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 jxoesneon/Ciel --skill code_generationgit clone --depth 1 https://github.com/jxoesneon/CielWrote 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/jxoesneon/ciel/code_generation)<a href="https://agentmods.dev/skills/jxoesneon/ciel/code_generation"><img src="https://agentmods.dev/badge/skills/jxoesneon/ciel/code_generation/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/jxoesneon/ciel/code_generation"><img src="https://agentmods.dev/badge/skills/jxoesneon/ciel/code_generation.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 | $0.00017 | $0.00290 |
| Opus 5.5 | $0.00007 | $0.00116 |
| Sonnet 5.5 | $0.00003 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
code_generation 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 1mo 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.
What it actually says
code_generation
Generate code from a specification.
Operations
gen.function(spec, lang, style)— a function with tests if requested.gen.module(spec, target_path)— a module.gen.scaffold(framework, name)— framework-native scaffold.gen.transform(file, transformation)— AST-level edit (rename, extract, inline).
I/O Contract
io_contract:
input: { op, spec, target_path?, lang?, style? }
output: { files_written: [paths], diff }
idempotent: false
side_effects: [fs]
---
## Style Adherence
Project style rules from `configuration/local/rules.config.md`. When generating tests, respects project testing conventions (pytest vs jest etc).
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.
- 1mo ago First seen · 37 lines · 17 tokens per session scan A 6c0fcbf0afde
code_generation is a skill published in the GitHub repository jxoesneon/Ciel (1 stars, last pushed 2d ago), licensed Apache-2.0. It adds 17 tokens to every session and 290 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
Code Quality Review
Conduct a comprehensive code quality review focused on clean code, architecture, and project standards.
surge
Use when a user provides a PRD, spec, or detailed requirements document and needs a full project delivered through iterative expert orchestration — multi-round analyze/research/design/implement/QA cycles with convergence detection. NOT for: single-file edits, quick prototypes, simple Q&A, or tasks without a written…
ai-native-software-dev
Use when the user asks to build, change, modernize, or reconstruct non-trivial software with an AI-native workflow, including greenfield development, work in an existing codebase, or authorized reference-based product reconstruction; also use when lifecycle planning, architecture, implementation, testing, review…
expert-redteam-review
Use when a user asks to evaluate a complex, high-impact, ambiguous, cross-functional, or hard-to-reverse decision; mentions expert panel, red team, adversarial review, rebuttal, judge, arbitration, risk review, challenge assumptions, poke holes, or wants stronger decision quality than a normal review.
code-review
Revisão holística pré-commit (estilo PR Review). Valida o diff contra as 3 memórias vivas, a spec da task e Clean Code, em paralelo ao QA/Security (fan-out); a evidência de teste é exigida no join. Executada pelo Tech Lead; veredito escrito em review.md.
compound
Persistência de aprendizados nas memórias vivas ao final de cada ciclo. Use para "atualizar memória", "guardar aprendizados" ou "sincronizar contexto do projeto". Executada pelo Tech Lead após o PO definir Status entregue.