engine-implementer

An orchestrated implementation process for projects built with the Phase Rust engine. It divides the work into planning, review, implementation, measurement, and final verification, using fresh agents for several stages.

In plain words
What is it for?
Use it for end-to-end Phase Rust engine implementation work. It helps produce and review a plan, make focused edits, measure the candidate commit, and verify the committed result.
Why use it?
A large engine change is easier to trust when the plan, code, and measurements are reviewed independently. The process also creates a checkpoint before the final verification.

Skill for Claude CodeCodex

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 skills/phase-rs/phase/engine-implementer
Any agent
npx skills add phase-rs/phase --skill engine-implementer
Clone the repo
git clone --depth 1 https://github.com/phase-rs/phase

Made for: Claude Code, Codex.

Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,683 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 $0.00043 $0.07683
Opus 5 $0.00022 $0.03841
Sonnet 5 $0.00009 $0.01537
Haiku 4.5 $0.00004 $0.00768

Measured yesterday against content hash 1d0839b36197, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

engine-implementer 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.

.claude/skills/engine-implementer/SKILL.md · 232 lines

How it starts

The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engine Implementer (Orchestrator)

This is the orchestrator for the phase.rs implementation pipeline. It runs as a skill in the main thread so it can spawn agents for every step that benefits from fresh context (plan review, surgical implementation, implementation review). Do not turn this into an agent — agents cannot spawn sub-agents, which is what made earlier versions silently degrade.

Roles

Step Where it runs Why
1. Produce plan Spawned general-purpose agent invoking /engine-planner Fresh context = plan is shaped by the task, not by the conversation history that led here
2. Review plan Spawned general-purpose agent invoking /review-engine-plan Fresh context = honest architectural review, independent of the planner
3. Implement Spawned engine-implementation-executor agent Baseline measurement, surgical edits, and preparatory checks; never commits
4. Checkpoint + measure This thread, then a fresh measurement executor Orchestrator creates the candidate commit; isolated executor measures that immutable candidate
5. Complete verification This thread Verify the committed candidate, never an in-flight working tree
6. Review implementation Spawned general-purpose agent invoking /review-impl Independent review of the immutable base-to-candidate diff
7. Final acceptance This thread Accept only the exact reviewed checkpoint candidate

Runtimes without subagent spawning (contributor environments — Codex CLI, plain LLM sessions). The pipeline's value comes from context isolation between author and reviewer, not from the spawning mechanism. If your runtime cannot spawn agents, do NOT silently degrade to reviewing your own work in the same context — that is the failure mode this skill exists to prevent. Instead: run each step against a fresh context (new session/conversation per step when your runtime supports it), and for every review step hand the reviewer ONLY the artifact under review (the full plan, or the unified diff), the original task description, CLAUDE.md, the relevant skill (/review-engine-plan or /review-impl), and, in chartered runs, the charter, phase index, and deferral allowlist — never the conversation that produced it. If even that is impossible, say so explicitly in the final report and in the PR body under a "Validation Failures" heading; do not claim the review loop ran clean.

Read the full file on GitHub · 232 lines

Files

What ships with it

1 file 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.

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 · 232 lines · 43 tokens per session scan A 1d0839b36197

Subscribe to this mod's changes

engine-implementer is a skill published in the GitHub repository phase-rs/phase (259 stars, last pushed yesterday), licensed Apache-2.0. It adds 43 tokens to every session and 7,683 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 2026-08-30.

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