verify-success-after-unknown-error

verify-success-after-unknown-error is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 26 tokens per session (976 once invoked), scanned A, original, MIT.

A checklist for confirming that a file operation succeeded when a tool reports an unclear error.

In plain words
What is it for?
It helps check whether expected files exist, have content, and can be read after code or shell execution.
Why use it?
An unknown error does not always mean the task failed, so checking the filesystem can prevent unnecessary retries and duplicate files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps check whether expected files exist, have content, and can be read after code or shell execution.

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Install with agentmods
npx agentmods add skills/hkuds/openspace/verify-success-after-unknown-error
About the project

OpenSpace is a skill-management layer for AI agents that stores, retrieves, evaluates, shares, and improves reusable workflows. It is intended for people using multiple coding agents who want skills to be reused and refined based on task outcomes. The catalogue provides 200 skills for use with OpenSpace and the agents it supports.

HKUDS/OpenSpace · 7,534 stars · on GitHub

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.

Any agent
npx skills add HKUDS/OpenSpace --skill verify-success-after-unknown-error
Clone the repo
git clone --depth 1 https://github.com/HKUDS/OpenSpace

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for verify-success-after-unknown-error

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/verify-success-after-unknown-error.svg)](https://agentmods.dev/skills/hkuds/openspace/verify-success-after-unknown-error)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/verify-success-after-unknown-error"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/verify-success-after-unknown-error.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 976 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 127
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
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 5.1 $0.00026 $0.00976
Opus 5 $0.00013 $0.00488
Sonnet 5 $0.00005 $0.00195
Haiku 4.5 $0.00003 $0.00098

Measured 4d ago against content hash 2d886251aa7e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

verify-success-after-unknown-error 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 4d 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.

benchmarks/gdpval/skills/verify-success-after-unknown-error/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Verify Success After Unknown Error

Purpose

When execute_code_sandbox or run_shell return "unknown error" messages, the underlying task may have actually succeeded. This skill provides a systematic approach to verify actual completion before assuming failure and retrying unnecessarily.

When to Apply

Use this pattern when:

  • execute_code_sandbox returns "unknown error" but your code may have completed
  • run_shell fails with unclear error messages
  • File creation, modification, or transformation tasks report errors
  • The error message is generic/unspecified rather than a clear failure reason

Verification Steps

Step 1: Check Expected Output Files

After receiving an unknown error, immediately verify if expected files were created:

# Example: Verify file creation after execute_code_sandbox
from tools import list_dir, read_file

# List directory to check if files exist
files = list_dir(path="/workspace/output")
print(files)

# Check specific file existence
expected_files = ["report.pdf", "data.xlsx"]
for f in expected_files:
    try:
        content = read_file(filetype="pdf", file_path=f"/workspace/output/{f}")
        print(f"✓ {f} exists and is readable")
    except:
        print(f"✗ {f} not found or unreadable")

Step 2: Validate File Content/State

Don't just check existence — verify the files have expected content:

# For spreadsheets
file_content = read_file(filetype="xlsx", file_path="/workspace/output/schedule.xlsx")
# Verify expected sheets, columns, or data exist

# For text/json files
file_content = read_file(filetype="txt", file_path="/workspace/output/result.json")
# Parse and validate structure

# For directories
dir_contents = list_dir(path="/workspace/output")
# Verify expected number of files or specific files exist

Step 3: Decision Logic

IF expected files exist AND content is valid:
    → Task succeeded despite error message
    → Proceed to next step without retry
    
ELIF files exist but content is incomplete:
    → Partial success, may need targeted fix
    
ELSE (files missing or corrupted):
    → True failure, retry or debug required

Read the full file on GitHub · 137 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 4d ago First seen · 137 lines · 26 tokens per session scan A 2d886251aa7e

Subscribe to this mod's changes

verify-success-after-unknown-error is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 26d ago), licensed MIT. It adds 26 tokens to every session and 976 once invoked, about $0.0001 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 2026-09-03.

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