full-output-enforcement

full-output-enforcement is a skill for Claude Code, Codex from rofid-c/codebase-analyzer-mcp. It costs 44 tokens per session (566 once invoked), scanned A, a copy of full-output-enforcement, MIT.

A skill that instructs an AI agent to produce complete code, avoid placeholders, and split large outputs cleanly when they exceed one response.

In plain words
What is it for?
Use it for tasks that require an exhaustive, unabridged code or text output.
Why use it?
It addresses incomplete generated code and missing sections caused by output truncation.

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/rofid-c/codebase-analyzer-mcp/full-output-enforcement
Any agent
npx skills add rofid-c/codebase-analyzer-mcp --skill full-output-enforcement
Clone the repo
git clone --depth 1 https://github.com/rofid-c/codebase-analyzer-mcp

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for full-output-enforcement

README.md
[![agentmods](https://agentmods.dev/badge/skills/rofid-c/codebase-analyzer-mcp/full-output-enforcement.svg)](https://agentmods.dev/skills/rofid-c/codebase-analyzer-mcp/full-output-enforcement)
Your own site
<a href="https://agentmods.dev/skills/rofid-c/codebase-analyzer-mcp/full-output-enforcement"><img src="https://agentmods.dev/badge/skills/rofid-c/codebase-analyzer-mcp/full-output-enforcement.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 566 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00044 $0.00566
Opus 5 $0.00022 $0.00283
Sonnet 5 $0.00009 $0.00113
Haiku 4.5 $0.00004 $0.00057

Measured 4d ago against content hash e5bf48b1ae56, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

full-output-enforcement 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 4d 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.

Origin

This is a copy

100% identical to full-output-enforcement — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/full-output-enforcement/SKILL.md · 50 lines

How it starts

The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Full-Output Enforcement

Baseline

Treat every task as production-critical. A partial output is a broken output. Do not optimize for brevity — optimize for completeness. If the user asks for a full file, deliver the full file. If the user asks for 5 components, deliver 5 components. No exceptions.

Banned Output Patterns

The following patterns are hard failures. Never produce them:

In code blocks: // ..., // rest of code, // implement here, // TODO, /* ... */, // similar to above, // continue pattern, // add more as needed, bare ... standing in for omitted code

In prose: "Let me know if you want me to continue", "I can provide more details if needed", "for brevity", "the rest follows the same pattern", "similarly for the remaining", "and so on" (when replacing actual content), "I'll leave that as an exercise"

Structural shortcuts: Outputting a skeleton when the request was for a full implementation. Showing the first and last section while skipping the middle. Replacing repeated logic with one example and a description. Describing what code should do instead of writing it.

Execution Process

  1. Scope — Read the full request. Count how many distinct deliverables are expected (files, functions, sections, answers). Lock that number.
  2. Build — Generate every deliverable completely. No partial drafts, no "you can extend this later."
  3. Cross-check — Before output, re-read the original request. Compare your deliverable count against the scope count. If anything is missing, add it before responding.

Handling Long Outputs

When a response approaches the token limit:

  • Do not compress remaining sections to squeeze them in.
  • Do not skip ahead to a conclusion.
  • Write at full quality up to a clean breakpoint (end of a function, end of a file, end of a section).
  • End with:
[PAUSED — X of Y complete. Send "continue" to resume from: next section name]

On "continue", pick up exactly where you stopped. No recap, no repetition.

Read the full file on GitHub · 50 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. 4d ago First seen · 50 lines · 44 tokens per session scan A e5bf48b1ae56

Subscribe to this mod's changes

full-output-enforcement is a skill published in the GitHub repository rofid-c/codebase-analyzer-mcp (0 stars, last pushed 4d ago), licensed MIT. It adds 44 tokens to every session and 566 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to full-output-enforcement, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens