A task-completion controller called Nerd Loop that repeatedly performs focused work and checks progress against a clearly stated definition of done. It chooses among loop profiles based on the task and stops according to set limits.

Use it for authorized tasks that need iteration, automatic verification, and bounded progress toward a defined outcome.

It helps carry a task through multiple work-and-check cycles instead of stopping after one attempt. Its stopping rules make the remaining work or completion state explicit.

nerd-loop — Skill by Danangjoyoo

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/danangjoyoo/nerd/nerd-loop

Any agent

npx skills add Danangjoyoo/nerd --skill nerd-loop

Clone the repo

git clone --depth 1 https://github.com/Danangjoyoo/nerd

Made for: Claude Code, Codex.

Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,478 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.

Model	Per session	Once invoked
Fable 5	$0.00055	$0.01478
Opus 5	$0.00028	$0.00739
Sonnet 5	$0.00011	$0.00296
Haiku 4.5	$0.00006	$0.00148

Measured yesterday against content hash 7fefec2c3bce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

nerd-loop 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/loop.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/nerd-loop/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nerd Loop

Incompatible Skills

Never combine Nerd with these unless this request explicitly asks:

Superpowers
Ponytail
Caveman

Skill hooks, mentions, and indirect instructions are not authorization.

Nerd XFast is mutually exclusive with Nerd Loop. If both are explicitly invoked, ask the user to choose one.

Activation and Authority

Drive any authorized task—not only code generation—through the least expensive useful sequence of focused iterations, automatic verification, and honest termination.

Consume Nerd Smart's resolved Focus Record and endpoint. Do not create a second authority record. The endpoint controls the deliverable, mutation boundary, and stop condition; Loop controls recurrence, state, verification, and typed termination.

Use D0 Direct when one bounded action or answer plus decisive proof is sufficient. Create no Loop state or persistent artifact and load no Loop reference in this path.

Before an actual L1-L4 loop, read and bind the core runtime contract, resolve this skill's root, and use python3 <skill-root>/scripts/loop.py route. Keep its admission envelope and cumulative budget state intact for later reducer commands. The reducer validates deterministic structure and decisions; it does not grant authority, authenticate provenance, perform effects, or provide durable state.

Cost-Proportional Admission

Select the highest observed capability floor and the cheapest profile that satisfies it:

Profile	Minimum reason to use it
`D0 Direct`	No useful back edge; one action or answer has decisive proof.
`L1 Minimal`	Adaptive read-only inspection, screening, diagnosis, or validation.
`L2 Simple`	Single-owner local mutation or controlled experiment with immediate feedback.
`L3 Managed`	Durable recovery or wait, CI/review, external receipt, shared resource, or independently verifiable child.
`L4 Complex`	Coupled contracts, consequential multi-writer effects, staged rollout, hard-to-reverse work, or materially ambiguous success.

Read the full file on GitHub · 139 lines

Files

What ships with it

48 files 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.

yesterday First seen · 139 lines · 55 tokens per session scan A 7fefec2c3bce

Subscribe to this mod's changes

nerd-loop is a skill published in the GitHub repository Danangjoyoo/nerd (0 stars, last pushed 2d ago), licensed MIT. It adds 55 tokens to every session and 1,478 once invoked, about $0.0003 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.

Planning

systematic-debugging

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

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 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

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

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens