> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/derHaken/SuperAntigravity/llms.txt
> Use this file to discover all available pages before exploring further.
# Confidence check
> Self-assessment gating before implementation — verifies you have enough understanding, context, and a clear approach before writing any code
The confidence-check skill prevents wasted effort from implementing with wrong assumptions. It runs a scored self-assessment across three dimensions and gates implementation on the result.
## When this skill fires
The skill description reads: *"Use before implementing a feature or making significant changes to verify you have enough context and understanding to proceed — prevents wasted effort from proceeding with wrong assumptions."*
Specific triggers:
* Before starting implementation of a feature
* When requirements feel ambiguous
* After reading existing code you're about to modify
* When you're unsure about a technical approach
## What it does
The skill scores three dimensions — Understanding, Context, and Approach — on a 0–10 scale. The total score determines whether to proceed, fill gaps first, or stop and discuss. An anti-gaming protocol prevents inflated scores: any dimension scored 8 or higher requires specific named evidence.
## How it works
### The three dimensions
**Understanding (0–10)**
* Do you understand what this is supposed to do?
* Do you understand why it needs to exist?
* Do you understand who uses it and how?
**Context (0–10)**
* Do you know which files you need to touch?
* Do you understand the existing code patterns you're building on?
* Do you know the data flow end-to-end?
**Approach (0–10)**
* Do you know which approach you'll take and why?
* Have you considered at least one alternative?
* Do you know how to test this?
### Anti-gaming protocol
For any dimension scored 8 or higher, you must write one specific piece of evidence naming a concrete artifact — a file, a line range, a function name, a specific behavior you observed. General statements do not count. If you cannot name specific evidence for a dimension scored 8+, the maximum score for that dimension is 6.
Valid evidence examples:
* "Context: 9/10 — I have read `auth.js:45-120` and understand the JWT validation flow, including how the middleware chain passes the decoded token to route handlers."
* "Understanding: 8/10 — The requirement says 'users can reset their password via email.' I know it means: generate a one-time token, email a reset link, validate the token on return, and expire it after 1 hour per the spec in JIRA-442."
Invalid evidence (too vague):
* "Context: 9/10 — I understand the codebase well."
* "Understanding: 8/10 — The requirement is clear."
### Scoring thresholds
| Score | Action |
| -------- | ------------------------------------------------------------------------ |
| 27–30 | Proceed with implementation |
| 20–26 | Fill gaps before starting — identify and resolve unclear items |
| Below 20 | Stop — load brainstorming skill or discuss with the user before any code |
### External validation at 20–26
When total score is in the 20–26 range, state your understanding out loud in one paragraph — what you are about to build, why, and how. Be specific. If the user does not correct it within their next response, proceed. If they do correct it, re-run the check from the beginning with the updated understanding.
### Context change handling
If your confidence drops below 20 mid-implementation:
**Stop immediately. Do not continue writing code.**
Announce: "Confidence has dropped to \[X]/30 due to \[specific reason]. Pausing implementation to \[specific gap-filling action]."
Then execute the gap-filling action. Do not resume until confidence returns to 20+ (with external validation) or 27+ for autonomous continuation.
### What to do with low scores
**Low on Understanding:** Restate the requirement in your own words and ask the user to confirm. Do not assume you understood.
**Low on Context:** Read the relevant files before proceeding. Do not write code that touches files you have not read. Use the `deep-research` skill for external unknowns.
**Low on Approach:** Load the `architecture-design` skill. Explore 2–3 options before committing to one.
## Example scenario
You're about to implement a password reset endpoint.
**Understanding: 8/10** — Evidence: "I know the endpoint needs to: accept an email address, generate a time-limited reset token, send a reset link, validate the token on return, and allow the user to set a new password. Gap: I don't know whether the token should be single-use."
**Context: 6/10** — Evidence: "I have read `user.model.js` and understand the User schema. I have not yet read the email service. I can see it referenced in `order.controller.js` but don't know its interface."
**Approach: 7/10** — Evidence: "I will use `crypto.randomBytes(32)` for token generation, store the SHA-256 hash in a `password_reset_tokens` table with an `expires_at` column. Gap: email dispatch step is uncertain."
**Total: 21/30 — Fill gaps before starting.**
Gaps:
1. Read the email service implementation
2. Confirm with user: single-use tokens?
State understanding and wait for confirmation before proceeding.
## Related skills
Fills the Context gap when external unknowns (third-party APIs, library behavior) are the blocker.
Fills the Approach gap when the technical path is unclear.
Required when total score falls below 20 — indicates the feature needs design before implementation.