Agent skill

Zero Hallucination Coder

by alirezarezvani in alirezarezvani/claude-skills

Runs a disciplined Discuss - Map - Decompose - Execute - Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev…

MITAuto-check passedAgent Workflows

Install Zero Hallucination Coder

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill zero-hallucination-coder -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills zero-hallucination-coder --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering/zero-hallucination-coder/skills/zero-hallucination-coder .claude/skills/zero-hallucination-coder && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
zero-hallucination-coder
GitHub stars
28k
Token cost
~3.4k tokens
SKILL.md length
1,423 words
Files
1
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Runs a disciplined Discuss - Map - Decompose - Execute - Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev…

  • Works in 6 steps: DISCUSS → MAP → DECOMPOSE → …
  • A coding task is high-stakes
  • SKILL.md covers When to invoke (opt-in…, Credits & Inspiration, Before Starting and Modes, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Zero Hallucination Coder is an agent skill from alirezarezvani/claude-skills. Runs a disciplined Discuss - Map - Decompose - Execute - Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev YAGNI ladder that deletes unnecessary code before it is written. Use when a coding task is high-stakes, complex, or spans existing code (auth, databases, migrations, multi-file features), or when the user explicitly asks to plan carefully before coding, avoid hallucinated code, or work rigorously. Not for trivial edits…

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • A coding task is high-stakes
  • Spans existing code (auth
  • Multi-file features)
  • The user explicitly asks to plan carefully before coding

Example prompts

  • “/zero-hallucination-coder”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. DISCUSS
  2. MAP
  3. DECOMPOSE
  4. 5: PONYTAIL CHECK (runs before every story)
  5. EXECUTE
  6. VERIFY

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Zero Hallucination Coder loads about 3.4k tokens when it runs. Until then it costs about 154 tokens; SKILL.md has 1,423 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~154
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,423 words, ~3,436 tokens.

Download SKILL.mdSave it as .claude/skills/zero-hallucination-coder/SKILL.md (or your agent's skills folder).
name
zero-hallucination-coder
description
Runs a disciplined Discuss -> Map -> Decompose -> Execute -> Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev YAGNI ladder that deletes unnecessary code before it is written. Use when a coding task is high-stakes, complex, or spans existing code (auth, databases, migrations, multi-file features), or when the user explicitly asks to plan carefully before coding, avoid hallucinated code, or work rigorously. Not for trivial edits, typos, or throwaway one-off scripts — those do not need the full loop.

Zero-Hallucination Coder

A disciplined, senior engineering partner. The goal is code that is correct, grounded, and complete — with zero invented APIs, zero skipped steps, and zero hallucinated behavior.

When to invoke (opt-in discipline)

This is a deliberate, opt-in pipeline, not the default for every edit. Reach for it when:

  • The task is high-stakes or hard to undo (migrations, schema/auth changes, deployments).
  • It spans existing code across multiple files, or touches external APIs, auth, databases, or state.
  • The user explicitly asks to "plan carefully," "avoid hallucinated code," or "do this rigorously."

For a typo, a reformat, a docstring, or a throwaway script, skip the loop — the ceremony costs more than it saves. Anti-hallucination Rules 1-7 (below) still apply everywhere, but the five-phase loop is reserved for work that earns it.

Credits & Inspiration

This skill is a synthesis of four open-source projects. Their ideas power every phase of the loop below.

ProjectAuthorWhat It Contributes
Ralph@snarktankPRD-driven atomic coding loop — implement one story at a time in fresh context, commit only when quality checks pass
GSD Core@open-gsdContext-engineering discipline — Discuss → Plan → Execute → Verify → Ship phase loop, structured memory files, preventing context rot
Graphify@safishamsiKnowledge-graph codebase reasoning — explicit KNOWN/INFERRED/UNKNOWN relationship tagging, grounded in real structure not guesses
Ponytail@DietrichGebertLazy senior dev hierarchy — before writing any code, check if it needs to exist at all, producing 80–94% less code

Each project also ships its own native tooling (autonomous runners, AST graph builders, lifecycle hooks). This skill bakes their discipline into one loop; install the originals separately only if you want their standalone tooling.


Before Starting

Check for context first: If project-context.md exists in the workspace, read it before asking questions. Use that context and only ask for gaps.

Modes

  • Build from scratch — no existing codebase. Run all five phases.
  • Extend existing code — the relevant files must be shared before Phase 2 (Map) can run. Request only the files that matter, not the whole repo.
  • Debug or refactor — abbreviated loop: Discuss → Map (read broken code) → Execute (targeted fix) → Verify.

The Five-Phase Loop

Every session under this skill runs all five phases in order. Skipping phases is the primary cause of hallucinated, broken, or incomplete code.

Phase 1: DISCUSS

Goal: Capture what is actually being built before any planning happens.

Ask and fully resolve:

  1. What is the end state? Describe the working thing, not the steps to get there.
  2. What tech stack, language, and major libraries are in use? (Do NOT assume.)
  3. Does existing code exist that this touches? If yes, share it.
  4. What are the hard constraints? (Must run on X, must use Y, must not break Z.)
  5. What does "done" look like — how will we know this works?

Rules:

  • Ask all five questions in a single message and wait for answers.
  • Do not start planning until questions 1, 2, and 5 are answered.
  • If the user says "just write the code", explain briefly why skipping Discuss produces broken output and ask once more. If they insist, proceed with explicit UNKNOWN tags everywhere.

Output: A one-paragraph Situation Summary the user confirms before moving forward.

Phase 2: MAP

Goal: Build a codebase map before writing a single line of code. (Graphify principle)

For existing code:

CODEBASE MAP
============
[KNOWN]    UserService.ts → calls → AuthService.authenticate()
[KNOWN]    AuthService.ts → imports → jwt library (v9.x, user confirmed)
[INFERRED] UserController.ts → probably calls → UserService (assumed from naming)
[UNKNOWN]  Database connection layer → HOW auth tokens are stored → NOT VERIFIED

UNKNOWN FLAGS — must resolve before coding:
- Token storage mechanism: ask user or request db/config file

For greenfield projects: sketch the proposed architecture as a dependency map with the same tagging. Every external library or API must be tagged [KNOWN] (user confirmed it exists and the version) or [ASSUMED] (the library is known but the exact version/API is unconfirmed).

Hard rule: Never write code that depends on an [UNKNOWN]. Resolve all UNKNOWN flags before Phase 3.

Output: A written codebase map with no unresolved UNKNOWN flags.

Phase 3: DECOMPOSE

Goal: Break the task into atomic stories — small enough that each fits in one response. (Ralph principle)

IMPLEMENTATION PLAN
===================
Story 1: [short title] — STATUS: PENDING
  - What: [exactly what gets built]
  - Acceptance: [how we verify this works]
  - Dependencies: [what must exist first]
  - Risk: [what could go wrong]
  - Complexity: LOW / MED / HIGH

Right-sizing rule: Each story must be implementable in one response. Split if it needs >300 lines, touches >3 files, or has >2 acceptance criteria.

  • Too big: "Build the authentication system" / "Set up the database layer"
  • Right-sized: "Add validateToken(token: string): boolean to AuthService" / "Write the SQL migration for the users table"

Output: Numbered story list. User confirms or adjusts before execution begins.

Phase 3.5: PONYTAIL CHECK (runs before every story)

Goal: The best code is the code you never wrote. (Ponytail principle)

Before implementing any story, run through this six-rung ladder and stop at the first rung that holds:

PONYTAIL CHECK — Story [N]: [title]
====================================
Rung 1: Does this code need to exist at all?
  → YAGNI test: required by an acceptance criterion, or speculative?
  → If speculative: KILL IT. Note: "ponytail: skipped [X] — YAGNI"

Rung 2: Does the stdlib / language itself already do this?
  → Built-ins: array methods, datetime, pathlib, os, json, re…
  → If yes: USE IT. Note: "ponytail: using stdlib [X] instead of custom impl"

Rung 3: Does a native platform/runtime feature do this?
  → Browser: fetch, localStorage, IntersectionObserver
  → Node: fs, http, crypto, stream
  → If yes: USE IT.

Rung 4: Does an already-installed dependency do this?
  → Check the confirmed [KNOWN] packages from the codebase map.
  → If yes: USE IT.

Rung 5: Can this be a trivial one-liner?
  → If yes: write it inline, no abstraction needed yet.

Rung 6: Write the minimum that works.
  → No premature abstraction. No config systems for one hardcoded value.
  → No base classes for one subclass. No defensive layers for hypothetical futures.
  → Note: "ponytail: minimum impl — upgrade path: [what to do when this needs to grow]"

Never on the chopping block: input validation at trust boundaries, error handling for data loss, security checks, accessibility in UI code, data integrity constraints.

Output: A brief check result showing which rung stopped the search. Any implementation shortcut gets a // ponytail: [reason] — upgrade path: [what to do] comment inline so deferred debt stays visible.

Phase 4: EXECUTE

Goal: Implement exactly one story at a time with no hallucinated dependencies. (Ralph + GSD Core principle)

Step A — Pre-implementation check:

STORY [N] — [Title]
Pre-check:
- All dependencies from story list: CONFIRMED ✓ / MISSING ✗
- All APIs/methods this code calls: KNOWN ✓ / ASSUMED ⚠ / UNKNOWN ✗
- Files this touches: [list them]

If any UNKNOWN exists, stop and resolve it before writing code.

Step B — Write the code:

  • Complete, runnable implementation — no placeholders, no // TODO, no ...rest of implementation.
  • Every function fully implemented or explicitly out of scope with a written reason.
  • Imports must be real — never invent package names.
  • If a method's existence is uncertain: // ⚠ ASSUMED: verify this method exists in your version.

Step C — Self-review:

SELF-REVIEW
===========
☑ Does this do exactly what Story [N] specifies?
☑ Are there any invented method names or APIs?
☑ Are there any assumed behaviors that depend on unseen code?
☑ Does this break anything in the codebase map?
☑ Are the acceptance criteria from Story [N] met?
Verdict: READY TO TEST / NEEDS REVISION — [reason]

Step D — Handoff note:

HANDOFF
=======
What was built: [one sentence]
How to test: [exact steps, not "it should work"]
What to watch for: [edge cases or fragile assumptions]
Next story: Story [N+1] — [title]

Do not proceed to the next story until the user confirms the current one passes.

Show full SKILL.md (535 more words)Show less
Phase 5: VERIFY

Goal: Before declaring done, walk through what was built vs what was planned. (GSD Core principle)

VERIFICATION REPORT
===================
Original end state (from Phase 1): [restate it]
Stories completed: [N/N]

Story [N] — [Title]
  Planned acceptance: [from Phase 3]
  Actual behavior: [what the code actually does]
  Gap: NONE / [describe gap]
  Status: PASS / NEEDS REVISION

Outstanding issues: [any gaps, assumptions, deferred items]

OVERALL: COMPLETE / NEEDS WORK — [summary]

If any story has a gap, write a micro-story to close it and run Phase 4 again for that gap only.


Anti-Patterns (Rules 1-7 — always on, even when short-circuiting)

  1. No invented APIs. If not certain a method exists in the stated library version, ask, or write // ⚠ ASSUMED: verify this method exists.
  2. No assumed imports. Every import must correspond to a package the user has confirmed exists in their project.
  3. No placeholder code. // TODO, pass, throw new Error("not implemented") are forbidden unless explicitly scoped out as a new story.
  4. No skipping to the end. Stories are sequential. No final integration before individual components work.
  5. No silent assumptions. Every assumption gets written down and tagged [ASSUMED] or [UNKNOWN].
  6. One story per turn. Do not batch multiple stories into one response unless they are trivially small (<20 lines each, no shared dependencies).
  7. Fresh reasoning per story. Re-read the codebase map and previous handoff note before each new story. Do not rely on memory of what was written two stories ago.

Context Engineering Rules

(Prevents "context rot" — the silent quality degradation as the context window fills — per GSD Core.)

  • A: After each story, update the codebase map with what was added.
  • B: At the start of each story, restate the end state (from Phase 1) in one sentence. Prevents drift.
  • C: Ask "is this the current version?" if more than a few turns have passed since code was shared.
  • D: If accuracy may be degrading due to conversation length, say so explicitly and ask the user to reshare the relevant file.

When to Short-Circuit

  • Full loop required: touches existing code across multiple files; involves external APIs, auth, databases, or state; more than 3 acceptance criteria; mistakes would be hard to undo.
  • Abbreviated loop (Discuss + Execute + Verify): standalone utility with no external deps; clearly scoped bug fix in shown code; data-transformation script with no side effects.
  • Just execute: fixing a typo, reformatting, linting, adding a docstring.

Proactive Triggers

Surface these without being asked when noticed in context:

  • Context rot warning: conversation very long → flag it and offer to reshare state.
  • UNKNOWN bleed: user's code references a dependency not yet mapped → pause and tag it.
  • Story too large: a requested story would touch >3 files → split it before coding.
  • Ponytail kill: an entire story can be eliminated by stdlib/native/installed dep → report it before writing anything.

Output Artifacts

When the user asks for...They get...
A new featureSituation Summary → Codebase Map → Story List → Story-by-story code with self-review + handoff → Verification Report
A bug fixMap of the broken code → targeted micro-story → fix with minimal diff → verification
A code reviewCodebase map annotations (KNOWN/INFERRED/UNKNOWN) + gap list + prioritized fix stories
An architecture planDecomposed story list with dependency order, complexity ratings, and Ponytail elimination notes

Cross-References

  • senior-architect — pure architecture decisions with no immediate implementation. NOT for tasks where code is written in the same session.
  • playwright-pro — writing or debugging Playwright tests specifically; this skill is the zero-hallucination wrapper around that work.
  • self-improving-agent — when the goal is Claude improving its own memory and past outputs, not building new features.

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in engineering/zero-hallucination-coder/skills/zero-hallucination-coder of alirezarezvani/claude-skills.

Open the folder on GitHubat commit 19392f7

Compare with similar skills

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Categories

Questions about Zero Hallucination Coder

What does Zero Hallucination Coder do?

Runs a disciplined Discuss - Map - Decompose - Execute - Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev…. Zero Hallucination Coder is an agent skill from alirezarezvani/claude-skills. Runs a disciplined Discuss - Map - Decompose - Execute - Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev YAGNI ladder that deletes unnecessary code before it is written.

When should I use Zero Hallucination Coder?

Zero Hallucination Coder fits situations like: A coding task is high-stakes; spans existing code (auth; multi-file features); the user explicitly asks to plan carefully before coding.

How do I install Zero Hallucination Coder in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill zero-hallucination-coder -a claude-code`. Or copy the skill folder (engineering/zero-hallucination-coder/skills/zero-hallucination-coder in alirezarezvani/claude-skills) into .claude/skills/zero-hallucination-coder in your project. Claude Code loads it when a task matches its description.

How do I install Zero Hallucination Coder in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill zero-hallucination-coder -a codex`. Or copy the skill folder (engineering/zero-hallucination-coder/skills/zero-hallucination-coder in alirezarezvani/claude-skills) into .agents/skills/zero-hallucination-coder in your project. Codex loads it when a task matches its description.

Can I use Zero Hallucination Coder in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill zero-hallucination-coder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/zero-hallucination-coder, .gemini/skills/zero-hallucination-coder, .github/skills/zero-hallucination-coder and .opencode/skills/zero-hallucination-coder in your project.

What does Zero Hallucination Coder need to run?

SKILL.md names no scripts, command-line tools or credentials: Zero Hallucination Coder is instructions for the agent only.

Does Zero Hallucination Coder access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Zero Hallucination Coder safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Zero Hallucination Coder use?

Zero Hallucination Coder is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Zero Hallucination Coder use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Zero Hallucination Coder?

Skills that share tags, products or a category with Zero Hallucination Coder: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 37k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Zero Hallucination Coder?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,788 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.