error-handling

A set of rules for handling errors and recovery in software. It covers explicit errors, adding context when errors cross boundaries, classifying failures, retries, circuit breakers, and safe logging.

In plain words
What is it for?
Use it when building exception handling, retry logic, circuit breakers, error messages, or structured logs that avoid exposing sensitive data.
Why use it?
It prevents failures from being silently ignored and helps systems recover in ways suited to the type of error.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/andr-ca/agentharness/error-handling
Clone the repo
git clone --depth 1 https://github.com/andr-ca/agentharness

Made for: Cursor.

Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,338 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00032 $0.01338
Opus 5 $0.00016 $0.00669
Sonnet 5 $0.00006 $0.00268
Haiku 4.5 $0.00003 $0.00134

Measured yesterday against content hash 1d78ade28f32, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

error-handling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/error-handling.mdc · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Error Handling & Recovery

Structured approaches to errors, recovery, and observability. Never silently hide errors.

Core Patterns

1. Explicit Errors (Always)

Return errors as values or raise them; never ignore them.

# ✅ Good: Explicit handling
try:
    user = parse_user_data(raw)
except json.JSONDecodeError as e:
    # Never log the raw payload — it can carry passwords/PII. Log a
    # bounded, redaction-safe summary instead.
    logger.error("Invalid user JSON", extra={"error": str(e), "payload_length": len(raw)})
    return None

# ❌ Bad: Silent failure
try:
    parse_user_data(raw)
except:
    pass  # User data silently ignored
2. Error Wrapping (Across Boundaries)

Add context as errors propagate—original error + where + why.

# ✅ Python: Preserve cause
try:
    return repository.find(user_id)
except DatabaseError as e:
    raise UserNotFoundError(f"find user {user_id}") from e

# ✅ Go: Wrap with context
user, err := repo.Find(userID)
if err != nil {
    return nil, fmt.Errorf("find user %s: %w", userID, err)
}
3. Error Classification

Decide recovery strategy based on error type.

def classify_error(error):
    if isinstance(error, (ConnectionError, TimeoutError)):
        return "transient"  # Retry
    elif isinstance(error, (ValueError, KeyError)):
        return "validation"  # Reject, don't retry
    else:
        return "unknown"

# Transient → retry with backoff
# Validation → log and fail
# Fatal → panic
4. Retry with Backoff (for Transient Errors)

Retry flaky operations; don't retry permanent failures.

import time

def retry(func, max_attempts=3, backoff_base=2):
    """Retry with exponential backoff."""
    for attempt in range(max_attempts):
        try:
            return func()
        except (ConnectionError, TimeoutError) as e:
            if attempt < max_attempts - 1:
                wait_time = backoff_base ** attempt
                logger.warning(f"Retry {attempt + 1}/{max_attempts}, waiting {wait_time}s")
                time.sleep(wait_time)
            else:
                raise
        except (ValueError, KeyError):
            raise  # Don't retry validation errors

# Usage
user = retry(lambda: fetch_user(user_id), max_attempts=3)

Read the full file on GitHub · 191 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 191 lines · 32 tokens per session scan A 1d78ade28f32

Subscribe to this mod's changes

error-handling is a cursor rule published in the GitHub repository andr-ca/agentharness (1 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 1,338 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.