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Audit score 70

gateguard

affaan-m/everything-claude-code

Fact-forcing gate that blocks edits and demands concrete investigation before allowing code changes.

What is gateguard?

GateGuard is a PreToolUse hook that forces Claude to investigate files, schemas, and dependencies before editing, writing, or running destructive bash commands. Use it on codebases where edits affect multiple modules or where data schemas must be understood to avoid bugs.

  • Blocks first Edit/Write/Bash attempt and demands concrete facts (imports, schemas, user instruction) before allowing retry
  • Handles MultiEdit by gating each file individually
  • Distinguishes between destructive bash (every time) and routine bash (once per session) to avoid slowdown
  • Reduces output quality variance by +2.25 points on average vs. ungated agents
  • Prevents common bugs like incorrect date format assumptions by forcing data schema inspection

How to install gateguard

npx skills add https://github.com/affaan-m/everything-claude-code --skill gateguard
Prerequisites
  • Node.js environment for hook installation, or Python 3.7+ for full package install
  • Access to grep, glob, and file read operations in your codebase
Claude Code
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How to use gateguard

  1. 1.Enable the GateGuard hook via hooks.json in your project, or run `pip install gateguard-ai && gateguard init` for full package
  2. 2.Attempt an edit, write, or destructive bash command; GateGuard will block it and list required facts
  3. 3.Gather the facts it demands: list imports/dependents, show data schemas (redacted), confirm user instruction
  4. 4.Retry the same action; GateGuard allows it after facts are presented
  5. 5.Optionally customize gate behavior via .gateguard.yml for your project's conventions and ignored paths

Use cases

Good for
  • Editing files that are imported by multiple modules across a codebase
  • Creating new files when unclear if existing code already serves that purpose
  • Modifying data processing logic without knowing the actual field names or date formats in use
  • Running destructive commands like rm -rf or git reset --hard
  • Working on analytics or webhook validation modules where design depth matters
Who it's for
  • Teams where AI-generated code must match existing patterns and conventions
  • Projects with data files that have specific schemas or formats
  • Developers working on multi-module codebases where side effects are common
  • Anyone frustrated with AI agents guessing instead of investigating

gateguard FAQ

Why does GateGuard block my edit if I'm confident it's correct?

Self-evaluation doesn't work experimentally—asking 'are you sure?' always gets 'yes.' The investigation itself creates awareness that changes output quality. Let it fire naturally.

Does GateGuard slow down every bash command?

No. Routine bash commands are gated once per session. Only destructive commands (rm -rf, git reset --hard, drop table) are gated every time.

Can I disable GateGuard for setup or repair work?

Yes. Start your session with `ECC_GATEGUARD=off` or use `ECC_DISABLED_HOOKS` for hook-level control.

What if GateGuard keeps asking for the same facts?

After the first 3 full denials per session (configurable), later denials are condensed to a single line to avoid context window bloat. Retrying after presenting facts never re-triggers the gate.

How is GateGuard different from code review?

GateGuard is pre-edit investigation that forces fact-gathering before changes are made. Code review happens after. They are complementary.

Full instructions (SKILL.md)

Source of truth, from affaan-m/everything-claude-code.


name: gateguard description: Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents. metadata: origin: community

GateGuard — Fact-Forcing Pre-Action Gate

A PreToolUse hook that forces Claude to investigate before editing. Instead of self-evaluation ("are you sure?"), it demands concrete facts. The act of investigation creates awareness that self-evaluation never did.

When to Activate

  • Working on any codebase where file edits affect multiple modules
  • Projects with data files that have specific schemas or date formats
  • Teams where AI-generated code must match existing patterns
  • Any workflow where Claude tends to guess instead of investigating

Core Concept

LLM self-evaluation doesn't work. Ask "did you violate any policies?" and the answer is always "no." This is verified experimentally.

But asking "list every file that imports this module" forces the LLM to run Grep and Read. The investigation itself creates context that changes the output.

Three-stage gate:

1. DENY  — block the first Edit/Write/Bash attempt
2. FORCE — tell the model exactly which facts to gather
3. ALLOW — permit retry after facts are presented

No competitor does all three. Most stop at deny.

Evidence

Two independent A/B tests, identical agents, same task:

TaskGatedUngatedGap
Analytics module8.0/106.5/10+1.5
Webhook validator10.0/107.0/10+3.0
Average9.06.75+2.25

Both agents produce code that runs and passes tests. The difference is design depth.

Gate Types

Edit / MultiEdit Gate (first edit per file)

MultiEdit is handled identically — each file in the batch is gated individually.

Before editing {file_path}, present these facts:

1. List ALL files that import/require this file (use Grep)
2. List the public functions/classes affected by this change
3. If this file reads/writes data files, show field names, structure,
   and date format (use redacted or synthetic values, not raw production data)
4. Quote the user's current instruction verbatim

Write Gate (first new file creation)

Before creating {file_path}, present these facts:

1. Name the file(s) and line(s) that will call this new file
2. Confirm no existing file serves the same purpose (use Glob)
3. If this file reads/writes data files, show field names, structure,
   and date format (use redacted or synthetic values, not raw production data)
4. Quote the user's current instruction verbatim

Destructive Bash Gate (every destructive command)

Triggers on: rm -rf, git reset --hard, git push --force, drop table, etc.

1. List all files/data this command will modify or delete
2. Write a one-line rollback procedure
3. Quote the user's current instruction verbatim

Routine Bash Gate (once per session)

1. The current user request in one sentence
2. What this specific command verifies or produces

Quick Start

Option A: Use the ECC hook (zero install)

The hook at scripts/hooks/gateguard-fact-force.js is included in this plugin. Enable it via hooks.json.

If GateGuard blocks setup or repair work, start the session with ECC_GATEGUARD=off. For hook-level control, keep using ECC_DISABLED_HOOKS with the GateGuard hook ID.

In long sessions, only the first GATEGUARD_FACT_FORCE_FULL_DENIALS fact-force denials (default 3) emit the full four-fact block; later denials are condensed to a single line carrying the denial ordinal, so near-identical blocks cannot accumulate in the context window and amplify model repetition loops (#2142). Retrying the same file or command after presenting facts never re-triggers the gate.

Option B: Full package with config

pip install gateguard-ai
gateguard init

This adds .gateguard.yml for per-project configuration (custom messages, ignore paths, gate toggles).

Anti-Patterns

  • Don't use self-evaluation instead. "Are you sure?" always gets "yes." This is experimentally verified.
  • Don't skip the data schema check. Both A/B test agents assumed ISO-8601 dates when real data used %Y/%m/%d %H:%M. Checking data structure (with redacted values) prevents this entire class of bugs.
  • Don't gate every single Bash command. Routine bash gates once per session. Destructive bash gates every time. This balance avoids slowdown while catching real risks.

Best Practices

  • Let the gate fire naturally. Don't try to pre-answer the gate questions — the investigation itself is what improves quality.
  • Customize gate messages for your domain. If your project has specific conventions, add them to the gate prompts.
  • Use .gateguard.yml to ignore paths like .venv/, node_modules/, .git/.

Related Skills

  • safety-guard — Runtime safety checks (complementary, not overlapping)
  • code-reviewer — Post-edit review (GateGuard is pre-edit investigation)