Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/agentsope/skillalchemy/agentsop-prompt-compilation)<a href="https://agentmods.dev/skills/agentsope/skillalchemy/agentsop-prompt-compilation"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsop-prompt-compilation.svg" alt="Measured on agentmods" 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 | $0.00096 | $0.06958 |
| Opus 5 | $0.00048 | $0.03479 |
| Sonnet 5 | $0.00019 | $0.01392 |
| Haiku 4.5 | $0.00010 | $0.00696 |
Grade A, and why
agentsop-prompt-compilation 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 6d 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 — 401 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prompt-compilation — The Compile-Readiness Gate
"It's unproductive to launch optimization runs using a poorly designed program or a bad metric." — DSPy core team [dspy.ai/learn/optimization/overview/]
"Compile when you can measure. The optimizer maximizes your metric — garbage metric in, garbage prompt out." — this skill's operating principle (synthesized from the line above + DSPy Case C)
This is an enhancement-overlay decision skill. It answers exactly one question the broad [[dspy]] library
skill buries under API surface: have you earned the right to run an optimizer yet, and which one? It produces a
go / no-go gate plus an optimizer pick. It defers every implementation detail — Signature syntax, module choice,
compile() calls, save/deploy — to [[dspy]] and the full workflow in [[agentsop-dspy]]. It defers metric construction
to [[agentsop-metric-design]]; this skill only checks the metric exists and is validated, then uses it as the gate.
The trap it removes: people reach for MIPROv2(auto="heavy") because the API is right there, before they have a
metric worth maximizing or enough data to avoid memorization. Compilation is a hyperparameter search costing
hundreds-to-thousands of LM calls ($2–$40+, minutes-to-hours) [dspy.ai/faqs/]. Spending that on an un-validated
metric or 8 examples is pure waste.
1. 何时激活 (When to Activate)
Activate when all three of these are plausibly true (the gate then confirms them):
- A hand-tuned prompt has plateaued. The team has manually iterated few-shot examples / wording past the point
of obvious returns. Symptom from
[[agentsop-dspy]]§1: "the team manually tunes few-shot examples; a metric exists but isn't being used to drive prompt design." - A metric exists (or can be built). There is a
metric(example, pred) -> bool|float— or one can be written and human-validated. Without this, do not activate; the optimizer has nothing to maximize. - Labeled examples exist. There is a dev set. The count determines which optimizer is even legal (§3, §4.2).
What ships with it
3 files 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.
- 6d ago First seen · 401 lines · 96 tokens per session scan A ecc3816152d4
agentsop-prompt-compilation is a skill published in the GitHub repository agentsope/SkillAlchemy (366 stars, last pushed 4d ago), licensed MIT. It adds 96 tokens to every session and 6,958 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 2026-08-30.
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