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 agentmods add skills/dojogenesis/mcp/implementation-promptnpx skills add DojoGenesis/mcp --skill implementation-promptgit clone --depth 1 https://github.com/DojoGenesis/mcpWrote 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/dojogenesis/mcp/implementation-prompt)<a href="https://agentmods.dev/skills/dojogenesis/mcp/implementation-prompt"><img src="https://agentmods.dev/badge/skills/dojogenesis/mcp/implementation-prompt.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 | $0.00029 | $0.02878 |
| Opus 5 | $0.00015 | $0.01439 |
| Sonnet 5 | $0.00006 | $0.00576 |
| Haiku 4.5 | $0.00003 | $0.00288 |
Grade A, and why
implementation-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 3d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Prompt Skill
Version: 1.1 Author: Tres Pies Design Purpose: Write clear, comprehensive, and self-contained prompts that enable autonomous implementation agents to execute high-quality work without asking questions.
I. The Philosophy: The Art of Commissioning
A prompt to an autonomous agent is not a command; it is a commission. It is a formal request for a work of craftsmanship. The quality of the commission directly determines the quality of the work. A vague, incomplete, or ambiguous prompt invites confusion, rework, and failure. A clear, comprehensive, and well-grounded prompt is an act of respect for the builder's time and capability.
This skill transforms prompt writing from a hopeful guess into a deliberate and rigorous engineering discipline. By following this structure, we provide the agent with everything it needs to succeed — enabling it to work with precision, autonomy, and a deep understanding of the existing codebase.
II. When to Use This Skill
- After a specification has been finalized and has passed the pre-implementation checklist
- When commissioning a new development task to an autonomous implementation agent
- When breaking down a large specification into smaller, manageable implementation chunks
- When preparing work for parallel track execution
III. The Prompt Writing Workflow
Step 1: Validate Specification Readiness
Goal: Ensure the specification is complete and implementation-ready before writing prompts.
Actions:
- Verify the specification has passed the pre-implementation-checklist (if applicable)
- Confirm backend grounding is complete (API contracts, data models, integration points)
- Check that all architectural decisions are documented
- Verify there are no missing dependencies or unclear requirements
- Identify if the work should be split into multiple tracks or sequential chunks
Key Insight: Never write an implementation prompt from an incomplete specification. The prompt quality is directly determined by the specification quality.
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.
- 3d ago First seen · 318 lines · 29 tokens per session scan A 4865ca0369c8
implementation-prompt is a skill published in the GitHub repository DojoGenesis/mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 2,878 once invoked, about $0.0001 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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