What's the difference between ThumbGate and SigmaShake?

Both gate an AI coding agent's tool calls before they run, across Claude Code, Cursor, Codex and others. The core difference is where the rules come from. SigmaShake gives you a hub of ready-made signed community rulesets and a three-tier enforcement model (DENY / ASK / FORCE-substitute-a-safe-command). ThumbGate generates the rule from your own correction: one thumbs-down on a mistake auto-writes the rule that blocks that exact mistake from then on, synced across your machines and team. SigmaShake is the broader, more mature catalog; ThumbGate is the learning loop for the mistakes no catalog has a rule for yet.

Is ThumbGate a good SigmaShake alternative?

It depends what you're optimizing for. If you want a large library of ready-made signed rules and the ability to auto-substitute a safe command instead of just blocking, SigmaShake is genuinely strong and we won't pretend otherwise. If you keep hitting team-specific or codebase-specific mistakes that no generic ruleset covers, ThumbGate's edge is that it learns those rules from your thumbs-down instead of asking you to author or find them. Many teams could run both.

Can ThumbGate substitute a safe command like SigmaShake's FORCE mode?

Not today. SigmaShake's FORCE tier rewrites a dangerous command into a safe equivalent before it runs — a real capability ThumbGate doesn't yet match. ThumbGate's enforcement blocks the call and returns a structured error plus a path back to the spec; it does not auto-rewrite the command. If safe-command substitution is a hard requirement, SigmaShake is ahead here.

ThumbGate vs SigmaShake (and APort, and agent-guardrails)

For developers and teams choosing a pre-action gate for their AI coding agents

TL;DR: Four tools gate an AI coding agent before it acts. SigmaShake is the most polished: a hub of ready-made signed rulesets, three-tier DENY/ASK/FORCE enforcement (including auto-substituting a safe command), a desktop app, and a tamper-evident audit log. ThumbGate's one differentiator is the learning loop — a single thumbs-down auto-writes the rule that blocks that exact mistake forever, synced across machines and team, instead of asking you to find or author one. APort is the org-identity layer (agent "passports," central policy). agent-guardrails is a free MIT starting point. We're honest below about where SigmaShake is ahead.

The shared category

All four start from the same fact: prompt-level rules in CLAUDE.md or .cursorrules are suggestions the model can ignore under context pressure. To actually stop a force-push to main or a DROP TABLE, you need a gate that fires before the tool call executes — not a reviewer after the PR, not a git revert after the damage. ThumbGate, SigmaShake, and agent-guardrails all hook the PreToolUse boundary. APort sits one layer up, as an identity/authorization layer for organizations.

This page is not a hit piece. SigmaShake in particular is well-built software with a real lead on catalog breadth and enforcement modes. We'll tell you where it wins and where ThumbGate's learning loop is the better fit.

Feature matrix

Capability	ThumbGate	SigmaShake	APort	agent-guardrails
Pre-action gating (blocks before execution)	Yes — PreToolUse hooks	Yes — PreToolUse	Authz layer, not a tool-call gate	Yes — PreToolUse hooks
Learns rules from your corrections	Yes — one thumbs-down auto-writes the rule	No — rules installed or authored	No — policy authored	No — hand-written deny rules
Pre-built ruleset library	Domain skill packs (Stripe, Railway, DB migrations)	Large signed community ruleset hub	N/A	Built-in deny rules (terraform/db/k8s/cloud/git)
Enforcement modes	Block + structured error (no auto-substitute)	DENY / ASK / FORCE (safe-command substitute)	Allow/deny by scoped permission	Deny / ask
Multi-agent support	Claude Code, Cursor, Codex, Gemini, Amp, Cline, OpenCode	Claude Code, Cursor, Codex, Copilot, Gemini	Claude, LangChain, CrewAI, Cursor	Claude Code (settings.json hooks)
Team / cross-machine sync of learned rules	Yes — hosted sync (Pro)	Local-first; optional cloud	Yes — central org policy	No
Org identity / agent permissions	Not the focus	Local rulesets, not identity	Yes — agent "passport" + scoped perms	No
License / source	MIT core + hosted commercial layer	Commercial, closed-source	Commercial	Free, MIT
Pricing	Free tier; Pro $19/mo or $149/yr	Commercial paid tier (see their site)	No public pricing (design-partner)	Free
Maturity	Newer; learning loop is the bet	Polished, broad catalog	Early / design-partner stage	Minimal adoption

Where SigmaShake is genuinely ahead

Saying this plainly builds more trust than pretending otherwise:

FORCE-substitution. SigmaShake can rewrite a dangerous command into a safe equivalent before it runs. ThumbGate blocks and explains; it doesn't auto-rewrite. If you want the gate to fix the command rather than stop it, SigmaShake wins.
A large signed ruleset hub out of the box. For common, well-known footguns, SigmaShake means you're protected on install with zero authoring. ThumbGate ships a handful of domain skill packs and expects to learn the rest from your corrections — great for novel mistakes, slower for day-one coverage of the obvious ones.
Maturity and polish. Desktop app, tamper-evident audit log, low-latency daemon, broad agent coverage including Copilot. SigmaShake is further along as a product.

Where ThumbGate is the better fit

The mistakes no catalog has a rule for. Every team has codebase-specific footguns ("never edit the generated client," "this repo deploys from release not main"). No community hub ships those. ThumbGate writes the rule the first time you thumbs-down the mistake.
Zero rule-authoring overhead. SigmaShake and agent-guardrails both ask you to install or write rules. ThumbGate's primary input is a thumbs-down — the correction is the rule authoring.
MIT core. The CLI and hook layer are MIT; the hosted sync is the paid part. SigmaShake and APort are closed-source.
Learned rules sync across the team. One engineer's thumbs-down becomes everyone's prevention rule.

And APort and agent-guardrails?

APort isn't really a head-to-head. It's an organizational authorization layer — agent "passports," scoped permissions, central policy and audit across Claude, LangChain, CrewAI, and Cursor. It positions as an additional authz layer for orgs and is at design-partner stage. If your problem is "which agents in my org are allowed to do what," APort solves a different problem than a tool-call gate. You could run APort for identity and ThumbGate for behavior.

roboticforce/agent-guardrails is a free, MIT set of hand-written deny rules plus PreToolUse hooks for terraform/db/k8s/cloud/git. A fine zero-cost starting point. No dashboard, audit, team management, or learning — if you outgrow a static deny list, that's the moment to look at ThumbGate or SigmaShake.

When to pick which

Pick SigmaShake if

You want day-one coverage from a large library of ready-made rules
Safe-command substitution (FORCE) is a requirement, not a nice-to-have
You want a mature desktop app and a tamper-evident audit log now
Closed-source commercial software is acceptable

Pick ThumbGate if

Your pain is repeat, team-specific mistakes no generic ruleset covers
You'd rather thumbs-down a mistake than hunt for or author a rule
You want learned rules to sync across machines and teammates
You want an MIT-licensed core you can read and embed

Honest framing: SigmaShake is the broader, more polished catalog-and-enforcement product today. ThumbGate's bet is narrower and sharper — the gate that learns the rule from your correction. They overlap, but optimize for different things, and running both is reasonable.

Adoption in two minutes (ThumbGate)

Install: npx thumbgate init — detects your agent, wires PreToolUse hooks, no workflow change.
Thumbs-down when the agent is wrong: a correction with context becomes a structured failure record.
The rule writes itself: ThumbGate auto-promotes a prevention rule from the correction.
Next time, it's blocked: the PreToolUse hook intercepts the call before it runs and points the agent back to the spec.

Tired of correcting the same mistake twice?

SigmaShake gives you a catalog. ThumbGate writes the rule from your thumbs-down. Free tier, MIT core, two-minute install.

$ npx thumbgate init

ThumbGate vs SigmaShake (and APort, and agent-guardrails)

The shared category

Feature matrix

Where SigmaShake is genuinely ahead

Where ThumbGate is the better fit

And APort and agent-guardrails?

When to pick which

Pick SigmaShake if

Pick ThumbGate if

Adoption in two minutes (ThumbGate)

Tired of correcting the same mistake twice?

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