Borrowing it
Nothing to install: this file belongs to nickmisasi/planner. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nickmisasi/planner/main/.claude/skills/implement/SKILL.mdgit clone --depth 1 https://github.com/nickmisasi/plannerWrote 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/nickmisasi/planner/implement)<a href="https://agentmods.dev/skills/nickmisasi/planner/implement"><img src="https://agentmods.dev/badge/skills/nickmisasi/planner/implement/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/nickmisasi/planner/implement"><img src="https://agentmods.dev/badge/skills/nickmisasi/planner/implement.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 | $0.00067 | $0.02772 |
| Opus 5.5 | $0.00027 | $0.01109 |
| Sonnet 5.5 | $0.00013 | $0.00554 |
| Haiku 4.5 | $0.00007 | $0.00277 |
Grade A, and why
implement 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 2mo 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convert a refined spec into thorough implementation plans that an orchestrating agent and its coding sub-agents can execute against. The detailed, file-oriented plan(s) live in the target repo worktree(s), and the high-level execution sequencing plan lives in the planning repo's idea folder.
Instructions
When the user invokes /implement, follow these steps:
1. Ensure Context is Loaded
Read the current idea's files:
spec.mdresearch.mdassumptions.mdsession.mdIMPL_ORCHESTRATION_PLAN.md(if it already exists — use it as prior context when regenerating or refining the implementation plan)
Also read:
projects/<project>/project.yaml— to get the target repo URL(s)projects/<project>/context.md— for known architecture context
If no idea is currently active, trigger the /continue skill first to select one.
Gate check: The idea should be in ready or review status. If it's still drafting or iterating, warn the user and suggest running /iterate first. Proceed only if they confirm.
2. Deep-Dive the Target Repo (Mandatory)
Spawn an explorer agent to analyze the target repository. This is not optional — the implementation plan must be grounded in the actual codebase structure.
Use the repo's local_path from project.yaml (or the worktree path from session.md if active). Point the explorer at that directory — no cloning needed.
Give the explorer a focused brief based on the spec:
Explore <repo> with the goal of informing an implementation plan for: <1-2 sentence spec summary>
Specifically report:
1. **Project structure** — directory layout, module organization, key entry points
2. **Relevant existing code** — files/modules that will be modified or extended
3. **Patterns and conventions** — how similar features are implemented (naming, file placement, testing patterns, error handling)
4. **Dependencies** — relevant libraries, frameworks, internal packages
5. **Test infrastructure** — how tests are organized, what frameworks are used, how to run them
6. **Build/deploy** — build system, CI/CD pipeline, deployment patterns
7. **Extension points** — plugin APIs, hooks, interfaces, or abstractions the implementation should use
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.
- 2mo ago First seen · 265 lines · 67 tokens per session scan A 63a11da3959a
implement is a skill published in the GitHub repository nickmisasi/planner (5 stars, last pushed 6mo ago), licensed MIT. It adds 67 tokens to every session and 2,772 once invoked, about $0.0003 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.
implement compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| implementnickmisasi/planner | Skill | 5 | 6mo ago | MIT | A | 67 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |