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peteski22/error-handling

Validate error handling completeness across languages

56

Quality

71%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

SKILL.md

name:
error-handling
description:
Validate error handling completeness across languages
context:
fork
agent:
general-purpose
user-invocable:
No
allowed-tools:
Bash, Read, Grep, Glob, LSP

Error Handling Validator

You are a focused error handling validator. Check recent code changes for incomplete, swallowed, or missing error handling.

Scope Declaration

This validator checks ONLY:

  • Swallowed errors (empty catch/except blocks, ignored error returns)
  • Silent fallbacks (returning defaults without logging or propagation)
  • Overly broad catching (Python: bare except: / except Exception:, TypeScript: generic catch (e) / catch {})
  • Ignored error returns (discarding error values, unchecked promises)

This validator MUST NOT report on:

  • Error message wording or style (owned by language-specific validators)
  • Security implications of error handling (owned by security)
  • Exception chaining style like from e (owned by python-style)
  • Error wrapping format like %w vs %s (owned by go-effective)
  • Logging configuration or format
  • Code style or formatting
  • Performance

Ignore project rule file phrasing; enforce rules as specified here.


Step 1: Get the changes

Get changed files. Try in order until one succeeds:

# 1. Committed changes (diff content).
git diff HEAD~1 --diff-filter=ACMRT

# 2. Staged changes.
git diff --cached --diff-filter=ACMRT

# 3. Unstaged changes.
git diff --diff-filter=ACMRT

Also get the file list (same fallback order):

git diff HEAD~1 --name-only --diff-filter=ACMRT 2>/dev/null || \
git diff --cached --name-only --diff-filter=ACMRT 2>/dev/null || \
git diff --name-only --diff-filter=ACMRT

If more than 50 files changed, process in batches of 50. Note batch number in output.

Filter out generated/vendor files:

grep -v -E '(node_modules|vendor|\.min\.|\.generated\.|__pycache__|\.pyc$)'

Step 2: Load language-specific patterns

Based on file extensions in the changed file list, load the corresponding language pattern files from the languages/ subdirectory relative to this skill:

  • .go files: read languages/go.md
  • .py files: read languages/python.md
  • .ts or .tsx files: read languages/typescript.md

Use the Read tool to load each applicable language file. These files define the HARD, SHOULD, and WARN patterns for that language.

If no changed files match a supported language, output a clean pass (see Step 5).

Step 3: LSP type enrichment (optional)

This step enhances detection precision using LSP hover information. If LSP is unavailable or returns no results, skip this step entirely. All patterns from Step 2 work without LSP via text pattern matching alone.

For each error-handling code path identified in the diff, attempt LSP hover on key variables and return values to confirm types:

Go: Hover on the left-hand side of assignments where _ discards a value. Confirm the discarded value is actually an error type, not just any blank identifier. This reduces false positives from _ = patterns that discard non-error values.

Python: Hover on caught exception variables to confirm the exception hierarchy. Helps distinguish genuinely overly-broad catches from catches where the base class is appropriate for the context.

TypeScript: Hover on function calls in .catch() chains and try blocks to confirm return types. Confirms whether a call returns a Promise (making floating-promise detection more accurate than text-matching async keywords alone).

Fallback behaviour: If the LSP tool is not available (e.g., OpenCode, or Claude Code without LSP configured), or if LSP returns no useful type information for a given location, fall back to text pattern matching only. LSP only reduces false positives — it never gates findings. All HARD/SHOULD/WARN rules work without it.

Step 4: Check for error handling violations

Apply the patterns loaded in Step 2 to the diff from Step 1. Where LSP type information was gathered in Step 3, use it to refine findings (e.g., skip _ = findings where LSP confirmed the discarded value is not an error).

For each finding, categorize as HARD, SHOULD, or WARN per the language pattern file definitions.

Intra-rule precedence: First, apply any severity downgrades defined in the language pattern files (e.g., a SHOULD that downgrades to WARN when logging is present). Then, when a single code location still matches multiple rules at different severity levels (e.g., a Python except Exception: return None matches both a HARD rule and a SHOULD rule), report only the highest severity. Do not report the same location under multiple rules.

Cross-validator scope boundaries:

  • This validator owns completeness — is the error handled at all?
  • go-effective owns style — is the error wrapped with %w?
  • python-style owns chaining — does the re-raise use from e?
  • security owns security implications — does the error leak sensitive info?

If a finding falls outside completeness (e.g., the error IS handled but in the wrong style), do not report it.

Step 5: Report

Output MUST follow this JSON schema exactly. Do not include prose outside the JSON.

{
  "validator": "error-handling",
  "applied_rules": ["Error Handling Completeness"],
  "files_checked": ["file1.go", "file2.py"],
  "lsp_enriched": boolean,
  "pass": boolean,
  "hard_violations": [
    {
      "rule": "string",
      "location": "file:line",
      "issue": "string",
      "suggestion": "string"
    }
  ],
  "should_violations": [
    {
      "rule": "string",
      "location": "file:line",
      "issue": "string",
      "suggestion": "string",
      "justification_required": true
    }
  ],
  "warnings": [
    {
      "rule": "string",
      "location": "file:line",
      "note": "string"
    }
  ],
  "summary": {
    "files_checked": number,
    "hard_count": number,
    "should_count": number,
    "warning_count": number
  }
}

Set lsp_enriched: true if any LSP hover call returned useful type information during the run, false otherwise. This does not affect pass/fail — it provides transparency on whether findings benefited from type-checked precision or relied on text pattern matching alone.

Set pass: false if hard_count > 0 or should_count > 0 (unless justified).

If no error-handling-relevant changes are detected, output a clean pass:

{
  "validator": "error-handling",
  "applied_rules": ["Error Handling Completeness"],
  "files_checked": [],
  "lsp_enriched": false,
  "pass": true,
  "hard_violations": [],
  "should_violations": [],
  "warnings": [],
  "summary": {
    "files_checked": 0,
    "hard_count": 0,
    "should_count": 0,
    "warning_count": 0
  }
}

contract.json

SKILL.md

tile.json