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.
npx skills add jmanhype/claude-code-plugin-marketplace --skill reflect-appworld-failuregit clone --depth 1 https://github.com/jmanhype/claude-code-plugin-marketplaceWrote 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.
[](https://agentmods.dev/skills/jmanhype/claude-code-plugin-marketplace/reflect-appworld-failure)<a href="https://agentmods.dev/skills/jmanhype/claude-code-plugin-marketplace/reflect-appworld-failure"><img src="https://agentmods.dev/badge/skills/jmanhype/claude-code-plugin-marketplace/reflect-appworld-failure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jmanhype/claude-code-plugin-marketplace/reflect-appworld-failure"><img src="https://agentmods.dev/badge/skills/jmanhype/claude-code-plugin-marketplace/reflect-appworld-failure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.01611 |
| Opus 5 | $0.00013 | $0.00805 |
| Sonnet 5 | $0.00005 | $0.00322 |
| Haiku 4.5 | $0.00003 | $0.00161 |
Grade A, and why
reflect-appworld-failure 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect on AppWorld Failure
Analyze failed AppWorld tasks to extract specific, actionable learnings that can be added to the playbook.
Purpose
When an AppWorld task fails, the Reflector calls this Skill with error details and failed code. You analyze the failure semantically and generate a high-quality bullet with:
- Specific title describing the pattern
- Detailed content with working code examples
- Relevant tags for retrieval
- Appropriate confidence level
Input Format
The input will be a text description with sections:
# Task
<task instruction>
## Apps
<comma-separated list of apps used>
## Error Type
<error_type: api_misuse, logic_error, timeout, etc.>
## Error Messages
<list of error messages from execution>
## Failed Code Snippet
<relevant code that failed>
## Missing Patterns (from heuristics)
<list of patterns the old system identified>
## Suggested Fixes (from heuristics)
<list of fix suggestions>
Your Analysis Process
-
Identify Root Cause: What was the fundamental mistake?
- Wrong API method name?
- Missing authentication?
- Incorrect data structure access?
- Logic error?
-
Extract Pattern: What general pattern does this represent?
- Is this specific to one app or applies to multiple?
- Is this about API order (login first)?
- Is this about method naming conventions?
- Is this about data validation?
-
Generate Concrete Example: Create working code that demonstrates the CORRECT pattern
-
Write Actionable Bullet: Make it specific enough that the Generator can apply it
Output Format
Return a JSON object with this structure:
{
"bullet": {
"id": "bullet-YYYY-MM-DD-HHMMSS",
"title": "<Specific pattern title>",
"content": "<Detailed explanation with working code example>",
"tags": ["app.<app_name>", "<error_category>", "<pattern_type>"],
"evidence": [
{
"type": "execution",
"ref": "<task_id>",
"note": "<brief note about failure>"
}
],
"confidence": "high|medium|low",
"scope": "app|global"
}
}
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.
- 10d ago First seen · 201 lines · 26 tokens per session scan A 6857a4c0f5df
reflect-appworld-failure is a skill published in the GitHub repository jmanhype/claude-code-plugin-marketplace (27 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 1,611 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 2026-08-30.
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