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 MadAppGang/magus --skill error-recoverygit clone --depth 1 https://github.com/MadAppGang/magusWrote 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/madappgang/magus/error-recovery)<a href="https://agentmods.dev/skills/madappgang/magus/error-recovery"><img src="https://agentmods.dev/badge/skills/madappgang/magus/error-recovery/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/madappgang/magus/error-recovery"><img src="https://agentmods.dev/badge/skills/madappgang/magus/error-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to high
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 →
- high Privilege Escalation · line 251 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 253 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 259 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 671 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Excessive Agency · line 55 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.
- medium Excessive Agency · line 954 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.
- medium Excessive Agency · line 1047 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.
- medium Excessive Agency · line 1048 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00039 | $0.07665 |
| Opus 5.5 | $0.00016 | $0.03066 |
| Sonnet 5.5 | $0.00008 | $0.01533 |
| Haiku 4.5 | $0.00004 | $0.00766 |
Grade A, and why
error-recovery scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Never check `OPENROUTER_API_KEY` or call a provider with `curl` yourself. Keys and routes are How it starts
The opening of the file, as written. The whole thing — 1,000 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Error Recovery
Version: 1.2.0 Purpose: Patterns for handling failures in multi-agent workflows Status: Production Ready
Overview
Error recovery is the practice of handling failures gracefully in multi-agent workflows, ensuring that temporary errors, timeouts, or partial failures don't derail entire workflows. In production systems with external dependencies (AI models, APIs, network calls), failures are inevitable. The question is not "will it fail?" but "how will we handle it when it does?"
This skill provides battle-tested patterns for:
- User escalation (STOP and report before fallback — DEFAULT)
- Timeout handling (external models running longer than expected)
- API failure recovery (401, 500, network errors)
- Partial success strategies (some agents succeed, others fail)
- User cancellation (graceful Ctrl+C handling)
- Missing tools (claudish not installed)
- Out of credits (payment/quota errors)
- Re-running a failed model (only when the user chooses it)
With proper error recovery, workflows become resilient and production-ready.
Core Patterns
Pattern 0: User Escalation (DEFAULT — Read First)
This is the MOST IMPORTANT pattern. It overrides all other patterns when the user has requested a specific model.
Rule: NEVER silently substitute, retry with a different model, or fall back to embedded Claude when the user requested a specific model. STOP and REPORT the failure first.
When this applies:
- User explicitly requested a model (e.g., "use Gemini to redesign X")
- User selected specific models for a task
- Any workflow where the model choice was intentional
When graceful degradation (Patterns 1-7) applies instead:
- Automated pipelines where any result > no result
- User explicitly said "use whatever works"
/teamworkflows where the command already handles failure reporting
The Protocol:
Step 1: Model fails (non-zero exit, empty output, API error, rate limit, binary crash)
Step 2: STOP immediately. Do NOT:
❌ Silently launch a different model
❌ Retry with a different provider prefix
❌ Fall back to embedded Claude without asking
❌ Run `claudish --top-models` or invent model IDs — use the live catalog (`list_models`) instead
❌ Substitute a "similar" model
Step 3: REPORT to the user with:
- What model was requested
- What happened (exact error message)
- How many attempts were made and what was tried
- Actionable options for the user to choose from
Step 4: WAIT for user's decision before proceeding
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 Changed · +4 lines 5b5a0ebade53
- 20d ago Changed · -178 lines 400066862761
- 22d ago Changed · -101 lines 5eb8ce595ac0
- 1mo ago Changed 363a69870907
- 1mo ago First seen · 1,275 lines · 39 tokens per session scan A 6b9b02e054f1
error-recovery is a skill published in the GitHub repository MadAppGang/magus (13 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 7,665 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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