Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/T-0-co/t-0-spec-kit-ralphnpx agentmods add skills/t-0-co/t-0-spec-kit-ralph/autonomous-longtaskWrote 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/t-0-co/t-0-spec-kit-ralph/autonomous-longtask)<a href="https://agentmods.dev/skills/t-0-co/t-0-spec-kit-ralph/autonomous-longtask"><img src="https://agentmods.dev/badge/skills/t-0-co/t-0-spec-kit-ralph/autonomous-longtask/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/t-0-co/t-0-spec-kit-ralph/autonomous-longtask"><img src="https://agentmods.dev/badge/skills/t-0-co/t-0-spec-kit-ralph/autonomous-longtask.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00038 | $0.02244 |
| Opus 5.5 | $0.00015 | $0.00898 |
| Sonnet 5.5 | $0.00008 | $0.00449 |
| Haiku 4.5 | $0.00004 | $0.00224 |
Grade A, and why
autonomous-longtask 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Long-Task Development
Dieses Skill optimiert Claude Code für lange, autonome Entwicklungsaufgaben - von mehrstündigen Feature-Implementierungen bis zu Multi-Session-Refactorings.
Wann diesen Skill nutzen
- Komplexe Features: Implementierungen die mehrere Dateien/Services betreffen
- Multi-Step Workflows: Tasks mit 5+ abhängigen Schritten
- Long-Running Tasks: Aufgaben die >30 Min dauern
- Multi-Session Tasks: Arbeit die über Context-Grenzen hinausgeht
Core Principles
1. Loop Closing (Test-Driven)
Jede Code-Änderung muss einen Feedback-Loop schließen:
1. Test schreiben (was soll passieren)
2. Code implementieren
3. Test ausführen → Loop geschlossen
4. Refactor falls nötig
5. Test erneut → Sicherheit
Anti-Pattern (Open Loop):
"Implementiere Feature X"
→ Code geschrieben, keine Verifikation
→ Bugs später entdeckt
Best Practice (Closed Loop):
"Implementiere Feature X mit E2E Test.
Führe den Test nach Implementation aus."
→ Sofortige Verifikation
2. Incremental Progress mit Checkpoints
Niemals alles auf einmal:
❌ Versuchen das komplette Feature zu "one-shotten"
→ Context läuft aus mitten in der Implementierung
→ Nächste Session erbt Chaos
✓ Kleine, getestete Inkremente
→ Jedes Inkrement funktioniert standalone
→ Klare Übergabe zwischen Sessions
Checkpoint-Pattern:
- Nutze
/rewindoderEsc Escfür Rollbacks - Committe nach jedem funktionierenden Inkrement
- Dokumentiere State in
STATUS.mdoderclaude-progress.txt
3. Context-Window Management
Claude Opus 4 kann 200K Tokens, aber:
- Sub-Agents haben eigene Context Windows (isoliert)
- Lange Sessions fragmentieren den Context
claude-progress.txtfür Session-Handoffs nutzen
Sub-Agents für Parallelisierung
Was sind Sub-Agents?
Lightweight Claude-Instanzen mit eigenem Context Window. Nur relevante Ergebnisse kommen zurück zum Orchestrator.
Verfügbare Agent-Typen
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.
- 2mo ago First seen · 379 lines · 38 tokens per session scan A e432ce96f1db
autonomous-longtask is a skill published in the GitHub repository T-0-co/t-0-spec-kit-ralph (10 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 2,244 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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