Results for “tool-failure-handling”

Use when the team needs a strategy for validation errors, API failures, job retries, user-facing error UX, observability, or recovery behavior. Trigger on requests to design error handling across frontend, backend, and integrations.

跨 TypeScript、Python、Go 的健壮错误处理模式——涵盖类型化错误、错误边界、重试策略及优雅降级

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Provides React/Next.js UI components for displaying tool call lifecycle states including pending, running, approval, success, and error, with support for human-in-the-loop approval flows.

Autonomously repairs failed task verification by choosing retry, decompose, prune, or escalate strategies before surfacing to the user.

Fix CI failures by fetching GitHub Actions logs, dispatching dev to fix, verifying locally, and pushing.

Easy debugging skill pack for Content Factory. Use when the user says debug skills, @debug-skills, something is broken, failed pipeline, or bug pack. Auto-loads systematic-debugging, cf-orchestrator, debugging-loop, and bug-fixing workflow.

Design error prevention, detection, and recovery experiences that minimize user frustration.

Design, review, and troubleshoot Salesforce Flow fault handling with error logging and bulk-safe automation paths.

Diagnoses pipeline failures, schema validation errors, ffmpeg crashes, and API errors, then attempts safe automatic recovery.

Assesses new tools, technologies, and integration options for adoption, comparing vendors and recommending implementations.

当遭遇挫折、失败或结果不如预期时，用于将负面经验转化为成长燃料

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

Repairs failed task verification by choosing a strategy: retry with adjustments, decompose into sub-tasks, prune infeasible tasks, or escalate to the user.

Diagnoses and fixes failing installed skills by reading the SKILL.md and error output, classifying the failure, applying the smallest fix, and attaching a verification recipe.

Systematically diagnose and fix software bugs by analyzing error messages, stack traces, logs, and runtime behavior across multiple languages. Use when the user requests debugging or provides relevant inputs for this workflow.

HASH error handling patterns using error-stack crate. Use when working with Result types, Report types, defining custom errors, propagating errors with change_context, adding context with attach, implementing Error trait, or documenting error conditions in Rust code.

Autonomous error recovery — detect failures, diagnose root cause, apply fixes, and resume without stopping

Runbook skill for failures: cron error, PA failure, cascade, gateway disconnect, semantic DB stale. Walks: detect → classify → diagnose → notify → log. Replaces ad-hoc failure handling. Triggers: "cron failed", "X is broken", "cascade", "incident", "gateway down", "PA failure".

Use this skill for CI log analysis, local reproduction, root cause isolation, targeted fixes, rerun strategy. Trigger when the task involves programming work related to CI Failure Triage, implementation, audits, debugging, strategy, or validation.

Rehearse

Audit a codebase for silent failures, swallowed exceptions, and observability gaps across Sentry and Langfuse, then produce a phased fix plan. Use when the user says "errors aren't showing in Sentry", "things fail silently", "empty catch blocks", "add error handling", "check my Langfuse tracing", or is hardening.

Provides patterns for robust error handling across TypeScript, Python, and Go, including typed errors, error boundaries, retries, circuit breakers, and user-facing error messages.

Handle errors as values using fp-ts Either and TaskEither to write cleaner, more predictable TypeScript code.

Urgent issue classification, root cause analysis, and fast-path routing for production hotfixes

Handle errors as values using fp-ts Either and TaskEither, replacing try/catch with predictable, type-safe error handling patterns.

Conduct failure mode and effects analyses. TRIGGERS - Use when user needs help with fmea-guide related tasks.

Identify the right tool for a process step. Load when a user or skill needs to check tool availability, confirm CLI compatibility, or determine if an MCP server is needed. Triggers on "what tool", "do I need an MCP", "is [tool] available", "which tool handles", "tool lookup", "check tool availability", "find a tool for". Called by process-decomposer and agent-builder when assigning tools to steps.

Helps users report issues with GTM skills — incorrect advice, broken activation, missing context, or unexpected behavior. Guides through gathering the right details (skill name, prompt used, actual vs expected output, context files present) and generates a properly formatted GitHub issue. Use when users say: 'this skill gave wrong advice', 'report a bug', 'file an issue', 'skill isn't working', 'wrong output', 'skill didn't activate', 'bad recommendation', 'incorrect behavior', or 'something is broken'.

Stop throwing everywhere - handle errors as values using Either and TaskEither for cleaner, more predictable code

Stop throwing everywhere - handle errors as values using Either and TaskEither for cleaner, more predictable code

Error Recovery Playbook

Imported skill tools from langchain

Error handling review — silent failure detection, catch block analysis, error logging.

Run tests and systematically fix all failing tests using smart error grouping. Use when user asks to fix failing tests, mentions test failures, runs test suite and failures occur, or requests to make tests pass.