fix-errors

Guidance for investigating unhandled errors reported by the VS Code error telemetry dashboard, which collects crash and failure data from users.

In plain words
What is it for?
Use it to trace stack traces and data flow, identify the source of malformed data, and plan a corrective fix.
Why use it?
It helps find where invalid data was created instead of hiding the failure at the line where the crash appears.

Skill for Claude CodeCodex

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 skills/malwarebo/nyrve/fix-errors
Any agent
npx skills add malwarebo/nyrve --skill fix-errors
Clone the repo
git clone --depth 1 https://github.com/malwarebo/nyrve

Made for: Claude Code, Codex.

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 984 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 $0.00075 $0.00984
Opus 5 $0.00037 $0.00492
Sonnet 5 $0.00015 $0.00197
Haiku 4.5 $0.00007 $0.00098

Measured 2d ago against content hash e57d5aafea7c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix-errors 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 2d ago.

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.

.github/skills/fix-errors/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When fixing an unhandled error from the telemetry dashboard, the issue typically contains an error message, a stack trace, hit count, and affected user count.

Approach

1. Do NOT fix at the crash site

The error manifests at a specific line in the stack trace, but the fix almost never belongs there. Fixing at the crash site (e.g., adding a typeof guard in a revive() function, swallowing the error with a try/catch, or returning a fallback value) only masks the real problem. The invalid data still flows through the system and will cause failures elsewhere.

2. Trace the data flow upward through the call stack

Read each frame in the stack trace from bottom to top. For each frame, understand:

  • What data is being passed and what is expected
  • Where that data originated (IPC message, extension API call, storage, user input, etc.)
  • Whether the data could have been corrupted or malformed at that point

The goal is to find the producer of invalid data, not the consumer that crashes on it.

3. When the producer cannot be identified from the stack alone

Sometimes the stack trace only shows the receiving/consuming side (e.g., an IPC server handler). The sending side is in a different process and not in the stack. In this case:

  • Enrich the error message at the consuming site with diagnostic context: the type of the invalid data, a truncated representation of its value, and which operation/command received it. This information flows into the error telemetry dashboard automatically via the unhandled error pipeline.
  • Do NOT silently swallow the error — let it still throw so it remains visible in telemetry, but with enough context to identify the sender in the next telemetry cycle.
  • Consider adding the same enrichment to the low-level validation function that throws (e.g., include the invalid value in the error message) so the telemetry captures it regardless of call site.

4. When the producer IS identifiable

Fix the producer directly:

  • Validate or sanitize data before sending it over IPC / storing it / passing it to APIs
  • Ensure serialization/deserialization preserves types correctly (e.g., URI objects should serialize as UriComponents objects, not as strings)

Read the full file on GitHub · 72 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. 2d ago First seen · 72 lines · 75 tokens per session scan A e57d5aafea7c

Subscribe to this mod's changes

fix-errors is a skill published in the GitHub repository malwarebo/nyrve (5 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 984 once invoked, about $0.0004 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.

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