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Error Recovery

CommunityPopular
bradygaster
error-recovery

Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.

Overview

Publisherbradygaster
Repositorysquad
Skill nameerror-recovery
Stars
3.3K
Forks
506
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bradygaster on GitHub. Read the source before you install it.

Installation

Install the Error Recovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/error-recovery
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bradygaster/squad.git /tmp/squad
mkdir -p .claude/skills
cp -r /tmp/squad/packages/squad-cli/templates/skills/error-recovery .claude/skills/error-recovery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Error Recovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Error Recovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Error Recovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Error Recovery Patterns

Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.


1. Retry with Backoff

When: Transient failures — API timeouts, rate limits, network errors, temporary service unavailability.

Pattern:

  1. Wait briefly, then retry (start at 2s, double each attempt)
  2. Maximum 3 retries before escalating
  3. Log each attempt with the error received

Example: API call returns 429 Too Many Requests → wait 2s → retry → wait 4s → retry → wait 8s → retry → escalate if still failing.


2. Fallback Alternatives

When: Primary tool or approach fails and an alternative exists.

Pattern:

  1. Attempt primary approach
  2. On failure, identify alternative tool/method
  3. Try the alternative with the same intent
  4. Document which alternative was used and why

Example: Primary CLI tool fails → fall back to direct API call for the same operation.


3. Diagnose-and-Fix

When: Build failures, test failures, linting errors — structured errors with actionable output.

Pattern:

  1. Read the full error output carefully
  2. Identify the root cause from error messages
  3. Attempt a targeted fix
  4. Re-run to verify the fix
  5. Maximum 3 fix-retry cycles before escalating

Example: Build fails with a type error → check for missing import → add it → rebuild.


4. Escalate with Context

When: Recovery attempts have been exhausted, or the failure requires human judgment.

Pattern:

  1. Summarize what was attempted and what failed
  2. Include the exact error messages
  3. State what you believe the root cause is
  4. Suggest next steps or who might be able to help
  5. Hand off to the coordinator or the appropriate specialist

Example: After 3 failed build attempts → "Build fails on line 42 with null reference. Tried X, Y, Z. Likely a design issue in the Foo module. Recommend the code owner review."


5. Graceful Degradation

When: A non-critical step fails but the overall task can still deliver value.

Pattern:

  1. Determine if the failed step is critical to the task outcome
  2. If non-critical, log the failure and continue
  3. Deliver partial results with a clear note of what was skipped
  4. Offer to retry the skipped step separately

Example: Generating a report with 5 sections — section 3 data source is unavailable → produce the report with 4 sections, note that section 3 was skipped and why.


Applying These Patterns

Each agent should reference these patterns in their charter's ## Error Recovery section, tailored to their domain. The charter should list the agent's most common failure modes and map each to the appropriate pattern above.

Selection guide:

Failure TypePrimary PatternFallback Pattern
Network/API transientRetry with BackoffEscalate with Context
Tool/dependency missingFallback AlternativesEscalate with Context
Build/test errorDiagnose-and-FixEscalate with Context
Auth/permissionsRetry with BackoffEscalate with Context
Non-critical data missingGraceful Degradation—
Unknown/novel errorEscalate with Context—

Frequently asked questions

What does the Error Recovery AI skill do?

Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.

Why use Error Recovery on TypingMind?

Because you install it once and use it with any model. Error Recovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Error Recovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/error-recovery. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Error Recovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Error Recovery?

As many as you like. As long as a model supports skills, you can use Error Recovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Error Recovery AI skill free?

Yes. It is published on GitHub by bradygaster under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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