Skills Janitor vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-11-13
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Skills Janitor or Temporal AI: which should you choose?

DimensionSkills JanitorTemporal AI
PricingFree, MIT-licensedFreemium (paid Cloud tiers)
CategoryContext-hygiene CLI for Claude Code/Codex skillsDurable execution runtime for AI agents and workflows
Install/RunPlugin marketplace, npx, or git clone (Bash + Python 3 + curl)SDKs in Go, Java, Python, TypeScript, .NET, PHP, Ruby, Rust
Recent milestonev1.8: project in maintenance mode (2026-09-01)Serverless Workers for Cloud Run in public preview (2026-10-05)
Best fitDevelopers trimming skill/MCP context wasteTeams with long-running state that must survive crashes

Don't shortlist these against each other — they solve different problems. Buy Temporal if you need a runtime that keeps AI agent and workflow state alive across crashes, retries, and abandoned sessions, with Saga compensation and durable timers. Choose Skills Janitor if your pain is a sprawl of Claude Code and Codex skills, duplicates, and MCP servers eating your context — and note it went into maintenance mode in v1.8 now that Claude Code ships /skill-doctor and /doctor natively.

Skills Janitor
Skills Janitor

Skills Janitor audits Claude Code and Codex skills, subagents and MCP servers to cut wasted context

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Free
Freemium
Plans
FreeFree
FreeFree
Pay-As-You-GoFrom $50/1M actions
Business Support Add-On$500/mo
Enterprise and Mission CriticalCustom
Popularity
8 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
CLI
WebAPI
Categories
💻 Code & Development
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
FeaturesSkills JanitorTemporal AI
Interactive swipe TUI (/janitor-swipe) with delete, keep, skip, undo and inspect keys
Swipe deck sorted heaviest-and-least-used first so likely waste surfaces early
MCP server triage (v1.7) across user, project, .mcp.json and plugin-bundled servers
Cross-references MCP servers against real session usage records
Swiping an MCP server left removes its config entry and leaves a timestamped .bak backup
Cross-scope duplicate detection using Jaccard similarity above a 30% threshold
Token cost reporting via /janitor-value: always-loaded descriptions vs on-demand bodies
Usage counts from real session transcripts, including auto-triggered skills
/janitor-report health check for inventory, duplicates and broken skills, with --brief
/janitor-fix --prune removes broken symlinks and empty directories
Prompt-injection heuristic scan (v1.6+) for instruction overrides, hidden comments, zero-width unicode and base64
Pre-install security and overlap scan via /janitor-discover on a GitHub search or URL
PASS / REVIEW / RISK verdicts on installed skills
Zero dependencies, offline-capable, no telemetry — runs on Bash, Python 3 and curl
Natural-language invocation ("check my skills", "which skills are wasting context?")
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Rust SDK generally available (2026-09-04)
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Serverless Workers for Google Cloud Run, public preview (2026-10-05)
Serverless Workers for AWS Bedrock AgentCore, pre-release (2026-09-18)
Serverless Workers for AWS Lambda, public preview (2026-08-03)
Native Task Queue priority and fair distribution, GA (2026-05-05)
Durable Timers that sleep for months, plus cron Schedules with backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to their version; Replay tests validate against real histories
IntegrationsSkills JanitorTemporal AI
Claude Code
OpenAI Codex
GitHub
OpenAI Agents SDK
Google ADK
AWS Bedrock AgentCore
Google Cloud Run
AWS Lambda
Kubernetes
GCP Marketplace
Azure
Slack

What do real users say about Skills Janitor vs Temporal AI?

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Skills Janitor

35 mentions across 3 sources · 39% positive — critical (weighted across 3 sources)

YouTube, Product Hunt, Lemmy

What users praise

  • • Usage stats drawn from real session transcripts, including auto-triggered skills
  • • Dedup uses Jaccard similarity at a 30% threshold to catch overlapping skills
  • • Token cost reporting separates always-loaded descriptions from on-demand bodies
  • • MCP triage ranks connected-but-never-called servers using actual transcript records

What frustrates them

  • • Project is in maintenance mode; no active feature development expected
  • • Claude Code's native doctor commands now cover the main trim-context use case
  • • Plugin skills and bundled MCP servers are flagged but not individually deletable
  • • Little independent evidence outside Product Hunt; Reddit, HN and GitHub returned nothing

Researched Oct 20, 2026

Temporal AI

No verifiable community signal. We scanned public discussion on Nov 7, 2026 and found posts matching the name “Temporal AI”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

How do Skills Janitor and Temporal AI compare feature by feature?

Temporal's product is a programming model: you write workflow logic in ordinary code, and the service persists state at every step so a crashed worker or abandoned session resumes where it stopped, with no checkpointing code. Activities retry automatically with backoff, four timeout classes, and heartbeating; Signals, Queries, and Updates mutate a running execution mid-flight; Workflow Streams add interactivity. AI-specific work is covered via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities, plus Serverless Workers for Cloud Run (public preview) and Bedrock AgentCore (pre-release). Saga patterns via compensating transactions handle rollback; durable timers sleep for months. Skills Janitor does none of this. It is a CLI that inventories skills, subagents, and MCP servers across user, project, codex, and plugin scopes, then lets you swipe-delete waste in a TUI sorted heaviest-and-least-used first. It cross-references MCP servers against real session usage, flags duplicate skills via Jaccard similarity above 30%, reports token cost of always-loaded descriptions, and scans for prompt-injection heuristics. It deletes only MCP config entries (leaving .bak backups) and flags plugin-bundled skills for review rather than deleting them. One is production infrastructure; the other is local developer hygiene.

Which is cheaper, Skills Janitor or Temporal AI?

Temporal is freemium: an open-source path plus paid Cloud tiers, with the enterprise-focused features listed as best-fit signals — SAML SSO, audit logging, SOC 2/HIPAA, and an SLA-backed support path. The static facts don't publish plan prices, so budget for a Cloud conversation if you need those controls; self-hosting trades license cost for operational effort. Skills Janitor is free and MIT-licensed, installs via plugin marketplace, npx skills add, or git clone, needs only Bash, Python 3, and curl, runs offline, and collects no telemetry. There is no paid tier and, per v1.8, no roadmap of new features — the project is in maintenance mode. Comparing the two on price is meaningless because the cost structures answer different questions: Temporal asks what a failure of long-running state costs you, while Skills Janitor asks whether token waste in your skill deck is worth five minutes of swiping.

Who should pick Skills Janitor, and who should pick Temporal AI?

  • AI agent team shipping long-running runs
    Pick: Temporal AI

    Agents must survive crashes, retries, and abandoned sessions; durable state plus retrying Activities is the whole point.

  • Platform engineer orchestrating multi-step microservices
    Pick: Temporal AI

    Automatic retries, four timeout classes, and Saga compensation replace hand-rolled recovery code.

  • Developer with skill sprawl in Claude Code and Codex
    Pick: Skills Janitor

    The swipe TUI plus /janitor-report surfaces duplicates, broken symlinks, and heaviest-least-used skills fast.

  • Security-minded dev vetting third-party skills
    Pick: Skills Janitor

    /janitor-discover and the prompt-injection heuristic scan check instruction overrides, zero-width unicode, and base64 before install.

  • Claude Code-only user wanting context trimming
    Pick: Skills Janitor

    Still works, but v1.8 notes Claude Code's native /skill-doctor and /doctor now cover the core case, so weigh whether you need the extra audit depth.

Frequently Asked Questions

Skills Janitor vs Temporal AI: which should you choose?

Don't shortlist these against each other — they solve different problems. Buy Temporal if you need a runtime that keeps AI agent and workflow state alive across crashes, retries, and abandoned sessions, with Saga compensation and durable timers. Choose Skills Janitor if your pain is a sprawl of Claude Code and Codex skills, duplicates, and MCP servers eating your context — and note it went into maintenance mode in v1.8 now that Claude Code ships /skill-doctor and /doctor natively.

Can Skills Janitor help me run AI agents reliably?

No. It audits skills, subagents, and MCP server configurations for context waste and duplicates; it does not execute or persist workflows.

Does Temporal manage my Claude Code or Codex skill files?

No. Temporal is a runtime for workflow and agent code in its SDK languages; it does not inventory local skill directories.

What happened to Skills Janitor development?

Per the 2026-09-01 release, v1.8 moved the project into maintenance mode now that Claude Code ships /skill-doctor, /doctor, /doctor prompt-audit, and /skills natively; bug fixes and PRs are still welcome.

Which languages can I write Temporal workflows in?

Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust; the Rust SDK reached general availability on 2026-09-23.

Does Skills Janitor delete plugin-bundled skills?

It only flags those for plugin review; deletion coverage is limited to individual skills and MCP server config entries, the latter leaving a timestamped .bak backup.

Is any of this data sent to a server?

Skills Janitor runs offline and collects no telemetry per its description; for Temporal Cloud data handling, review the vendor's terms — the provided facts don't specify.

What else are Skills Janitor and Temporal AI compared with?

Where can you read more about Skills Janitor and Temporal AI?

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Analysis generated by our model pipeline from live data: