds 101 tokens to every session and 8,570 once invoked, about $0.0005 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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