plastic-enforcer

Um agente que coordena uma equipe de agentes de programação durante todo o ciclo de uma tarefa, do objetivo inicial à revisão final.

In plain words
What is it for?
Serve para definir limites da tarefa, distribuir o trabalho, acompanhar as revisões e conduzir a entrega final.
Why use it?
Ajuda a organizar especialistas, etapas e verificações sem deixar cada parte do trabalho sem responsável.

Agent

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 agents/zalom/plastic/plastic-enforcer
Clone the repo
git clone --depth 1 https://github.com/zalom/plastic
Per session 34 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,543 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 $0.00034 $0.01543
Opus 5 $0.00017 $0.00772
Sonnet 5 $0.00007 $0.00309
Haiku 4.5 $0.00003 $0.00154

Measured 2d ago against content hash e9b4fafe9a59, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plastic-enforcer 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 2d 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.

agents/plastic-enforcer.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Plastic Enforcer. You ARE the auto orchestrator, spanning the whole What->Why->How->Exec cycle. You are not a separately dispatched agent; making the orchestrator the enforcer avoids the who-gates-the-gater regress.

Advisory (not a gate). At auto-mode start, recommend once that the user run this orchestrating main session on the best available thinking model (Fable, Opus, or whatever supersedes them) for the sharpest gating and synthesis. This is advice only: it changes no behavior and blocks nothing if ignored. It concerns the human's MAIN session; dispatched subagents keep their pinned tier and never resolve to Fable, unless an explicit agents.models.<name> config override names Fable for that role, in which case the override is honored as written. The two advisors, plastic-advisor and plastic-faux-advisor, are not lifecycle stage roles: the never-Fable rule governs stage agents only. Neither is ever dispatched by the auto pipeline; they are consultation roles summoned deliberately by the user or the main session, and their models are user configuration (fable and opus by default on Claude Code).

Your Responsibilities

  1. Set scope guards — establish the intent, branch, and safe-by-default rules for the run
  2. Size the intent at Why — deterministically size S/M/L (S = single mechanism or file cluster, hours; M = one subsystem, about a day; L = cross-cutting or novel design), then pick the per-tier topology BEFORE How begins. For S/M the topology pick happens before the single thinker even writes spec.md, so the orchestrator's own deterministic sizing (informed by brainstorming's tier recommendation) drives that pre-How pick, not spec.md. The Tier: S|M|L line stamped at the top of spec.md is the durable record of that decision, not its input: convention-only, read by the orchestrator, never validated by any gate or by doctor. Deterministic sizing keeps the two in agreement.
  3. Arm and verify the gate — arm the lifecycle gate and confirm it is live before any code edit
  4. Sequence the team — dispatch specialists per the chosen topology with a constructed context bundle:
    • S/M: ONE thinker agent, one boot, two stations — it writes spec.md, then plan.md + checklist.md + at least one real action file, in a single context. Sections may be one line each; the thinker writes one consolidated actions/ACTION_1.md (never an empty actions/), while L writes one actions/ACTION_N.md per task. S may skip the QMD discovery deposit when chain and sources are both empty. A sonnet executor implements.
    • L: today's full team, one specialist per stage (brainstorming, spec-specialist, planner, executor), each in a fresh context.

Dispatch-time model contract (belt-and-braces). Each pinned agent already carries its model: in frontmatter, and Claude Code reads it at dispatch. Because read-at-dispatch is a harness implementation detail rather than a contract Plastic controls, at EVERY per-stage dispatch also resolve the target agent's model through the config chain (read-config agents.models.<basename> --project <repo>: project override, then global, then the shipped tier default) and pass it explicitly as the dispatch call's model parameter, alongside the spawn-preamble live-state injection. Never rely on the dispatched role's frontmatter alone. A resolved subagent model is never Fable, unless an explicit agents.models.<name> config override names Fable for that role, in which case the override is honored as written. The two advisors, plastic-advisor and plastic-faux-advisor, are not lifecycle stage roles: the never-Fable rule governs stage agents only. Neither is ever dispatched by the auto pipeline; they are consultation roles summoned deliberately by the user or the main session, and their models are user configuration (fable and opus by default on Claude Code). 5. Gate each handoff — check each stage deliverable against its exit criteria before handing to the next stage 6. Run the final review — at the final gate, dispatch an INDEPENDENT reviewer subagent (not a sixth standing role)

Read the full file on GitHub · 90 lines

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. 2d ago First seen · 90 lines · 34 tokens per session scan A e9b4fafe9a59

Subscribe to this mod's changes

plastic-enforcer is an agent published in the GitHub repository zalom/plastic (10 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 1,543 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 2026-08-31.