waza: Skill for Claude Code

.github/skills/error-recovery/SKILL.md

error-recovery is a skill for Claude Code, Codex from microsoft/waza. It costs 24 tokens per session (785 once invoked), scanned A, a copy of error-recovery, MIT.

A shared guide for recovering from failures while AI agents work. It describes how to retry temporary errors, use alternatives when a tool fails, and investigate structured failures such as build or test errors.

In plain words
What is it for?
It helps handle timeouts and rate limits with backoff, switch to fallback methods, read error output, apply targeted fixes, and retry verification.
Why use it?
It gives agents a consistent response to failure instead of stopping at the first error. This can distinguish temporary service problems from issues that need a code change or escalation.

Skill for Claude CodeCodex ✓ vendor

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

This is microsoft/waza's own configuration. It tells Claude Code and Codex how to work on waza itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything waza configures →

About the project

microsoft/waza is a Go command-line tool for building and evaluating AI agent skills through test suites, benchmarks, and model comparisons. It is for developers who need to measure and improve how reliably agent skills work. The catalogue entries are Waza's own skills, instructions, agent, and MCP integration.

microsoft/waza · 1,420 stars · on GitHub · microsoft.github.io

Reuse

Borrowing it

Nothing to install: this file belongs to microsoft/waza. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/microsoft/waza/main/.github/skills/error-recovery/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/microsoft/waza

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 error-recovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/waza/error-recovery/github.svg)](https://agentmods.dev/skills/microsoft/waza/error-recovery)
Your own site
<a href="https://agentmods.dev/skills/microsoft/waza/error-recovery"><img src="https://agentmods.dev/badge/skills/microsoft/waza/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.

agentmods 80×15 button for error-recovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/waza/error-recovery"><img src="https://agentmods.dev/badge/skills/microsoft/waza/error-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 785 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.
Origin 100% copy Near-identical to another mod 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 $0.00024 $0.00785
Opus 5.5 $0.00010 $0.00314
Sonnet 5.5 $0.00005 $0.00157
Haiku 4.5 $0.00002 $0.00078

Measured 1mo ago against content hash a6bc62ea076c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

error-recovery 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 1mo 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.

Origin

This is a copy

100% identical to error-recovery — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/skills/error-recovery/SKILL.md · 100 lines

How it starts

The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 100 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. 1mo ago First seen · 100 lines · 24 tokens per session scan A a6bc62ea076c

Subscribe to this mod's changes

error-recovery is a skill published in the GitHub repository microsoft/waza (1,420 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 785 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to error-recovery, differing in 0 lines, and is treated as a copy.

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