skills/gateguard/SKILL.md
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.
npx skillsauth add affaan-m/everything-claude-code gateguardInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
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.
Two independent A/B tests, identical agents, same task:
| Task | Gated | Ungated | Gap | | --- | --- | --- | --- | | Analytics module | 8.0/10 | 6.5/10 | +1.5 | | Webhook validator | 10.0/10 | 7.0/10 | +3.0 | | Average | 9.0 | 6.75 | +2.25 |
Both agents produce code that runs and passes tests. The difference is design depth.
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 (search the tree — Glob/Grep, or find/grep via Bash)
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
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 (search the tree — Glob/Grep, or find/grep via Bash)
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
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
1. The current user request in one sentence
2. What this specific command verifies or produces
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.
pip install gateguard-ai
gateguard init
This adds .gateguard.yml for per-project configuration (custom messages, ignore paths, gate toggles).
%Y/%m/%d %H:%M. Checking data structure (with redacted values) prevents this entire class of bugs..gateguard.yml to ignore paths like .venv/, node_modules/, .git/.safety-guard — Runtime safety checks (complementary, not overlapping)code-reviewer — Post-edit review (GateGuard is pre-edit investigation)development
Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
development
Use when multiple consumers and providers must evolve an API or event schema without field drift, integration surprises, or one side silently redefining the interface.
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Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, or validate GPU nodes.
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Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.