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 The-AI-Directory-Company/agents-and-skills --skill code-generation-promptgit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-skillsWrote 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/the-ai-directory-company/agents-and-skills/code-generation-prompt)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/code-generation-prompt"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/code-generation-prompt/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/the-ai-directory-company/agents-and-skills/code-generation-prompt"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/code-generation-prompt.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 | $0.00033 | $0.01377 |
| Opus 5 | $0.00016 | $0.00688 |
| Sonnet 5 | $0.00007 | $0.00275 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
code-generation-prompt 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 8d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Generation Prompt
Before you start
Gather the following from the user before generating any code:
- What does the code need to do? — Specific behavior, not vague goals
- What language and framework? — Including version constraints
- What are the inputs and outputs? — Data types, formats, example values
- What are the constraints? — Performance requirements, dependencies allowed, compatibility targets
- Where does this code live? — Standalone script, library function, API endpoint, UI component
- Are there existing patterns to follow? — Link to existing code in the repo or style guide
If any of these are missing, ask before proceeding. Generating code from incomplete requirements produces throwaway output.
Procedure
1. Define the requirement in structured form
Write the requirement as a structured block before generating code. This prevents drift between what was asked and what gets built.
TASK: [one sentence describing the function]
LANGUAGE: [language + version]
FRAMEWORK: [framework + version, or "none"]
INPUTS: [list each input with type and example value]
OUTPUTS: [return type with example value]
CONSTRAINTS: [performance, security, compatibility requirements]
ERROR CASES: [what should happen when inputs are invalid]
2. Choose the generation strategy
Select one based on complexity:
- Direct generation — For isolated functions under 50 lines. Write the full implementation in one pass.
- Scaffold-then-fill — For modules with multiple functions. Generate the interface (function signatures, types, exports) first, then implement each function.
- Test-first generation — For logic-heavy code. Generate test cases from the requirements first, then write the implementation to pass them.
3. Write the prompt
Structure the prompt in this order:
- Role and context — What the code is part of, what conventions to follow
- Exact task — What to implement, referencing the structured requirement
- Input/output contract — Types, validation rules, example values
- Constraints — What NOT to do (no external dependencies, no async, no mutation, etc.)
- Output format — Single file, multiple files, include tests, include types
What ships with it
4 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.
- 8d ago First seen · 137 lines · 33 tokens per session scan A 99217e468025
code-generation-prompt is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 1,377 once invoked, about $0.0002 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 2026-09-03.
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