Review And Fix — Incan Compiler

SkillDev tools

Run the Incan review/fix loop end to end: review, fix actionable findings, and review again until clean or blocked. Use when the user wants an autonomous review-and-repair pass or says /review-and-fix.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Review And Fix — Incan Compiler skill

What this skill tells your AI

The instructions your AI receives, as published by encero-systems/incan in .agents/skills/review-and-fix/SKILL.md and read by ahel’s review.

Purpose

/review-and-fix is the user-facing entry point for autonomous review plus repair.

The user should not need to choose between the simple reviewer and the orchestrated reviewer. This skill decides that itself from the current worktree.

Under the hood it chooses one of two paths:

  • small/local scope: /loop /review /fix
  • broad/multi-surface scope: review-orchestrate -> /fix -> final review pass

/loop still owns repetition and stopping conditions for the small/local path. For broad scopes, this skill owns the high-level routing and uses the persistent report at .agents/state/review-report.md.

Workflow

  1. Inspect the current dirty worktree before choosing a path.
  2. Choose the small/local path when the change is narrow enough for one honest reviewer, for example:
    • a small number of touched files,
    • one main subsystem,
    • code-only or docs-only,
    • no evidence of cross-cutting code/docs/tests/RFC churn.
  3. Choose the broad/multi-surface path when any of the following are true:
    • multiple subsystems are touched,
    • both code and user-facing docs moved,
    • tests, docs, and implementation all changed,
    • the worktree is large enough that one reviewer is likely to skip surfaces,
    • the user explicitly wants subagents or delegated review.
  4. For the small/local path:
    • invoke /loop with /review as detector and /fix as repair skill,
    • let /loop repeat until clean or legitimately blocked.
  5. For the broad/multi-surface path:
    • run review-orchestrate,
    • consume the merged findings with /fix,
    • then run a final review pass appropriate to the remaining scope.
  6. Treat .agents/state/review-report.md as a live structured artifact, not a final prose summary.
  7. For orchestrated runs, treat slice reports as the primary evidence and the canonical report as a thin merged findings index. Preserve findings by default; do not over-prune them during merge.
  8. Each new /review-and-fix invocation starts with a fresh report scaffold. Do not reuse an older run's findings or activity log.

Routing rule

The default user expectation should be simple:

  • users ask for /review-and-fix
  • this skill decides whether the work is small or broad
  • the user does not need to manually choose /review vs review-orchestrate

If the scope is borderline, prefer the broader review path. The cost of one wider first pass is lower than repeated serial misses and reruns.

Verification expectations

The repair pass should aim to leave the worktree in a strong verified state:

  • make fmt
  • narrow relevant checks
  • cargo run -p incan_core --bin generate_lang_reference when language registries, the reference generator, or workspaces/docs-site/docs/language/reference/language.md changed; inspect and commit any resulting generated diff
  • make pre-commit

If the broad gate fails for unrelated environmental reasons, report that explicitly as residual risk instead of pretending the loop is clean.

Output format

Produce a short summary:

## Review And Fix — <subject / branch>

### Chosen path
<small/local review loop or broad orchestrated review>

### Review findings
<high-signal findings from the chosen review path>

### Fixes applied
<what changed>

### Final review state
<clean / blocked / residual risk>

### Verification
<commands and outcomes>

Signals

GitHub stars
228
Forks
70
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
review-and-fix
Source
github.com/encero-systems/incan