implement

A command that carries out an already approved coding task in small, checkable steps.

In plain words
What is it for?
Use it after a task has been approved and needs to be implemented incrementally.
Why use it?
Breaking approved work into verifiable pieces makes it easier to review progress and catch problems during implementation.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/mrkt365-india/boilerforge/implement
Clone the repo
git clone --depth 1 https://github.com/MRKT365-India/boilerforge

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 14 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00014
Opus 5 $0.00000 $0.00007
Sonnet 5 $0.00000 $0.00003
Haiku 4.5 $0.00000 $0.00001

Measured yesterday against content hash 00a264c2bfd7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

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.

workflow-packs/claude/.claude/commands/implement.md · 4 lines

What it actually says

implement

Implement the approved task in small, verifiable steps.

Changes

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.

  1. yesterday First seen · 4 lines · 0 tokens per session scan A 00a264c2bfd7

Subscribe to this mod's changes

implement is a command published in the GitHub repository MRKT365-India/boilerforge (0 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 14 tokens. 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.

Related

Other commands, from other repositories

review-code

Read ALL memory bank code rules + best practices, check the files that changed, and APPLY fixes so they adhere. The active counterpart to /scan (which is read-only). Use after an AI session, before commit, to make changed files compliant.

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rules

Command "rules" from chohra-med/expo_boilerplate, covering invocation, what a "rules-boundary" directory is, the five sections (one owner agent each), generate (the "create them if they don't exist" path) and resolve (what each agent reads).

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init

Command "init" from chohra-med/expo_boilerplate, covering command: init — spec-driven bootstrap, invocation, step 1 — capture intent (the interview, one message), step 2 — scaffold (copy from templates/, fill the {{...}}) and step 4 — write the first spec from the goal.

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generate-agents

Command "generate-agents" from chohra-med/expo_boilerplate, covering invocation, how it works, the concern each agent gets (one per agent), rules for the injected block (every agent) and idempotent + the loop.

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learn

Command "learn" from chohra-med/expo_boilerplate, covering command: learn — the learning loop (feedback → rules), when to run it, invocation, the loop (6 steps) and 1 — capture.

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tickets

Command "tickets" from chohra-med/expo_boilerplate, covering invocation, source a — a ticket mcp (linear / github issues / jira / …), source b — an inline plan (no ticket system), then: build and hard rules.

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